Lowell v. Lyft, Inc.

Full title: HARRIET LOWELL, et al., Plaintiffs, v. LYFT, INC., Defendant.

Court: United States District Court, S.D. New York

Date published: Sep 30, 2024

17-CV-06251 (PMH) (S.D.N.Y. Sep. 30, 2024)

Opinion

17-CV-06251 (PMH)

09-30-2024

HARRIET LOWELL, et al., Plaintiffs, v. LYFT, INC., Defendant.

PHILIP M. HALPERN, UNITED STATES DISTRICT JUDGE

OPINION & ORDER

PHILIP M. HALPERN, UNITED STATES DISTRICT JUDGE

Harriet Lowell (“Ms. Lowell”) and Westchester Disabled on the Move, Inc. (“WDOMI,” and together, “Plaintiffs”) bring this class action against Lyft, Inc. (“Lyft” or “Defendant”) for violations of the Americans with Disabilities Act of 1990 (“ADA”), 42 U.S.C. §§ 12101 et seq. and New York State Human Rights Law (“NYSHRL”), N.Y. Exec. Law §§ 296 et seq. (Doc. 20).¹Plaintiffs allege that Lyft discriminates against individuals in 96% of its service regions (“NonAccess Regions”) who require wheelchair accessible vehicles (“WAVs”) to travel, and offer “Access mode” in only nine regions (“Access Regions”).² (Id.). Plaintiffs seek injunctive relief, including orders enjoining Lyft from operating its WAV programs and Access mode in a discriminatory manner pursuant to 42 U.S.C. §§ 12182, 12184, and the NYSHRL, and directing Lyft to implement a number of remedial measures. (Doc. 20; Doc. 421 at 21-22).

1 This matter proceeded before Judge Roman prior to its reassignment to this Court on April 3, 2020. On November 23, 2022, the Court dismissed, on consent of the parties, Plaintiffs' fifth claim for relief for declaratory judgment. (Doc. 323). On October 2, 2023, Plaintiffs voluntarily dismissed their third and fourth claims for relief under the New York City Human Rights Law (“NYCHRL”), N.Y. City Admin. Code § 8101, et seq. (Doc. 393). Thus, only the first and second claims for relief remain extant. (See Doc. 421).

2 The Court adopts the nomenclature used by Lyft. As set forth in more detail herein, Lyft organizes its coverage areas into more than 300 geographic regions (“Regions”) nationwide. “Access Regions” are the nine Regions in which Lyft offers a selection on its App called “Access mode” which is a mode that gives passengers the option to travel in a WAV and drivers to give rides in their WAVs. “Non-Access Regions” are all the other Regions in the nation in which Access mode does not appear as an option in the App.

The Court conducted a bench trial in this action from July 8, 2024 to July 12, 2024. The parties subsequently filed post-trial briefs and response briefs. (Doc. 438, “Lyft Br.”; Doc. 440, “Pl. Br.”; Doc. 441, “Lyft Opp.”; Doc. 442, “Pl. Opp.”).

This Opinion and Order constitutes the Court's findings of fact and conclusions of law for purposes of Federal Rule of Civil Procedure 52(a)(1). To the extent any statement labeled as a finding of fact is a conclusion of law, it shall be deemed a conclusion of law, and vice versa.

Notwithstanding the laudable purpose for which this action was brought, the requirements of the ADA and NYSHRL for these types of claims for relief have not been met. A review of the proof amassed at trial, as analyzed under applicable law, demonstrates that Plaintiffs failed to sustain their burden of proof that the proposed modifications which Plaintiffs seek would result in WAV transportation services in the Non-Access Regions.

For the reasons that follow, the Court concludes that the Complaint must be dismissed with prejudice and judgment must be entered in favor of Defendant.

BACKGROUND

I. The Parties

Ms. Lowell is a citizen of Westchester County and a resident of White Plains, New York, who relies on a motorized scooter for travel. (SF ¶ 1).³ She began progressively losing the ability to walk in 1997 and has used a motorized scooter since 2008. (JE 1 ¶¶ 4-5).⁴ WDOMI is a nonprofit community-based organization headquartered in Yonkers, New York. (SF ¶ 2). A significant percentage of WDOMI's constituents, clients, and staff are persons with disabilities, including mobility-related disabilities. (Id. ¶ 5). WDOMI is staffed, directed, and operated by the individuals with disabilities that it seeks to serve, including wheelchair-users. (Id.).

3 The parties submitted a joint statement of Stipulated Facts. (Doc. 421 at 10-14). The Court cites to the parties' stipulated facts as “SF__ .”

4 The affidavits constituting direct testimony of certain witnesses were each marked at trial as Joint Exhibits. Accordingly, the Court cites to the affidavits as “JE__ .”

Plaintiffs are representatives of three classes certified by the Court on March 24, 2023: (1) all residents of or visitors to any and all regions serviced by Lyft, aside from Lyft's Access Regions or New York City (“NYC”), who require WAVs for vehicular transportation, and who are denied equal access to Lyft's transportation services (the Non-Access Region Class) (represented by Ms. Lowell and WDOMI and asserting claims under the ADA); (2) all residents of or visitors to any and all regions serviced by Lyft in New York State aside from NYC who require WAVs for vehicular transportation, and who are denied equal access to Lyft's transportation services (the New York State Other Than NYC Class) (represented by Ms. Lowell asserting claims under the ADA and NYSHRL and WDOMI asserting claims under the ADA); and (3) all residents of or visitors to Westchester County who require WAVs for vehicular transportation, and who are denied equal access to Lyft's transportation services (the Westchester Class) (represented by Ms. Lowell asserting claims under the ADA and NYSHRL and WDOMI asserting claims under the ADA). (Doc. 365).⁵

5 The Court's Opinion and Order adopting Magistrate Judge Krause's Report and Recommendation concerning class certification is available on commercial databases. Lowell v. Lyft, Inc., No. 17-CV-06251, 2023 WL 2622925 (S.D.N.Y. Mar. 24, 2023).

Lyft is a business corporation incorporated under the laws of the State of Delaware, with its principal place of business in San Francisco, California. (SF ¶ 6). Lyft launched what it refers to as its peer-to-peer marketplace for on-demand ridesharing in or about 2012. (Id. ¶ 7). Lyft operates multimodal transportation networks in the United States that offer access to a variety of transportation options through Lyft's platform and App. (Id. ¶ 8). Lyft's transportation network is designed to address a wide range of mobility needs. (Id. ¶ 9). The Lyft network spans rideshare, car rentals, bikes, scooters, and transit. (Id.). Lyft's stated mission is to “improve people's lives with the world's best transportation.” (Id. ¶ 10).

II. The App, Access Regions, Non-Access Regions, and Modes

Lyft's ridesharing platform is a two-sided technology platform premised on principles of supply and demand. (JE 9 ¶ 5). Members of the general public may download the Lyft App and agree to the Terms of Service. (SF ¶ 11). Drivers on the Lyft ridesharing platform must agree to the Terms of Service and Driver Addendum and meet applicable state and/or local regulatory vehicle and driver requirements. (Id. ¶ 12). Documentation requirements vary by region. (Id.). Lyft's policy, to which drivers on the platform must adhere, precludes drivers from discriminating against riders with disabilities; and obliges them to make reasonable accommodations as required by law, including for those riders who travel with service animals, and riders with wheelchairs that can be folded for safe and secure storage in the trunk or back seat. (JE 2 ¶¶ 3-4). The Lyft Terms of Service and the Driver Addendum also govern charges, fares, and payments. (SF ¶ 13).

Lyft organizes its coverage areas into more than 300 geographic Regions nationwide. (Id. ¶ 14). Lyft offers a variety of ride modes on the App, but does not offer every ride mode in every Region. (Id. ¶ 15). Lyft offers its standard mode service (“Standard mode”)⁶ in all 50 states. (Id. ¶ 16). Lyft makes Standard mode available in all regions where it operates, regardless of population density, wait time, number of available vehicles, or any other considerations or metrics. (Id. ¶ 17). Standard mode appears in every Region where Lyft operates as an available ride mode when a user inserts their destination address. (Id. ¶ 18). When any mode (other than Access mode) is available on the Lyft platform in a Region, riders are able to request a ride in that “mode” at any time, 24 hours a day, but Lyft makes no guarantee that the ride request will be matched or that a driver will be available or accept the ride request. (Id. ¶ 19).

6 “Standard mode,” as used by Lyft, is a service mode offered on the App for up to four riders (as opposed to “XL mode” for up to six riders, for example) that connects riders to drivers with classic cars (as opposed to SUVs, luxury vehicles, or WAVs, for example). (See JE 2 ¶ 31; see also JE 1 ¶¶ 15, 20; JE 9 ¶¶ 15-16).

Depending on a user's location, the App displays information specific to that location, such as available ride modes, price, and availability. (Id. ¶ 20). The App, in addition to ridesharing options, may show local information such as public transportation options, bike share, or rental car offerings. (Id.). Wait times (i.e., the amount of time between the time a ride is requested and the time when the driver arrives) and completion rates (i.e., the percentage of requested rides that are completed) on the Lyft platform vary by location and by mode. (Id. ¶ 21). Lyft does not guarantee any service levels or outcomes to its users, including wait times, completion rates, or that a requested ride will be completed. (Id. ¶ 22). Lyft does not restrict its Standard mode in any Region based upon the level of service, including wait times and completion rates. (Id. ¶ 23).

Lyft offers Standard mode solely through an independent contractor (“IC”) model. (Id. ¶ 24). The IC model refers to drivers who personally own or rent a car and use Lyft's App to connect with riders. (Id. ¶ 25). These IC drivers set their own hours and drive where they want to drive. (Id.).

Lyft, to date, has launched Access mode⁷ in its Access Regions, which include nine cities in the United States: Boston, Massachusetts; Chicago, Illinois; Dallas, Texas; Los Angeles, California; New York, New York; Philadelphia, Pennsylvania; Portland, Oregon; Phoenix, Arizona; and San Francisco, California. (Id. ¶ 32). Lyft offers Access mode in the Access Regions using two models: the IC model and a model referred to as the “Partner” or “W-2” model. (Id. ¶ 37). As in the case of Standard mode, the IC model for Access mode depends on drivers who personally own or rent WAVs. (Id. ¶ 38). WAVs are vehicles built to accommodate fixed-frame wheelchairs, and typically feature a wheelchair ramp or lift, a lowered floor to accommodate the equipment, and a securement device to keep the wheelchair in place when the vehicle is in motion. (Id. ¶ 27). The IC WAV drivers, like other IC drivers on the Lyft platform, set their own hours and drive where they want to drive. (Id. ¶ 38).

7 “Access mode,” as used by Lyft, is a service mode offered on the App in select Regions that connects riders to drivers with WAVs. (See JE 2 ¶ 31; see also JE 1 ¶¶ 15, 20; JE 9 ¶¶ 15-16).

The “Partner” or “W-2” model, unlike the IC model, relies on services from third-party transportation companies (with whom Lyft contracts) to provide WAVs and WAV drivers. (Id. ¶ 39). Under the W-2 model, Lyft pays the third-party companies a negotiated hourly rate (that varies by city and by company) for a driver and WAV. (Id. ¶ 40). The third-party companies, in exchange for the hourly rate, provide the contracted-for number of WAVs and drivers to drive the WAVs on the Lyft platform. (Id.). Lyft does not offer Access mode in Regions other than the Access Regions. (Id. ¶ 35).

III. The Instant Lawsuit

Plaintiffs commenced this action on August 17, 2017, describing this action as one seeking the provision of “reliable transportation options.” (Doc. 1 ¶ 4; see also id. ¶¶ 8, 97-100). Plaintiffs brought claims under the ADA, NYSHRL, and the NYCHRL. (Id. ¶¶ 118-159). The NYCHRL claims concerned the putative NYC subclass who would have been residents and visitors of NYC (had such a class been certified, and had Plaintiffs not withdrawn these claims for relief). NYC is an Access Region where WAV users seeking a Lyft WAV could open the App and request a WAV.

The thrust of the action, however, is not merely for the opportunity to request a WAV through the App. As Plaintiffs' counsel stated in his opening, “[t]his case is about this Court enforcing compliance with the [ADA and NYSHRL] to end Lyft's discrimination against people with disabilities who want access to transportation.” (Trial Tr. at 5:20-23 (emphasis added)).⁸ Plaintiffs alleged, in the Complaint and in their Amended Complaint, that “[b]y forcing users” with disabilities “to wait significantly longer to obtain rides from wheelchair-accessible vehicles than other users wait to obtain rides through its transportation services,” Lyft denied individuals “full and equal enjoyment” of its services “in violation of Title III of the ADA.” (Doc. 1 ¶ 130; Doc. 20 ¶ 137). The Amended Complaint pleads two extant claims, one brought under the ADA and the other under the NYSHRL. The gravamen of the ADA claim is as follows:

8 The Court cites to the trial transcript as “Trial Tr. __.”

126. Title III of the ADA prohibits discrimination on the basis of disability in the full and equal enjoyment of specified public transportation services provided by private entities primarily engaged in the business of transporting people and whose operations affect commerce. 42 U.S.C. § 12184....

131. Title III of the ADA also prohibits discrimination on the basis of disability in the full and equal enjoyment of services provided by places of public accommodations. 42 U.S.C. § 12182. Public accommodations, under the ADA, explicitly include travel services. 42 U.S.C. § 12181(7)(f) ....

135. Through its ongoing policies and procedures, the opportunities that Lyft offers people with mobility disabilities to participate in or benefit from it services, advantages, and accommodations are not equal to the opportunities that Lyft provides to other individuals. 49 U.S.C. § 12182(b)(1)(A)(ii)....

138. By failing to make reasonable modifications to its policies, practices, and procedures to make wheelchair accessible vehicles available with equivalent reliability and similar wait times as inaccessible vehicles, Defendant denies users of motorized and other non-folding wheelchairs, including Plaintiff Lowell, WDOMI members, and class members, full and equal enjoyment of Defendant's transportation service in violation of Title III of the ADA.

(Doc. 20 ¶¶ 126, 131, 135, 138). As to Plaintiffs' state law claim, the essence is as follows: “Defendant's deliberate failure to equip its vehicles and/or to require its drivers to operate accessible vehicles for the benefit of persons with disabilities requesting its services is an unlawful and prohibited discriminatory practice” and “[a]s a direct and proximate result of Defendant's violations of the NYSHRL, Plaintiff and members of the New York State Subclass have been injured as set forth herein.” (Id. ¶¶ 149-150).

After the close of discovery, on August 26, 2022, Plaintiffs moved for class certification, maintaining the position that this case was about transportation and not the App. (See Doc. 338). Indeed, and in light of Plaintiffs' representations, the Court held that this case concerned “reasonable modifications” to Lyft's “policies, practices, and procedures” that are “necessary to afford on-demand WAV service” “with equivalent reliability and similar wait times as inaccessible vehicles.” (Id. at 3, 10).

Plaintiffs' theory has shifted, however, beginning with their pretrial memorandum (Doc. 429), at trial, and since they rested their case at trial. Plaintiffs no longer describe the relief sought as access to reliable transportation-Plaintiffs now take the position that they merely seek the opportunity to request a WAV through the Lyft App, regardless of whether one is available and without any guarantee that they would be matched with a ride. (See, e.g., Pl. Br. at 8).

IV. Plaintiffs' Proof at Trial ⁹

9 Some of the proof by live testimony that Plaintiffs attempted to elicit is based upon compound and lengthy questions which assume a variety of facts, and to which the witness answered “yes” or “no.” Evidence obviously comes from the witnesses' testimony, and not the lawyer's questions. See, e.g., United States v. McCarth y, 54 F.3d 51, 56 (2d Cir.) (“[Q]uestions asked by counsel are not evidence, unlike the testimony of witnesses.”), cert. denied, 516 U.S. 880 (1995). During this trial, some of the evidence directly related to the burden of proof failed to come in as a result of this process.

With respect to Plaintiffs' case, the Court received direct testimony by affidavit from Donna Drumm, Isabella Gerundio, Ms. Lowell, Melvyn Tanzman, Timothy Adobato, Peter Ruprecht, and Daniel Bussani; and permitted the parties to elicit live testimony from these witnesses beginning with cross-examination. The Court, based upon the joint representations of counsel under Federal Rule of Civil Procedure 32(a)(4), permitted the cross-examination of Mr. Ruprecht by deposition designations and counter-designations. The Court received live testimony from Dongwon Lee, Claudia Stern, and Alex Eleguddin. Plaintiffs also presented the following witnesses by deposition designation and counter-designations: Karim Bousta, Joyce Chan, Deepak Gupta, Ansel Lurio, Asaf Selinger, Chris Wu, and Richard Zhou.

The testimony received is summarized in the order in which the parties presented their witnesses, with the exception of Ms. Gerundio who was called as a witness in both Plaintiffs' and Defendant's cases-in-chief. For purposes of efficiency, after the Court received her affidavit in evidence, Ms. Gerundio was called to the stand only once, beginning with Plaintiffs' direct/cross-examination of her.

What follows is a summary of the salient facts elicited from the witnesses and exhibits referenced and introduced at trial.¹⁰

10 Many exhibits were admitted prior to trial as indicated in the Joint Pretrial Order following a final pretrial conference held on February 1, 2024. (See Doc. 410; Doc. 421, Ex. C). To the extent there were admitted exhibits listed in the Joint Pretrial Order that were not referred to at trial, provided in the parties' courtesy copy binder of “exhibits admitted and referenced at trial,” and not cited in the parties' post-trial briefing, the Court cannot and has not considered them herein. See, e.g., Sea Trade Mar. Corp. v. Coutsodontis, No. 09-CV-00488, 2015 WL 4998638, at *4 (S.D.N.Y. Aug. 20, 2015) (“Judges are not like pigs, hunting for truffles buried in briefs or the record.”).

A. Donna Drumm

Ms. Drumm, an able-bodied individual, is the founder of DrummAdvocacy, a law practice that advocates for specific reasonable accommodations for people with disabilities. (JE 1 ¶¶ 1-5). On Sunday October 9, 2022, Ms. Drumm (with the intended purpose of appearing as a witness in the case), downloaded the Lyft App and opened it in Dobbs Ferry, New York to get a ride to NYC (in a mode other than Access mode). (Id. ¶ 4). The first four drivers cancelled, and it took approximately 40 minutes from the time she first requested a ride until a Lyft vehicle picked her up. (Id. ¶¶ 13-16). Ms. Drumm's ride from Dobbs Ferry to East 88^th Street in Manhattan cost $53.54. (Id. ¶ 17). On the return trip from NYC, there were five mode options on the App from which to choose, including Access mode, as opposed to only three options when she was in Westchester which did not include Access mode. (Id. ¶¶ 18-27). Ms. Drumm also initiated the Lyft Driver Application so that she could testify as to the process for applying to be a Lyft Driver. (Id. ¶ 29). She did not complete all nine modules in the application because she did not want to be a Lyft driver; but she posits it would only take an additional 15 seconds or so to complete the application if Lyft added a question asking drivers whether they have a WAV. (Id. ¶¶ 29-40).

B. Isabella Gerundio

Ms. Gerundio testified that she is Lyft's Program Manager for WAVs. (JE 2 ¶ 1). Prior to joining Lyft, she had no direct experience with transportation, creating programs for people with disabilities, or ensuring compliance with the ADA or other disability laws. (Trial Tr. at 51-52). Ms. Gerundio described her job at Lyft as “show[ing] up every single day to see if [she] can find a solution to the [WAVs] program.” (Trial Tr. at 61:6-8). The challenge that Lyft faces with the WAVs program is figuring out how can it provide a reliable, on-demand WAV service on a supply-and-demand based rideshare platform. (JE 2 ¶ 7). Lyft has not found a way to do so without location-specific strategies to find WAV supply, strategies that cost millions of dollars annually. (Id.).

Ms. Gerundio spends approximately 70% of her time managing Lyft's WAV program, a majority of which concerns the Access Regions, looking at acceptance rates, reliability, driver ratings, and whether there is enough supply to meet demand. (Trial Tr. at 79). The rest of her time is spent testing pilots and experiments in the Access Regions to try to find solutions for the NonAccess Regions. (Id. at 80). Ms. Gerundio testified that she was unaware of Lyft ever hiring any consultants, statisticians, experts, or disability experts to assist or advise Lyft with how best to provide WAV service, with the caveat that her team makes an effort to talk to as many subjectmatter experts, manufacturers, and vendors, whose expertise is in WAVs. (Id. at 53).

Ms. Gerundio testified that her team ran a model for all Non-Access Regions to analyze the viability of providing WAV service and determined there was no viable opportunity to start such a program. (Id. at 114-116). Those experiments are run in the Access Regions because Lyft is already operating Access mode in the Access Regions, so the chance of success with any pilot program experimented in those Regions is higher. (Id. at 119; JE 2 ¶ 13). Ms. Gerundio testified that she does not run experiments in Non-Access Regions because of the risk of piloting a WAV program in a Non-Access Region that fails and has to be taken down after only one or two months. (Trial Tr. at 117-119).

Lyft has only launched WAV service in Access Regions with regulatory requirements or where it is subsidized, either through a contractual obligation such as healthcare and transit partnerships, or “to be part of the conversation” (such as the CPUC proceedings in California). (Id. at 57-58). Lyft has never launched WAV service anywhere where it was not either required or subsidized to do so. (Id. at 54-55). However, although it is no longer required to provide WAV service in Dallas, Texas, Lyft continues to offer Access mode there despite its low completion rate and low reliability metric now. (Id.; id. at 170, 191).

Lyft currently uses two of three supply models (the IC model, W-2 model, and rental model) to attempt to artificially create a supply of WAVs in the Access Regions. (JE 2 ¶¶ 15, 20, 22). Lyft, in some of the Access Regions, uses the IC model. (Trial Tr. at 56). This method also permits drivers to cross-dispatch, which means the vehicle can operate in multiple modes: the driver can match with a Standard mode user or an Access mode user. (Id. at 107). Lyft, in NYC for example, permits all IC drivers with WAVs to provide both WAV and Standard mode rides. (Id. at 111). There are 4,000 WAV drivers in NYC, which Ms. Gerundio believes is a result of regulations encouraging manufacture of WAVs, such as a NYC Taxi & Limousine Commission (“TLC”) licensing requirement of having a WAV. (Id. at 168-169).

To further incentivize IC WAV drivers to accept WAV rides, Lyft pays a per-ride bonus to the drivers on top of their regular earnings for each WAV ride completed. (Id. at 169; JE 2 ¶ 16). Ms. Gerundio testified that other than the actual financial cost of the incentives, there is no burden to Lyft in providing incentives to drivers. (Trial Tr. at 153). She recalled an occasion in August 2020 in which Lyft sent a promotional text and in-app console card to drivers in the Philadelphia and Delaware markets, looking for drivers with WAVs who might be interested in driving on the Lyft platform in Philadelphia. (JE 2 ¶ 18). Lyft received, out of over 26,000 drivers requested, fewer than 130 responses and 30 referrals; and of that amount, only one driver ended up driving a WAV on the Lyft platform. (Id.).

WAV service in other Access Regions is provided only through the W-2 model, such as San Francisco where W-2 drivers are a dedicated WAV supply and cannot cross-dispatch (i.e., the WAV drivers cannot offer rides in any mode other than Access mode). (Trial Tr. at 56, 107). The W-2 model is expensive because Lyft pays a third-party company on a per-hour, per-vehicle basis regardless of the number of WAV rides requested. (JE 2 ¶ 21). Under the W-2 model, Lyft can specify locations for the WAVs and can instruct its third-party partners to require drivers to drive solely in Access mode. (Id. ¶ 20). In other words, the W-2 model offers greater reliability than the IC model by guaranteeing a supply of WAV drivers. (Id. ¶ 21). The reason, Ms. Gerundio testified, that W-2 drivers are not cross-dispatched in the W-2 model markets is because it would significantly decrease their availability to offer WAV rides. (Trial Tr. at 107-108). The metrics of reliability, acceptance rate, and completion rate went down for W-2 drivers who were crossdispatched. (Id.).

Lyft, in June 2021 and in San Francisco where it is using the W-2 model, paid an annualized cost per vehicle of approximately $365,000 with fewer than 16 WAV rides occurring per week, such that Lyft received almost no money in ride fares to offset those annual costs. (JE 2 ¶ 21). Lyft had put out an RFP for partners in San Francisco to try to improve the costs of the W-2 model and Ms. Gerundio learned, as a result of that process, that it becomes more challenging and more expensive each year to solve this problem because of supply-chain issues and certain internal and regulatory metrics requirements. (Trial Tr. at 165-167). Ms. Gerundio also testified that there was a burden associated with just putting out that RFP, which included involving sourcing managers, global supply management, and the finance team to develop the RFP; researching which WAV vendors existed in the local market; contacting those vendors to determine if they had interest in a partnership; conducting vendor interviews; and conducting negotiations. (Id. at 192).

Lyft also tried a third model in NYC, in which Lyft contracted with a rental car company to procure WAVs for rental to independent drivers (the “Rental model”). (Id. at 187; JE 2 ¶¶ 2223). The Rental model was in place in NYC from 2019 to September 2021 and Lyft determined that it did not work. (JE 2 ¶¶ 22, 25). Lyft is no longer using this model. (Id.). Lyft had to pay its rental partner a fee for every WAV (that was actually sitting idle) and realized as a result of an analysis performed, that the IC WAV drivers who rented their WAVs through a Lyft-sponsored rental program spent only 2% of their time providing Access mode rides-a result that did not work. (Id. ¶ 24). She testified that Lyft has no current plan to utilize the Rental model in any market in the future. (Id. ¶¶ 22, 25). Ms. Gerundio also testified that Lyft has a subsidiary called Express Drive which rents vehicles to drivers. (Trial Tr. at 103). She explained that Express Drive is an umbrella with two companies under it, Hertz and FlexDrive. (Id. at 104). The WAV team looked into whether FlexDrive or Hertz could add WAVs to the fleet, and they did create a pilot but it did not come to fruition due to a lack of viable supply. (Id. at 104-105).

Ms. Gerundio made clear that Lyft considers reliability rate and profit and loss in determining whether it should turn on Access mode. (Trial Tr. at 114-115, 144-145). The performance metric that Lyft strives to meet when there is not a regulatory or contractual requirement is an 80 percent reliability rate (i.e., when a rider requests a ride and a driver accepts it). (Id. at 121-122). Ms. Gerundio testified that she would not launch WAV service if there was not a plan in place to hit the 80 percent. (Id. at 123). Ms. Gerundio also testified that a plan to launch Access mode in a Non-Access Region had to be cost-neutral or profitable. (Id. at 146). Without a plan to recoup costs, it would not be reasonable to launch Access mode, regardless of whether the launch cost Lyft $300,000 or $3.3 million. (Id.). With respect to measuring the effectiveness of WAV service, Ms. Gerundio testified that the programs in San Francisco, Los Angeles, and NYC were effective because of their higher completion rates (though they do not always hit the 80 percent mark); but that no Access Region has effective WAV service when one considers cost as an element of effectiveness. (Id. at 154-155, 164).

Nowhere in the nine Access Regions does Lyft operate Access mode by simply turning Access mode on in the App in those Access Regions. (Id. at 160). Ms. Gerundio testified that Lyft did a lot of work before turning on Access mode. (Id. at 161). At one point, Access mode was inadvertently turned on in Denver, Colorado, a Non-Access Region. (Id. at 142-144). Ms. Gerundio testified that she did not know how long it was turned on in Denver, whether there was any reputational damage to Lyft as a result of that occurrence, or whether there was any burden associated with turning on Access mode at that time. (Id.).

Ms. Gerundio maintained that simply showing Access mode on the Lyft App is not a solution to WAV service. (JE 2 ¶ 35). Displaying Access mode on the App will not make the supply of WAVs suddenly appear; riders could get stranded and Lyft would face reputational damage and lawsuits. (Id. ¶¶ 35-36). Even assuming that drivers could be found, and prior to offering WAV service, Lyft would have to ensure that ramps, lifts, and securement devices for wheelchairs in the WAVs met applicable regulatory requirements and the drivers are properly trained in the use of such equipment. (Id.). Lyft would also have to pay special bonuses to incentivize the drivers to pick up Access rides and not just do Standard rides. (Id. ¶ 36).

In 2021, the total amount Lyft spent to create WAV supply in the Access Regions was $13.8 million. (Id. ¶ 37).¹¹

11 The parties stipulated that Lyft spent approximately $10-13 million on its WAV programs in 2019; spent approximately $13-15 million on its WAV programs in 2020; that its WAV budget for 2021 was $20 million; and that its projected WAV budget for 2022 was $25 million. (SF ¶¶ 28-31).

C. Harriet Lowell

Ms. Lowell, as noted supra, is a resident of White Plains, a city in Westchester County, New York. (JE 3 ¶ 1; SF ¶¶ 1, 3). She is an individual with a disability under the ADA and NYSHRL. (Doc. 421 at 10 ¶¶ 1-2). Ms. Lowell travels in Westchester, NYC, and throughout New York State (“NYS”). (JE 3 ¶¶ 12, 32 n.1, 40). She has not downloaded the Lyft App or the Uber app because they do not offer rides to her in Westchester. (Trial Tr. at 204). Ms. Lowell testified that she wants to attend spontaneous get-togethers, without being stranded. (Id. at 215-216). Ms. Lowell's position at trial was not that Lyft should offer the same service as it offers to non-disabled people; rather, that Lyft should turn on Access mode in Non-Access Regions so the option is available to her. (Id. at 208-209). She maintains that with Access mode in place, some service would be possible, understanding that transportation is often imperfect and unreliable but “any service is better than none.” (Id. at 208-209; JE 3 ¶ 32).

Ms. Lowell stated that she would not want to be relying on Lyft if she knew she would be stranded. (Trial Tr. at 216). She is asking that Lyft modify its policies to provide the best access to WAV service that it can reasonably provide, provide people with disabilities with the opportunity to seek on-demand transportation, and provide some access to service to people with disabilities. (JE 3 ¶¶ 33, 36). Ms. Lowell also testified that she “want[s] equivalent access to the [A]pp.” (Trial Tr. at 210).

D. Melvyn Tanzman

Mr. Tanzman is 72 years old and resides in Yorktown, New York. (JE 4 ¶ 1). He was Executive Director of WDOMI from 1999 to 2020. (Id. ¶ 2). Mr. Tanzman explained that WDOMI is an independent living center that advocates for people with disabilities. (Id. ¶ 11). Herecounted Ansel Lurio's story that demonstrates “how useless it is for people with disabilities to download Lyft's App.” (Id. ¶ 37). Mr. Lurio was at a park when it started to snow, his motorized scooter could not function, and he needed a WAV to pick him up. (Id. ¶ 41). Mr. Lurio downloaded Lyft but the App informed him that Lyft had no WAVs and that he should call Paratransit. (Id. ¶ 43). Paratransit requires 24-hour notice so it could not assist him. (Id.). Ultimately Mr. Lurio had to call an ambulance, but by law it could only take him to the hospital, so he had to spend the night at the hospital before getting a ride home. (Id. ¶ 44). Mr. Lurio was angry that Lyft affirmatively refused to provide any service to him; but he was not angry that Lyft did not have any WAVs available at that particular moment. (Id. ¶ 45). Mr. Tanzman stated that WDOMI does not request that Lyft provide perfect WAV service. (Id. ¶ 53). Mr. Tanzman believes that Lyft simply refuses to provide any service to wheelchair users in Westchester County and the majority of the United States. (Id. ¶¶ 50-53).

E. Timothy Adobato

Mr. Adobato is 64 years old and, since 2022, resides in Port Charlotte, Florida. He previously lived in Randolph, New Jersey. (JE 5 ¶ 1). He has been a quadriplegic since 1977. (Id. ¶ 3). Mr. Adobato has traveled in and to New Jersey, Salt Lake City, and Florida, and wants to fly to San Diego. (Id. ¶¶ 13-15, 36). He would prefer to fly and get a Lyft WAV, which he believes would be less expensive than driving himself or renting a WAV. (Id. ¶¶ 13-15). He also indicates that he would download and order a Lyft WAV for travel and other social events when Lyft offers service where he lives and in the places where he usually travels. (Id. ¶ 28). Mr. Adobato maintains that “[s]omething is better than nothing.” (Id. ¶ 25).

F. Peter Ruprecht

Mr. Ruprecht is the President of Drive Master Co. Inc., a retail sales organization selling WAVs and manufacturing equipment to convert vehicles into WAVs, established in 1952. (JE 6 ¶ 2). Mr. Ruprecht is unaware of any car manufacturer in the United States that manufactures vehicles with the wheelchair accessible sort of modifications already installed. (JE 7 at 2). There are some manufacturers that sell vehicles that are modified to be WAVs, such as Braun and VMI. (Id.). Drive Master sells WAVs to individuals and for taxi and ridesharing use. (JE 6 ¶ 6). They have sold WAVs for as low as $10,000 and they have 8 WAVs available for rent as well. (Id. ¶¶ 9, 11). Drive Master's website has a list of mobility equipment dealers. (JE 7 at 3). These dealers likely also rent WAVs. (Id.). No one has ever expressed interest in renting one of Drive Master's WAVs to drive for a ride share like Uber or Lyft. (Id. at 4).

Drive Master offers vehicle conversion services, with costs to convert starting at $16,000. (JE 6 ¶ 12). Drive Master recommends bringing a WAV in for maintenance twice per year, which takes one to two hours at a cost of $155 per hour. (Id. ¶ 14). Drive Master would be amenable to partnering with Lyft to facilitate an increased supply of WAVs on Lyft's platform. (Id. ¶ 18). Mr. Ruprecht would need to negotiate the terms of any such agreement, and he would structure any such partnership so that Drive Master could make a profit. (JE 7 at 5-6).

G. Daniel Bussani

Mr. Bussani is the Chief Executive Officer of Bussani Mobility, specializing in WAV retail sales and rentals; mobility equipment sales; and WAV maintenance and repair services. (JE 8 ¶¶ 1, 6). They sell vehicles for personal use that come with wheelchair or access equipment preinstalled, which he gets from a company called Braun. (Trial Tr. at 240). Bussani Mobility sells WAVs to individuals for as low as $18,000 to $20,000. (JE 8 ¶ 10). They offer vehicle conversion services beginning at $17,000 to $18,000 although the cost to convert a vehicle has increased in the last six months to approximately $25,000. (Id. ¶ 13). They recommend bringing a WAV in for maintenance twice per year, with maintenance visits costs at approximately $150 each. (Id. ¶ 15). Bussani Mobility has 20 WAVs available for rent as well. (Id. ¶ 16). Mr. Bussani testified that the company does not rent to drivers who drive the vehicles on a ride-sharing platform because automobile insurance for those cars does not cover commercial use. (Trial Tr. at 243).

Bussani Mobility receives dozens of requests each week for WAVs to drive for a taxi or ridesharing company. (JE 8 ¶ 19). It receives 10-15 calls each day from individuals who seek to drive for Uber and virtually none have mentioned driving for Lyft. (Id.). Mr. Bussani testified that quite some time ago, Uber approached him to make a business arrangement, they had informal meeting, and it never went anywhere after that. (Trial Tr. at 246). Mr. Bussani testified that he would partner with Lyft to provide wheelchair-accessible rides, sell Lyft WAVs, and offer discounted rates for Lyft drivers. (JE 8 ¶¶ 20-22). Although he does not know what he would charge Lyft to provide a WAV with a driver on an hourly basis, as that is not the business he is in, he would charge less than $1,000 per day. (Trial Tr. at 250). Mr. Bussani testified that he would be willing to sit with Lyft to negotiate the terms of deal to sell WAVs to Lyft or for Lyft drivers to purchase WAVs at a discounted rate. (Id. at 244-245). He is open to finding a business opportunity for Bussani Mobility, with the potential to earn a profit. (Id. at 245). He would not continue with a business relationship if it was not profitable over time. (Id. at 246).

H. Dongwong Lee

Mr. Lee was hired by Lyft in 2017 as the Operations Strategy Manager and in 2018 he began working on WAV projects. (Trial Tr. at 252-253). When asked at trial about certain WAV projects that Lyft had considered, he confirmed that “Project Access” was an evaluation of the options to provide WAV service in new markets; the project “Perseus” involved an evaluation of renting vehicles to drivers; and “Project Beach Boys” was a consideration of partnering with a third-party company who would use its fleet of WAVs and drivers to actually service the rides. (Id. at 254-255). Mr. Lee testified concerning the “LyftSub” project, which the national WAV team collectively spent thousands of hours on. (Id. at 256). One of the motivations of looking at LyftSub was to find a scalable solution for providing WAV service nationwide. (Id. at 257). The team modeled scenarios that it thought had the potential to be profitable, based on unproven assumptions. (Id. at 256-257). Those unproven assumptions included insurance costs, the number of WAV rides that could be generated once a WAV supply existed in a market, the economics of transit and healthcare partnerships, and what the volume of rides from those sources might be. (Id.at 281). Mr. Lee also testified that Lyft has a subsidiary called FlexDrive and it, through Lyft's Express Drive, rents vehicles to drivers on the platform. (Id. at 262-263).

Mr. Lee confirmed that he was one of the main contributors to a presentation laying out various considerations regarding the LyftSub proposal. (Id. at 266; Tr. Ex. 75).¹² Mr. Lee explained that the concept of LyftSub was that Lyft would create a subsidiary and own the supply of WAVs. (Trial Tr. at 272). His analysis included a chart demonstrating the volume of rides per vehicle that Lyft would need before the program would become more economically attractive than the IC and W-2 models cost per ride. (Id.; Tr. Ex. 75 at LYFTILRC00022649). In other words, the chart demonstrated when there might be an advantage to Lyft owning its own supply of WAVs by costing less than partnering with another entity. (Trial Tr. at 272-273).

12 The Court cites to the exhibits marked at trial as “Tr. Ex. __.”

I. Claudia Stern

Ms. Stern, a Certified Public Accountant, holds a bachelor's degree in physics and an MBA from Harvard, and worked in telecommunications for 20 years before becoming a CPA. (Id. at 289-290). She handles large volumes of data sets and makes sense of them, sees trends, and comes to conclusions about them. (Id. at 290). For purposes of this litigation, her primary job was to analyze data produced by Lyft under the direction of Alex Elegudin and Plaintiffs' counsel. (Id. at 291). She received six data sets produced by Lyft and primarily utilized the demand data set. (Id. at 293). The demand data set contained data concerning a number of different services, and her focus was on Standard and Access services. (Id. at 293-294).

There was 49 months of demand data provided, with 326 Regions listed. (Id. at 294-295). The supply data set likewise contained Region, month, and number of drivers, by service mode (i.e., Access or Standard). (Id. at 295-296). Ms. Stern noted as significant that she saw Access mode drivers in areas where Access mode service was not being provided. (Id. at 296). In other words, there were drivers with WAVs that were driving or giving rides to customers in Non-Access Regions. (Id. at 296-297). The WAV dataset she received contained, by month and by region, the number of drivers and number of vehicles, as well as the number of WAV and non-WAV rides those drivers made. (Id. at 297). The fourth dataset was the “rider/driver” set which provided information about the number of passengers and drivers each month. (Id. at 298). She also received the “toggle report” which contained information about how many people went through the process of turning on the toggle to get to Access mode and whether they left it on. (Id.). The last data set was information about WAV passengers from their first ride-unique information to each passenger, such as their first date of service and how many rides they had taken through January 2021. (Id.).

Ms. Stern prepared a chart using the demand and supply data sets, summarizing how Lyft performed service in Access Regions. (Id. at 300-301; Tr. Ex. 6). The chart contains a column purporting to set forth an average percentage of completed versus requested rides, which Ms. Stern calculated from data in the demand file by dividing the completed number of rides by requested rides by month, although the chart does not set forth a column including requested ride data. (Trial Tr. at 301-303; Tr. Ex. 6). The average price per trip was calculated by taking the total price per trip paid during the month and dividing it by the number of completed trips. (Trial Tr. at 303-304; Tr. Ex. 6). This summary chart did not factor in differences in the use of the W-2 or IC model in computing the average loss for all Regions or average cost per trip for all Regions. (Trial Tr. at 370-371; Tr. Ex. 6).

Ms. Stern prepared another chart for Access Regions where WAV service is provided by Lyft, identifying the number of available vehicles per month and calculating the average wait time. (Trial Tr. at 306-307; Tr. Ex. 15). She prepared an exhibit estimating the number of drivers that would be needed to provide Access service in Non-Access Regions based on the statistics she had for Access Regions using the demand data set. (Trial Tr. at 307-308; Tr. Ex. 11). To estimate the number of completed rides which appears in the exhibit, she took the number of Standard rides completed in Non-Access Regions and the number of Standard rides completed in Access Region and, with the percentages generated from those figures, used that same ratio, assuming that there are people seeking WAV service in the same proportion across the United States as are in the Access Regions. (Trial Tr. at 308-310). Using those ratios and applying them to data from the supply data set, Ms. Stern estimated that there would be 885 drivers in Non-Access Regions, which breaks down to three drivers per Non-Access Region per month on average. (Id. at 311-312). Ms. Stern performed the same calculations for year 2020 as she did for 2019. (Id. at 312).

Ms. Stern also created a model projection for three years of providing Access service in Westchester using data from her summary chart (Tr. Ex. 6), basing the number of Access rides on the number of Standard rides that occurred in Westchester in 2019, and using a ratio based on what she observed for the Access Regions (Tr. Ex. 29). (Trial Tr. at 312-314). This projection assumes that the price per ride would decrease as ridership increases, and assumes that Lyft will get 50% profit from every Standard ride provided by these WAV drivers. (Id. at 314-315). Thus, she concluded that by including cross-dispatching, Lyft could be profitable by Year 3. (Id. at 315). The model for Westchester under Year 1 lists an average cost of ride as $89.70. (Id. at 369; Tr. Ex. 29). However, the summary chart data that Ms. Stern prepared calculated an average $173.34 cost per trip for all Regions (Tr. Ex. 6); Ms. Stern explained the reason for the difference is that the average cost per ride for the Westchester model was based on her using the lowest 50% of the cost data for all Regions. (Trial Tr. at 372-373).

Ms. Stern testified about a chart she prepared containing information about WAV service in Phoenix, an Access Region, from July 2019 through March 2020. (Id. at 316-318; Tr. Ex. 10). Based on information she had previously learned as a result of reading Dr. Rysman's expert report, Ms. Stern agreed that any data about Phoenix costs may actually be higher than reflected in her exhibits. (Trial Tr. at 357, 360-361).

Ms. Stern testified about a chart she generated of the number of WAV drivers in Westchester County by month which she explained demonstrates there were 527 WAV drivers in Westchester in January 2021. (Trial Tr. at 318-320; Tr. Ex. 110). Ms. Stern testified that she produced work papers for this chart which included additional data including the sum of hours spent by those WAV drivers in Westchester. (Trial Tr. at 350-352; Trial Ex. RRR1). The result of calculating the average time spent by those 527 WAV drivers in Westchester is 10.23 minutes per Access mode driver driving in Westchester County in that month. (Trial Tr. at 352).

Ms. Stern testified about another chart showing WAV drivers in all the regions of New York. (Trial Tr. at 320, 322-323; Trial Ex. 111). Like the previous exhibit displaying the number of WAV drivers in Westchester, this chart also does not include the sum of hours these WAV drivers were driving in Non-Access Regions. (Trial Tr. at 353-354). The areas with the largest number of WAV drivers shown in the chart are Nassau, Suffolk, and Westchester, which are closer to NYC than any of the others on the chart. (Id. at 354). Ms. Stern generated a chart designed to show where the WAV drivers are located geographically in areas in the Northeast United States including New York (id. at 323-324; Trial Ex. 109) and a similar one for the contiguous United States (Trial Tr. at 324; Trial Ex. 108). These charts depict the Lyft supply data showing where WAV drivers show up in Non-Access Regions. (Trial Tr. at 325). The data pictured represents a four-year period and does not indicate the number of drivers or the hours spent by the driver(s) in the locations pictured. (Id. at 365).

Ms. Stern prepared a chart showing the denser cities in terms of people per square mile in the United States, organized by density, and indicating whether WAV service is provided by Lyft and whether or not Lyft is required or incentivized to provide such service. (Id. at 325-326; Trial Ex. 116). She also prepared a chart of Regions with a relatively low supply of drivers in the first month of operation, using data from the supply database, in an effort to demonstrate that the number of drivers increases over time. (Trial Tr. at 326-327, Tr. Ex. 106). The supply data that was produced had approximately 46,000 lines of data for over 300 Regions, but the chart included only 40 data points for 20 Regions. (Trial Tr. at 364-365).

Ms. Stern utilized the WAV dataset to generate a chart showing by year the number of vehicles and drivers by type of driver, whether IC or W-2, in the Access Regions. (Trial Tr. at 327328; Tr. Ex. 107). The chart demonstrates that some cities are just IC, some are just W-2, and some are a combination of both. (Trial Tr. at 328-329; Tr. Ex. 107). She utilized both the demand and WAV datasets to generate a chart representing a comparison of months when W-2 drivers were cross-dispatched with months when they were not dispatched. (Trial Tr. at 329; Tr. Ex. 114). The cross-dispatching analysis she performed was only for W-2 drivers who are on the platform by contract, such that cross-dispatching those drivers would not increase the supply of WAVs. (Tr. Tr. at 355-356).

Ms. Stern prepared a chart showing the average cost per ride by quarter and the number of WAV rides that occurred as well as the number of non-WAV trips taken. (Trial Tr. at 333-334; Tr. Ex. 115). She prepared a chart showing service metrics and the number of WAV rides in NYC, highlighting in bold the months of September and October 2019 when the toggle for requesting WAV rides was removed. (Trial Tr. at 334-335; Tr. Ex. 112). With respect to NYC, Ms. Stern testified that it has a greater volume of Access rides than any other Access Region and the largest number of Access drivers. (Trial Tr. at 368).

J. Alex Elegudin

Mr. Elegudin was retained by Plaintiffs to give expert testimony in connection with two questions: (1) does Lyft provide equal opportunity to access services for people with disabilities as people without disabilities in the Non-Access Regions; and (2) are there modifications to Lyft's policies and practices that it can implement in order to provide that access to its services in NonAccess Regions. (Trial Tr. at 382-383). Based upon his specialized knowledge and experience, Mr. Elegudin was qualified to testify as an expert in disability services and accessibility, and in the areas of regulation and compliance with regulations. (Id. at 393-394).¹³

13 Mr. Elegudin, as of the time he prepared his expert report and was deposed in this case, did not have specialized knowledge, education, or experience in statistics, platform industries, private transportation companies, data modeling, or marketing and was thus not qualified as an expert in those areas. (Trial Tr. at 484-486, 488-489).

Mr. Elegudin testified that he began his analysis by reviewing Lyft's Standard mode service. (Id. at 395). The documents he reviewed did not suggest that Lyft analyzes demand or any other factor or metric before offering Standard mode service. (Id.). Rather, he concluded that Lyft simply offers Standard mode anywhere possible where there is internet service. (Id.). Mr. Elegudin also described the IC and W-2 models, and reviewed cost data in connection with both models. (Id. at 402-403). He concluded from that data that the IC model is more cost effective because those drivers already have access to their vehicle so Lyft does not have to pay any additional cost for access to the vehicle. (Id. at 403). After reviewing how Lyft provides Standard and Access service, he considered whether and where there were opportunities to make modifications to provide service to wheelchair users. (Id. at 403-404). Mr. Elegudin offered a number of recommendations for modifications that he opines would result in accessible service by Lyft. (Id. at 405).

The first modification he proposed was that Lyft “should remove the blocker” so that Access mode would appear on the App. (Id. at 405-406). Mr. Elegudin testified that he recalled deposition testimony that there was minimal cost or it was not difficult to turn off the blocker because they have done it numerous times. (Id. at 409-410). He reviewed the Westchester regulations and does not believe Lyft has a legal obligation to provide training to drivers if it turns off the blocker, but NYC does require such training. (Id. at 412). He reviewed the regulations in the nine Access Regions and most of them do have training regulations. (Id. at 413). He also testified that there are not any special inspection requirements for WAVs in Westchester. (Id. at 415). The benefit of turning off the blocker in Westchester County would be that Access mode would become available in the App, people with disabilities who want to go into the App and request a ride would be able to do so, and drivers that have access to a WAV in Westchester would be able to see Access mode as well and respond to requests for rides. (Id. at 416).

Mr. Elegudin testified that in the regulations he reviewed, he did not see anything preventing Lyft WAVs that travel from NYC to Westchester from picking up WAV riders in Westchester. (Id. at 417). He explained that when he was creating accessibility rules for NYC that ultimately required Lyft to start providing Access mode there, he projected ridership, looked at demand, looked at how Lyft operates in Standard mode, had an understanding for how rideshare companies work, and performed research and analysis on rideshare and operations. (Id. at 418). Mr. Elegudin also made projections in this case for Westchester County in his expert report. (Id. at 419).

Mr. Elegudin testified that he has spoken to manufactures and dealers, and determined that there are 150,000 to 200,000 WAVs on the road today. (Id. at 421). Based on publicly available data, there are 5,000 WAVs in NYC, and those WAVs travel to regions in the area such as Nassau, Suffolk, and Westchester. (Id. at 423; but see id. at 424 (“there's 10,000 WAVs in NYC alone”)). He believes that in any given month there are probably 500 or more WAVs that travel to Westchester County. (Id. at 423). This is how he is able to conclude that making Access mode available in Non-Access Regions such as Westchester would result in there being WAVs available in Westchester. (Id. at 421).

Mr. Elegudin also testified that in connection with making Access mode available, Lyft should also stop implementing the “toggle.” (Id. at 428). He explained that the TLC determined that the toggle was a “demand suppression tool” because it was hiding the feature, and the TLC recommended, using its regulatory powers, that Lyft remove the toggle. (Id.). The toggle was removed in NYC and within a few months, based on his view of the data, the trip volumes went up by 500 percent. (Id. at 428).

Mr. Elegudin is of the opinion that removing the blocker would increase supply and demand. (Id. at 445-446). The basis for his opinion with respect to demand is that during his time at the TLC, he launched a service called Accessible Dispatch; and when they turned on the mode specifically for the app and the call center started working, demand increased. (Id. at 446). Additionally, during his review of the data in this case, specifically in Access Regions, when Lyft turned on Access mode, demand increased. (Id.). He also bases this opinion on his experience with the TLC. (Id.). Whenever the TLC compelled a company to offer WAV service, the companies have done so and demand increased. (Id.).

With respect to supply, Mr. Elegudin testified that when he was at the TLC operating the Accessible Dispatch program, they “turned on the mode” and when drivers became aware of the availability of this specific feature, they became available and supply increased. (Id. at 449-450). Additionally, at the TLC, they did driver focus groups and studies; and found that when a new service becomes available it is a new economic opportunity that attracts new drivers and increases supply. (Id. at 450).

Mr. Elegudin agreed that part of his opinion is that the proposed modification of displaying Access mode in all regions would only provide a starting point or baseline from which WAV service could develop and improve over time. (Id. at 512-513). He did not, in reaching his conclusions as to this proposed modification, rely on any studies or textbooks. (Id. at 513-514). Mr. Elegudin did not perform any analysis with respect to this proposed modification concerning wait times or completion rates. (Id. at 516). He did not perform any analysis of the supply that would appear on the platform if this modification were to be implemented. (Id. at 517). He did not survey the drivers whom he believes would drive WAVs in Westchester to determine if any would want to drive on Lyft's platform in Westchester. (Id. at 518).

Mr. Elegudin testified that his proposed modification of increasing advertising and marketing would increase demand on the App. (Id. at 447). The basis for this opinion is that when he worked at the TLC and they operated the Accessible Dispatch program, they performed a lot of analysis on marketing and how to get people with disabilities to use their app and call center. (Id.). They “invested significantly for this program” which increased demand. (Id. at 447-448). Additionally, based on his experience with the MTA New York City Transit (“MTA”), when they wanted to promote their accessible service offerings, they knew that awareness was a key to increasing utilization so they also used marketing. (Id. at 448). Mr. Elegudin's research and analysis in industry trends is also a basis for his opinion that promoting marketing and awareness of a service increases demand. (Id.). Finally, based on the documents he reviewed in this case, Lyft spends hundreds of millions of dollars to market their services in Standard mode service, which “clearly shows its purpose for increasing demand.” (Id.).

Mr. Elegudin testified that his proposed modification of asking existing and onboarding drivers if they have a WAV would increase supply. (Id. at 450-451). The basis for this opinion is that when he worked at the TLC passing new regulations, the TLC needed to know what the supply was in the NYC Taxi fleet and for-hire vehicle fleet. (Id. at 451). Through the licensing division, they required as a licensing requirement all drivers to identify whether they had a WAV. (Id.). Once that was a requirement for renewal of vehicle licensing and new drivers being licensed by the TLC, they started to get an increase in supply and knowledge of what the supply actually was. (Id.). Additionally, Mr. Elegudin opined that he reviewed data, documents, and testimony in this case that demonstrated that when Lyft asked in Access Regions if drivers have a WAV, it increased supply because Lyft became aware of the number of WAV drivers out there. (Id. at 452-453).

Mr. Elegudin testified that his proposed modification of increasing and utilizing crossdispatching for WAVs would increase supply. (Id. at 453-454). The basis for this opinion is that when he worked at the TLC they studied utilization, and cross-dispatching is about whether the service is being utilized only by wheelchair users or is it being utilized by everyone else. (Id. at 454). He testified that their analysis of yellow taxi trips in WAVs showed that the majority of WAV trips were being done by customers without disabilities, and approximately 2% of trips were in WAVs by customers with disabilities. (Id. at 454-455). Mr. Elegudin testified that, as an accessibility expert, history has shown that creating separate and different solutions for people with disabilities often does not work, versus a system utilized both by those with and without disabilities. (Id. at 455). Additionally, they learned that keeping drivers busy doing trips improves the economic opportunities which increases supply. (Id. at 455). He also found that, based on the data in this case that he reviewed with Ms. Stern's assistance, when Lyft utilized cross-dispatching, it improved the economics as the cost per trip decreased and there was minimal change in service levels. (Id. at 455-456). This increased supply because when drivers are active it attracts more drivers to the system. (Id. at 456). Mr. Elegudin also bases his opinion on his experience with the MTA paratransit operation, in which only about 20% of the ridership were wheelchair users, using the WAVs to also drive ambulatory users increased the economics, making the cost per ride lower. (Id. at 456).

Mr. Elegudin testified that his proposed modification of utilizing prioritization logic is a way to make cross-dispatching more effective and ultimately make more WAVs available. (Id. at 457-458). He explained that when a driver is driving in multiple modes at the same time, such as Standard mode and Access mode, and a trip comes in at the same or near the same time, the App's algorithm prioritizes the trip based upon the preferred mode. (Id at 458). Based on his analysis of testimony and documents in this case, prioritization logic is used in all of Lyft's modes; and when Lyft does utilize it in NYC, the WAV trip is a priority, so the WAV customer gets the trip. (Id. at 458). Based on his knowledge in the industry, prioritization logic would make cross-dispatching more effective. (Id. at 459).

Mr. Elegudin testified that his proposed modification of adding WAVs to Lyft's Express Drive fleet for leasing would increase supply. (Id. at 459). He bases his opinion on his experience at the TLC. (Id.). When regulating the industry in NYC, the TLC wanted to make sure there was adequate supply. (Id.). As a result, the TLC did outreach to third-party companies already leasing vehicles to the TLC to encourage them to add WAVs to the fleet. (Id.). The reality, the TLC found, was that many drivers did not own WAVs and needed to lease vehicles that they could utilize to drive on the platform. (Id. at 459-460). Mr. Elegudin also based this opinion on the LyftSub proposal, which he believed showed that having WAVs available as a result of the LyftSub program would increase supply. (Id. at 460-461).

Mr. Elegudin testified that his proposed modification of utilizing third-party or transit partnerships would increase the supply of WAVs on Lyft's platform. (Id. at 462). He based this opinion on his experience at the TLC when they allowed for partnerships to meet WAV demand; and at the MTA, utilizing transit partnerships to fulfill WAV trips. (Id. at 463). He also has attended many conferences and courses on transportation, and finds that partnerships are very common in the industry because it enables companies to work together where one has an existing supply which can meet the demand. (Id. at 463-464). Additionally, based on his review of documents in this case, Lyft utilizes transit partnerships to increase its WAV supply by working with providers in Access Regions. (Id. at 464).

Mr. Elegudin testified that his proposed modification of providing bonuses and incentives for its WAV drivers would increase supply. (Id. at 466). He based this opinion on his experience at the TLC, where they created the taxi improvement fund which gave financial incentives per trip to yellow taxi and WAV drivers every time they performed a WAV trip. (Id.). He also recounted his experience at the MTA where they gave a bonus to drivers to perform WAV trips to deal with some of the costs that come with performing WAV service. (Id. at 466-467). Based on his experience and study of the rideshare industry and as a consultant, he found that bonuses and incentives were commonly given to drivers to encourage them to be available and to accept trips, thereby increasing supply. (Id. at 467). Additionally, based on his review of documents in the case, he understands that Lyft spends significant amounts of money on providing bonuses and incentives for Standard mode drivers and its WAV drivers in Access Regions. (Id. at 467-468).

Mr. Elegudin also testified about his proposed modification of imposing a ten-cent surcharge, which he no longer believes is a necessary modification. (Id. at 469). Mr. Elegudin testified, in connection with this proposed modification, about three models he prepared with Ms. Stern's assistance. (Id. at 472-480). The first model used an estimate of the number of Access mode rides in Westchester, average price per ride, average cost per ride, and projected Lyft's net profit if it imposed a ten-cent surcharge. (Id. at 472-475; Tr. Ex. 25). The second model used a different average cost per ride and projected Lyft's net profit if it imposed a ten-cent surcharge. (Trial Tr. at 476-477; Tr. Ex. 28). The third model was the same as the second model but added in cross-dispatching with a ratio based on cross-dispatch analysis in Lyft's data, estimating profitability in a few years. (Trial Tr. at 477-479; Tr. Ex. 29).

Mr. Elegudin confirmed that he did not offer any opinion regarding actual numbers of WAVs available, completion rates or wait times if all of his proposed modifications were made in the Non-Access Regions. (Trial Tr. at 519-520). Mr. Elegudin did not testify as to any actual cost to implement his proposed modifications. (See id. at 520-521). Mr. Elegudin is of the opinion that other than turning off the blocker and asking drivers whether they have a WAV, none of the other proposed modifications are essential. (Id. at 429, 468). Specifically, Mr. Elegudin testified as follows:

Q. Are any other modifications, other than turning off the blocker, essential to the provision of WAV service by Lyft? ....

A. Yes. Oh, I'm sorry. Are any other ones essential? No. No other ones are essential....

I think my modification with regard to removing the blocker and asking drivers whether they have a WAV, are the most essential

modifications they make. My other modifications that I've been talking about really have to do with efficiency. The more -- these modifications, including -- including the implementing of incentives and bonuses, would allow Lyft to provide access mode service in a more efficient manner, it would allow service levels to ramp up in a faster manner, and would ultimately help the economics of the service.

(Id. at 429:9-21, 468:7-16).

Mr. Elegudin confirmed that it is his opinion that the overall breadth of all of the modifications he identified would lead to a level of some service, meaning service would be launched, and that people with disabilities would go from having zero opportunity to get a trip and zero trips fulfilled, to having some number larger than zero trips fulfilled. (Id. at 526).

Mr. Elegudin also made clear his overall view, based upon his experience, that Lyft can and should make WAV service available in the Non-Access Regions but that Lyft was not required to do so, stating: “I think the law says they can and should, if it isn't a burden.” (Id. at 392).

K. Plaintiffs' Witnesses via Deposition Designation: Karim Bousta, Joyce Chan, Deepak Gupta, Ansel Laurio, Asaf Selinger, Chris Wu, and Richard Zhou

Mr. Bousta testified that his initial title at Lyft was Vice President of Driver Experience Operations and then it later evolved to become the Head of Operations, Market Development of Drivers and Fleet Services. (Trial Tr. at 533). Prior to joining Lyft, Mr. Bousta did not have any specific exposure to disability-related training. (Id. at 532-533).¹⁴

14 The balance of the deposition designation testimony concerned an email thread between Mr. Bousta, Mr. Lee, Chris Wu, “and a few other people.” (Trial Tr. at 534-535). It has not been made clear to the Court whether the email referenced in this examination was offered or admitted as an exhibit at trial.

Ms. Chan, whom the Court presumes is or was a Lyft employee (see Lyft Br. At 10),¹⁵ testified that Lyft attracts drivers organically, by using paid media channels, and through referral networks. (Trial Tr. at 537). There is a standard onboarding process for drivers other than professional drivers. (Id. at 537-538). Lyft runs background checks of every driver who applies to drive on the platform. (Id. at 538). Ms. Chan also testified concerning Lyft's Access mode, stating that Lyft's $20 million WAV budget is based on what it believes it needs to meet regulatory or contractual obligations, and is drawn for the overall rideshare budget. (Id. at 540-541). Ms. Chan testified that Lyft has not been able to make Access mode work in some of the densest cities in the world, and therefore if Access mode is turned on in locations with insufficient density, it would just be creating poor user experiences both for drivers and passengers. (Id. at 543-544). She explained that providing reliable service is one of the tenets of ride share, and a customer promise by Lyft. (Id. at 547).

15 The designated portions of Ms. Chan's deposition do not include any background or employment information about this witness, nor is there any identifying information contained in the Joint Pretrial Order.

Ms. Chan explained that she has not seen data that people with WAVs want to drive in ride share programs because there are no publicly available sources of data concerning WAVs. (Id. at 550). The reason is that WAVs are typically custom retrofitted or custom ordered and therefore their production is not recorded by a central and public body. (Id.). When asked what qualifies drivers to drive in “Lux” and “Lux Black,” Ms. Chan explained that the requirements are “like a make and model of a type of car,” and that Lyft is able to obtain and confirm that information through the vehicle identification number of the vehicle because it is provided from the manufacturer. (Id. at 552-553). She explained that while it would not be difficult for drivers to tell Lyft that their vehicle is wheelchair-accessible, it would be difficult for Lyft to certify that the vehicle itself is safe for transport, as there is not a standard governing body that does vehicle inspections for wheelchair-accessible vehicles like there are for standard vehicles. (Id. at 553). In Regions that require vehicle inspections, Lyft has state-certified mechanics actually check the vehicle. (Id. at 554).

Ms. Chan testified that Lyft has tried to shift demand for WAVs with coupons, and forming awareness in the community through partnerships, but to her knowledge has not done WAV-specific advertisement to customers. (Id. at 560-561). Lyft has used Google and Facebook ads targeted to try to recruit WAV drivers, but the programs were deemed ineffective by the marketing team. (Id. at 561-562).

Ms. Chan explained that Lyft's rider-side analysis is based on ride session data at a granular level but there is not enough sessions data to perform such an analysis for WAV because the sessions themselves are sparse and highly variable. (Id. at 563). Because of this, Lyft tries to guess where it thinks sessions are going to happen and keeps a car parked there. (Id. at 563-564). This is true for San Francisco; the outer boroughs of New York; Los Angeles; Portland; and in all the areas around Portland. (Id. at 564).

Ms. Chan also explained that in Regions where there is low density for Standard mode, if there is no car within a defined time window, a rider will see on the App that no cars are available. (Id. at 564). This also happens in places of hyper demand such as airports. (Id.). When the queue of available cars is emptied out, there will be no cars available or the rider will have to wait 20 minutes. (Id.). Either result she describes as unreliable, and in those places there is low adoption of ride share. (Id.). Lyft does not take action to increase demand in those areas. (Id. at 565). Ms. Chan explained that in markets that should be most predictable for Access mode, she has not “managed to achieve profitability, or even neutrality.” (Id. at 567). She testified that Lyft has conducted experiments in raising its prices and it has seen material demand shedding. (Id. at 571572). She believes that Lyft would see material demand change if it raised prices even by 10 cents, if Uber did not raise theirs. (Id. at 571).

The designated portions of Mr. Gupta's deposition concerned discussion of an email regarding cross-dispatching (id. at 577-578),¹⁶ and Mr. Gupta testified that he was not aware of a Lyft IC driver with a WAV who indicated they would not provide WAV rides (id. at 578).

16 It has not been made clear to the Court whether the email referenced in this portion of the witness' examination was offered or admitted as an exhibit at trial.

Mr. Lurio was deposed as WDOMI's representative and explained that the supply of WAVs is not published information, but that WDOMI estimates there are approximately 1,000 WAVs or more in Westchester County. (Trial Tr. at 579). That estimate is based upon the number of people who use WAVs and the number of WAV dealerships in the County. (Id. at 580).

Mr. Selinger stated that throughout his tenure in his role at Lyft, Express Drive bought cars around the country. (Id. at 580). He explained that Lyft's Express Drive did not offer WAVs, though there were conversations about bringing WAVs to Express Drive. (Id. at 582-583). When asked why Lyft uses the W-2 model even though those drivers cost more than the IC model, Mr. Selinger explained it is because they enable Lyft to meet certain TLC regulations in locations where there is not sufficient IC coverage. (Id. at 581). When the W-2 driver is not dispatched, the driver is simply waiting for a trip-Lyft has 36 people who for most of the day sit and wait for the chance of an Access ride. (Id. at 582). Lyft continues to provide WAV service even in a nonprofitable state due to regulations and to provide this access to people in wheelchairs. (Id. at 580). Mr. Selinger testified that, per the TLC with respect to for-hire vehicles, there are around 3,500 WAVs licensed in NYC out of about 95,000 vehicles. (Id. at 581).

Mr. Wu was Channel Manager at Lyft and did not have any transportation-related background or experience before joining Lyft. (Id. at 583-584). As Channel Manager, he managed most of the WAV program at Lyft. (Id. at 584). On the operation side, between August 2017 to 2019 he was staffed full-time to lead the WAV program and was the highest-ranking middle manager focused on WAVs. (Id.). Mr. Wu explained the NewCo proposal, which was a proposal to create a subsidiary that would help Lyft mitigate legal risk and allow it to purchase WAVs and hire drivers. (Id. at 585). The intention was to allow Lyft to purchase WAVs and connect WAV drivers to customers or hire drivers to provide WAV service. (Id. at 585-586). Lyft did not, to his knowledge, implement NewCo. (Id. at 589-590). Mr. Wu also presented LyftSub, another proposal which ultimately was not approved. (Id. at 598). He explained that LyftSub was a subsidiary that Lyft would create to enable some sort of WAV operation. (Id. at 598-599). Mr. Wu recalled a Core Ops Business Review meeting in January 2018 as the time when the Lyft executive committee decided not to not move forward with his recommendations or options for increasing WAV service at Lyft. (Id. at 595-596). The concern with the solution presented was passenger experience, and that the integration provided a different experience for wheelchair users than with ambulatory users. (Id.). Mr. Wu continued to try to come up with better solutions until he separated from Lyft in August 2019. (Id. at 596).

Mr. Wu described a document shown to him as a “deck that describes the problem of WAV” containing a recommendation to create LyftSub, a subsidiary of Lyft that engages a staffing agency for contracted drivers and leases WAVs, which he, Don Lee, and “[p]robably a lot of other people” worked on. (Id. at 599-600).¹⁷ Mr. Wu thought, at that time, the reference in the deck that Lyft will do as little as possible unless forced was probably true. (Id. at 601; Tr. Ex. 75 at LyftILRC00022626). He believed it to be theoretically true that LyftSub had a line of sight to profitability, if all the assumptions in his work were true. (Id. at 601-603).

17 Although Plaintiffs have not made clear to the Court whether this document was offered or admitted as an exhibit at trial, in Lyft's objections to Plaintiffs' deposition designations in the parties' Joint Pretrial Order, reference is made to this exhibit (Exhibit Wu 16) as being Trial Exhibit 75. That exhibit was admitted at trial.

With respect to advertising, Mr. Wu explained that advertising temporarily increases demand and therefore does not create an accurate picture of what steady supply looks like. (Id. at 590-591). This reality is problematic when considering WAV service, because one cannot match supply to demand as easily as it can be done in Access mode. (Id. at 591-593). Mr. Wu was also asked about a “toggle,” which he stated enables WAV passengers to see WAVs in the market that the passenger is in. (Id. at 586). The balance of the designated deposition testimony concerned documents marked at Mr. Wu's deposition and it has not been made clear to the Court whether they were offered or admitted as exhibits at trial. (Id. at 593-595, 608-611).

Mr. Zhou discussed Lyft advertising through “banner ads” in Los Angeles; and the components of the cost to run them include engineering time, operations, regulatory team's due diligence in assessing downstream effects, and marketing. (Id. at 612-613). With respect to marketing, Lyft also does a text message campaign, in addition to email and in-App advertisements, and posters such as billboards. (Id. at 613-615). Mr. Zhou explained that in all Regions, IC WAV drivers have the capability to switch between modes, but W-2 drivers do not have that option except in Portland and Boston. (Id. at 615). The markets where Lyft has W-2 drivers providing WAV service are New York, Boston, Phoenix, Los Angeles, and San Francisco. (Id. at 616). He estimated that 80 to 85 percent of Lyft's drivers are ICs or renters, and the remainder are W-2 drivers. (Id. at 616). Mr. Zhou explained the positive financial results of crossdispatching W-2 drivers included completion of more rides, which for the business meant one extra driver available in the market and helped the driver who normally sat around idle keep more attentive to their job. (Id. at 616-617). Mr. Zhou produced the aggregate cost for the WAV program, broken down in the reports by market, time frame, month, and ride type. (Id. at 618). The data was not broken down by W-2, IC, and rental cost. (Id. at 618). The marketing cost data was also produced in the aggregate figure discussed but not separately indicated in a separate column. (Id. at 619).

V. Defendant's Proof

With respect to Defendant's case, the Court received direct testimony by affidavit from Isabella Gerundio, Leon Treger, and Abbas Bozorgirad. The parties were permitted to elicit live testimony from those witnesses by way of cross-examination, re-direct examination, and re-cross examination. The Court received Pauline Scudieri's testimony by video-conference on a finding of good cause and compelling circumstances under Rule 43(a), all based upon counsel's joint representations. The Court received live testimony from Dr. Marc Rysman. Defendant presented Pamela Daly's testimony by deposition designation and counter-designations.

A. Leon Treger

Mr. Treger is the Operations Lead for WAV and High Value Modes (“HVM”) at Lyft. (JE 9 ¶ 1). When he became Strategy & Operations Lead in November 2020, he managed Lyft's WAV program in NYC, which included overseeing all aspects of WAV, including building dashboards, monitoring costs, and managing relationships with Lyft's contractual partners. (Id. ¶ 3). The scope of his role increased to all WAV markets nationwide. (Id.). Mr. Treger explained that Lyft's platform is a technology platform that uses computer algorithms to match riders who seek transportation to certain destinations with rideshare drivers who are driving to or through those locations. (Id. ¶ 4). The platform is premised on supply and demand, and metrics such as wait times and completion rates on the Lyft platform vary by geographic region. (Id. ¶¶ 5, 10; Trial Tr. at 709-712).

The impact of supply and demand on the performance of the platform is highly localized. (JE 9 ¶ 10). Mr. Treger gave the example that within NYC, it is typically quicker for riders to connect with drivers in Midtown Manhattan than the Bronx, because there tends to be a higher concentration of riders and drivers in Midtown. (Id.). NYC is one of 300 regions, referred to by Lyft as “BKN,” and it is subject to regulation by the TLC. (Id. ¶ 11). The number of total rides completed in a single day in NYC is greater than the total number of rides completed everywhere else in New York State combined. (Id. ¶ 12). Keeping the Lyft App “on” for Standard mode in low-use areas (for example in zip codes where there are no rides) presents no financial downside to Lyft. (Id. ¶¶12-13). Not all ride modes are offered everywhere. (Id. ¶15). Lyft offers different modes for different types of vehicles: “Lux Black” mode is a black car service that is available in NYC; however, it is not available anywhere else in the State because, in most NYS regions, Lyft offers only Standard and XL modes as there is insufficient supply of or demand for other modes in those regions. (Id.).

Because NYC drivers are regulated by the TLC, Lyft permits TLC-licensed drivers to pick up riders in NYC for a destination anywhere; but those drivers cannot pick riders up at the dropoff locations for the return trip to NYC. (Id. ¶18). Lyft indicates that regulatory and other operational reasons preclude it. (Id.). Indeed, when a TLC-licensed driver drops off a rider in Nassau or Westchester County, they receive a message that states, in effect, that they are missing required documents to drive in that county. (Id.). Mr. Treger testified that he learned of the TLC-license limitation on pick-ups in Westchester County from the Lyft Compliance Team, and that this rule applies to all drivers, not just WAV drivers. (Trial Tr. at 626-628, 633).

The TLC imposed rules for WAVs which Lyft was able to meet by investing heavily to create a WAV supply in NYC. (JE 9 ¶¶ 20-25). Lyft spent over $5 million to create the WAV supply in NYC needed to meet the TLC requirements in 2019, and over $6 million in 2020. (Id. ¶ 22). The TLC took a number of steps to increase WAVs in the market as well, and the combination of the regulations significantly increased the overall number of TLC-licensed WAVs. (Id. ¶ 25). The operational effort dedicated to Access mode in NYC is complex and enormously expensive. (Id. ¶¶ 27-32). Lyft must manually operate Access mode, whereas Standard and other non-WAV modes utilize Lyft's complex algorithms. (Id. ¶¶ 27-28). There is no scale of supply or demand for WAV (id. ¶¶ 29-30), and Lyft loses money on almost every WAV ride completed (id. ¶ 32).

B. Abbas Bozorgirad

Mr. Bozorgirad, since 2019, is a Data Scientist at Lyft who helps to review and analyze data to estimate metrics meaningful to the business. (JE 10 ¶¶ 1-2). There are possibly a hundred data scientists at Lyft. (Trial Tr. at 643). The data is collected from cellphones that riders and drivers use. (Id.). Lyft's data scientists analyze the data, get the trend, and come up with the algorithm for creating the way that Lyft works best in that Region. (Id.).

Mr. Bozorgirad explained Lyft's various modes, and that having multiple modes can be good for the business. (JE 10 ¶¶ 4-8). He further testified that multiple modes cannot be offered in all Regions, as the business has to consider where to offer specialized modes to ensure functionality, promote good user experience, and maximize revenue. (Id.). If Lyft's users (riders and drivers) are unhappy with their experience, they might stop using Lyft. (Id.). Mr. Bozorigirad stated that Plaintiffs' assertion that there are WAV drivers attempting to drive in Access mode in Non-Access Regions is incorrect, as the vast majority of WAV drivers shown in Non-Access Regions appear in Regions immediately adjacent to or near Access Regions (i.e., counties near NYC or San Francisco). (Id. ¶ 10). The reason the drivers appear in the Non-Access Regions is likely because they are taking riders from an Access Region to their destinations in Non-Access Regions. (Id.). Even in NYC, Lyft's largest WAV market by ride volume, WAV rides comprise 0.1% of all rides on the platform. (Id. ¶ 11). In Los Angeles, just 1 in every 5,000 rides is an Access mode ride. (Id. ¶ 12). Lyft's data for Standard mode shows that in areas of high population density, more rides are requested; and they are completed in lower wait times, more reliably. (Id. ¶¶ 1314).

Mr. Bozorgirad testified that Lyft keeps the revenue from any W-2 rides performed. (Id. ¶ 32). Because the cost is so high and demand for Access mode is so low, those W-2 WAV drivers end up sitting idle. (Id. ¶¶ 31-32). Little to no revenue is received by Lyft to offset the high hourly rate paid to the drivers. (Id.). While Lyft might be able to offset some of the high costs of W-2 WAVs by cross-dispatching the W-2 drivers, when Lyft experiments in doing that, the service levels for Access mode rides get significantly worse with longer wait times and less reliability. (Id. ¶ 34). Drivers that are cross-dispatched can elect to accept rides in Access mode or in Standard mode. (Id. ¶ 16). As for the IC model, most of these IC WAV drivers spend the bulk of their time servicing Standard mode and clustering in areas with the highest density of Standard mode demand. (Id. ¶¶ 16-23). Mr. Bozorgirad testified concerning his familiarity with a cross-dispatch experiment in NYC, utilizing W-2 drivers as IC drivers. (Trial Tr. at 644). The result was that the W-2 drivers ended up mostly utilized by Standard mode riders, so they were not available to complete Access rides. (Id.). The experiment with allowing cross-dispatch revealed that Lyft was not able to complete as many Access rides as it wanted. (Id.).

When WAV drivers are not available because they are engaged in a Standard mode ride, the WAV rider will have a worse user experience, wait longer for a ride, or not be matched with a ride at all. (JE 10 ¶ 24). If any of those things happen enough, users will stop using Lyft. (Id.). Lyft employs prioritization logic in the Access Regions to help improve performance for Access mode rides by making Access mode the highest priority compared to other modes when there is crossdispatch (i.e, if a WAV request and non-WAV request come in at the same time, the WAV driver will be paired with the WAV rider even if it is further away). (Id. ¶¶ 25-27). Doing so requires Lyft to figure out ways not to allow Standard mode service levels to then deteriorate to a point that riders do not want to take those rides. (Id. ¶ 27). Lyft has found that in most markets, the benefit of cost savings from cross-dispatch is outweighed by the negative impact on service levels. (Id. ¶ 35).

C. Pauline Scudieri

Ms. Scudieri lives in Decatur, Texas, which is about 65 to 75 miles northwest of Dallas. (Trial Tr. at 684). Ms. Scudieri owns a WAV. (Id.). She purchased a Toyota Sienna in May 2021, with some equipment pre-installed, and additional modifications including hand controls and “easy lock” which snaps the wheelchair in place while she is operating the vehicle. (Id. at 684-685). The car cost $40,000, and then the additional modifications were approximately $39,000. (Id. at 685686).

Ms. Scudieri works in Dallas, Texas. (Id. at 687). At the time of her deposition in this action, in April 2022, she understood that Lyft offered WAV service in Dallas but believed that the service with just one or two WAVs was insufficient. (Id.). Ms. Scudieri testified that she uses a wheelchair. (Id. at 689). Having reliable service therefore creates a real option for her; and getting stranded is, if it happens, a frustration. (Id. at 688). If she became stranded, it would just be a matter of having to find another way back. (Id. at 689).

Ms. Scudieri testified that a ten-minute wait time is not unreasonable and depending on the situation, thirty minutes is not unreasonable. (Id. at 690). If no WAVs were available, she would make other plans. (Id. at 691). Having a second option is always in the back of her mind, and she testified that it would be great to have the option of taking a Lyft ride, and let her make the decision whether the wait time was too long. (Id. at 690-691). For Lyft to be an option, there would need to be a Lyft vehicle available to come get her. (Id. at 691-692). She wanted the option to have a car come get her, and though it would be frustrating if every time she checked one was not available, at least the option would be there to check if one was available. (Id. at 692).

D. Pamela Daly

Ms. Daly lives in Boston, and understands that Lyft offers WAV service there. (JE 11 at 2). She has heard that the service is not reliable in meeting people's needs, meaning they are not able to get a ride when they call for a car. (Id.). She has never looked into using either Lyft or Uber, because she does not think it would work for her. (Id.). She heard that people have been stranded using Lyft's service because they were not able to get picked up to return home. (Id. at 3). Ms. Daly used the term “reliable access” in a declaration in this action, meaning she would be eager to use Lyft if it was something “reasonably dependable.” (Id. at 3-4). Ms. Daly stated that she is deterred from using Lyft because she does not consider it accessible to her. (Id. at 4).

E. Marc Rysman

Dr. Rysman was retained by Defendant to give expert testimony in connection with his evaluation of whether Lyft could provide Access mode using the platform approach that it uses for Standard mode. (Trial Tr. at 656). Based upon his specialized knowledge, training, education, and experience, Dr. Rysman was qualified to testify as an expert in statistical regression analysis, which predicted the outcome of a hypothetical Access mode based on population density extrapolated from the standard mode on Lyft's platform. (Id. at 675-676).¹⁸

18 Dr. Rysman did not have specialized knowledge, education, or experience in transportation, disability modifications, or WAVs and was thus not qualified as an expert in those areas. (Trial Tr. at 670-672).

Dr. Rysman explained that a platform industry, market, or firm is one that connects participants to each other and thus must account for both sides of its market in making all of its choices. (Id. at 658). Lyft is a platform in the sense that it connects riders with drivers and has to manage both sides of the market in order to achieve successful outcomes. (Id. at 662). To measure the success of the platform in general, Dr. Rysman looks for the number of transactions. (Id.). The criteria Dr. Rysman focused on, in this particular ride-sharing platform, are completion rates, utilization rate of the drivers, wait times, and the number of rides that are produced. (Id.). A failing platform has low completion rates, high waiting time, drivers not able to be successful and make money on the platform, and a low number of rides. (Id. at 663).

Dr. Rysman explained the “network effect” is a term used in economics to describe when a product is valued based on how many consumers use the product. (Id.). The Lyft platform exhibits network effects in that when more consumers are using the App, more drivers will drive on the App, which attracts additional riders to the platform. (Id.). The rider increase then attracts more drivers, and creates a “positive feedback loop or virtuous circle.” (Id. at 663-664). He further explains that “economies of density” and local outcomes are important with ride sharing. (Id. at 664-666). Dr. Rysman performed a statistical regression analysis to establish the relationship between variable population density and outcomes, using Standard mode as a model to predict what would happen if Access mode were opened in New York State. (Id. at 668-668). Dr. Rysman utilized data from the month of February 2020 and focused on data by zip codes for the analysis. (Id. at 697-700). He constructed bar graphs, mapping of the raw data, plots of the data, and ultimately used a Tobit model for the final results, which is a standard model to study outcome variables that often take on the value of zero. (Id. at 700-701). Dr. Rysman concluded that Access mode in a platform approach would not be viable, would generate very poor outcomes, low numbers of rides, poor completion rates, and generally an unsuccessful platform. (Id. at 676, 696). The number of rides would be zero in most cases and in that sense it would not be a viable platform. (Id. at 696).

Dr. Rysman found a close relationship between rides requested and completion rates, which is demonstrated in a bar graph that he prepared. (Id. at 701-702; Tr. Ex. P). He then prepared a map of New York State with color-coded zip codes based on his observation of rides requested that shows zero rides requested in more than 50% of the land area in New York State, and areas where he saw 5,000 to 127,000 rides requested in one month. (Trial Tr. at 703-704; Tr. Ex. Q). Dr. Rysman also mapped wait times, and concluded that the places with higher numbers of rides requested had low wait times, and a lot of land area where the App is available but no one is using it. (Trial Tr. at 704; Tr. Ex. Q). Dr. Rysman performed additional analysis to illustrate the relationship between ride volume, wait time, and completion rates. (Trial Tr. at 705-707; Tr. Ex. R). He compared the number of rides and population density in another map of New York State. (Trial Tr. at 708-709; Tr. Ex. S). He also prepared a graph to show the relationship between population density and completion rates (Trial Tr. at 709-711; Tr. Ex. V); and between wait time, population, and completion rates (Trial Tr. at 711-712; Tr. Ex. X). Dr. Rysman concluded from this analysis of Standard mode data that population density is very important in predicting outcomes on a platform. (Trial Tr. at 712).

Dr. Rysman then applied those findings to Access mode by plugging in the population density of the WAV population and then using the statistical relationship to predict the outcomes in the hypothetical Access mode. (Id. at 713). He assumed the population of people who use wheelchairs is 1.1% based upon a report concerning the wheelchair population in NYC. (Id. at 713-714; Tr. Ex. Z). He then summarized his findings from his regression analyses in a table (Tr. Ex. AA) and used the results of the Tobit model to calculate the probability of seeing zero WAV rides in each zip code, which he demonstrated in a color-coded map of New York State (Trial Tr. at 715-720; Tr. Ex. Y). Dr. Rysman concluded that for almost all of New York State, there is a 90-91% chance of seeing zero rides requested. (Trial Tr. at 720; Tr. Ex. Y). He also zoomed in on the southern portion of the state, including both New York City and Westchester County, and found that in 93% of Westchester zip codes, there would be less than one WAV ride request per day over a month, even in the more dense parts of the County. (Trial Tr. at 721-722; Tr. Ex. Y). Dr. Rysman opined that it is inconceivable for a platform to operate at that level of activity. (Trial Tr. at 723). He did not evaluate whether NYC could have a successful platform approach to Access mode, as the approach is already implemented there; and even with regulatory inflation of the number of IC drivers, Lyft was still using W-2s to reach the WAV service metrics required of it. (Id. at 754). In other words, Dr. Rysman explained, even in NYC, which is by far the most dense place in the United States, a platform approach to Access mode would not be successful, even with regulatory amplification of the number of drivers available for WAV riders. (Id. at 755).

Dr. Rysman's ultimate opinion is that Access mode applied in a platform manner to the population of people that use wheelchairs will generate such a low number of rides that it would make the platform not viable. (Id. at 724).

Dr. Rysman believes his predictions are conservative and the platform would be even less successful than what is suggested by his analysis because he held everything constant between Standard and Access modes, but WAVs are more expensive than a classic vehicle. (Id. at 724725). As a result, there may be less WAVs than his model assumed. With respect to factors that motivate drivers on the Lyft platform, he recognized that Lyft does not charge more for WAV rides, drivers collect the same amount, and WAV rides are shorter on average but take more time than Standard mode rides. (Id. at 725). These realities mean more driver time not being utilized, driving down revenue, and with higher costs. (Id.). All of this further suggests that his predictions about Access mode are conservative and the platform should be even less successful than his analysis suggests. (Id.). Dr. Rysman also testified about his review and rebuttal of Mr. Elegudin and Ms. Stern's analysis and report, from the lens of an economist. (Id. at 727-735).

Dr. Rysman noted that Standard mode generates a lot of rides in some places so Lyft makes a business decision to keep it available everywhere, even though they face the reputational cost of not generating rides in rural areas. (Id. at 734-735). He concluded that opening up Access mode will generate rides almost nowhere, so Lyft would get no reputational benefit of generating rides, but face the reputational cost of having a mode that does not deliver outcomes. (Id. at 735).

STANDARD OF REVIEW

I. ADA

Plaintiffs' first claim for relief against Defendant alleges, as modified by the Joint Pretrial Order, disability discrimination in violation of Title III of the ADA, under 42 U.S.C. §§ 12182(a), 12182(b)(2)(A)(ii), (iv), (v), 12184(a), 12184(b)(2)(A), and (b)(2)(C). (Doc. 20 ¶¶ 125-150; Doc. 421 at 4-6).

Title III of the ADA prohibits discrimination against individuals “on the basis of disability in the full and equal enjoyment of the goods, services, facilities, privileges, advantages, or accommodations of any place of public accommodation....” 42 U.S.C. § 12182(a). It also prohibits discrimination against individuals “on the basis of disability in the full and equal enjoyment of specified public transportation services provided by a private entity that is primarily engaged in the business of transporting people and whose operations affect commerce.” 42 U.S.C. § 12184(a).

A Title III claim under either section therefore requires that a plaintiff establish that: (1) she is disabled within the meaning of the ADA; (2) that the defendant is subject to the ADA under the identified section; and (3) that the defendant discriminated against the plaintiff within the meaning of the ADA. Roberts v. Royal Atl. Corp., 542 F.3d 363, 368 (2d Cir. 2008). “The ADA describes discrimination in both general and specific terms.” Id. There are two provisions relevant herein, under which Plaintiffs have brought their claim that Lyft is a public accommodation and/or a private entity engaged in specified public transportation:¹⁹ (1) refusal to make reasonable modifications in policies, practices, or procedures, when such modifications are necessary to afford such goods, services, facilities, privileges, advantages, or accommodations to individuals with disabilities (42 U.S.C. § 12182(b)(2)(A)(ii); 42 U.S.C. § 12184(b)(2)(A)); and (2) failure to remove barriers where such removal is readily achievable, or where it is not readily achievable, by failing to make services available through alternative methods if such methods are readily achievable (42 U.S.C. §§ 12182(b)(2)(A)(iv), (v); 42 U.S.C. § 12184(b)(2)(C)).

19 The parties stipulated that Plaintiffs satisfy the first element of their ADA claim. (Doc. 421 at 10 ¶¶ 1-2). With respect to the second element, Defendant disputes that it is a public accommodation under § 12182 of the ADA, but agrees that it falls into the definition of “public accommodation” under the NYSHRL and that it is an entity engaged in specified public transportation under § 12184 of the ADA. (Id. ¶¶ 3-4). Given the conclusions reached herein regarding the third element of the claim, the Court need not and does not decide whether Lyft is a public accommodation under the ADA.

A. Reasonable Modifications Theory

With respect to the first provision, which is referred to herein as the “reasonable modifications theory,” the ADA provides that “discrimination” includes,

a failure to make reasonable modifications in policies, practices, or procedures, when such modifications are necessary to afford such goods, services, facilities, privileges, advantages, or accommodations to individuals with disabilities, unless the entity can demonstrate that making such modifications would fundamentally alter the nature of such goods, services, facilities, privileges, advantages, or accommodations.

42 U.S.C.A. §§ 12182(b)(2)(A)(ii), 12184(b)(2)(A).

Under the reasonable modifications theory, a defendant discriminates by: (1) having a policy, practice, or procedure that impedes the ability of people with disabilities to access its service; and (2) failing to implement “reasonable” modification(s) to those policies, practices, or procedures. (See Pl. Br. at 6 (citing 42 U.S.C. § 12182(a), (b)(2)(A)(ii); id. § 12184(a), (b)(2)(A))). Plaintiffs “bear[] the initial burdens of both production and persuasion as to the existence of an accommodation” and the effectiveness of the modification proposed. (Doc. 414, “JPFC” ¶ 85 (citing Dean v. Univ. at Buffalo Sch. Of Med. & Biomedical Scis., 804 F.3d 178, 189-90 (2d Cir. 2015); Borkowski v. Valley Cent. School Dist., 63 F.3d 131, 138 (2d Cir. 1995); Staron v. McDonald's Corp., 51 F.3d 353 (2d Cir. 1995))).²⁰ An effective modification is one that accommodates the plaintiff's disabilities, and affords access to the service allegedly denied. See U.S. Airways, Inc. v. Barnett, 535 U.S. 391, 399-400 (2002) (“An ineffective ‘modification' or ‘adjustment' will not accommodate a disabled individual's limitations.”); Roberts, 542 F.3d at 372 (plaintiffs bear initial burden of production that the “desired access” may be achieved by the modification proposed). (See also JPFC ¶ 86).

20 The Court cites herein to the parties' Joint Proposed Findings of Fact and Conclusions of Law to the extent such findings and conclusions are undisputed and supported by the record and law.

“[T]he determination of whether a particular modification is ‘reasonable' involves a factspecific, case-by-case inquiry that considers, among other factors, the effectiveness of the modification in light of the nature of the disability in question and the cost to the organization that would implement it.” Castillo v. Hudson Theatre, LLC, 412 F.Supp.3d 447, 451 (S.D.N.Y. 2019) (quoting Staron, 51 F.3d at 356). “In deciding what's reasonable, facilities may consider the costs of such accommodations, disruption of their business and safety. But they must also take into account evolving technology that might make it cheaper and easier to ameliorate the plight of the disabled....As new devices become available, public accommodations must consider using or adapting them to help disabled guests have an experience more akin to that of non-disabled guests.” (JPFC ¶ 90 (quoting Baughman v. Walt Disney World. Co., 685 F.3d 1131, 1135 (9th Cir. 2012)). “[T]he plaintiff's burden does not require him or her to furnish exact or highly detailed cost estimates.” Roberts, 542 F.3d at 371.

“[A] defendant need not make an accommodation at all if the requested accommodation ‘would fundamentally alter the nature of the service, program, or activity.'” Powell v. Nat'l Bd. of Med. Examiners, 364 F.3d 79, 88 (2d Cir. 2004). Thus, the defendant, should the plaintiff meet their initial burdens, has the burden of proving as an affirmative defense, that making such modifications would fundamentally alter the goods or services that it offers. PGA Tour, Inc. v. Martin, 532 U.S. 661, 682 (2001) (citing 42 U.S.C. § 12182(b)(2)(A)(ii)).

B. Barrier Removal Theory

With respect to the second theory of discrimination at issue, which is referred to herein as the “removal of barriers,” the ADA provides that “discrimination” includes,

(iv) a failure to remove architectural barriers, and communication barriers that are structural in nature, in existing facilities, and transportation barriers in existing vehicles and rail passenger cars used by an establishment for transporting individuals (not including barriers that can only be removed through the retrofitting of vehicles or rail passenger cars by the installation of a hydraulic or other lift), where such removal is readily achievable . . .

42 U.S.C. §§ 12182(b)(2)(A)(iv), 12184(b)(2)(C).

Under the ADA's plain language, “barriers” that are subject to removal are architectural barriers, communication barriers that are structural in nature, and transportation barriers in existing vehicles. Id. Plaintiffs bear the burden of production to identify a barrier and to come forward with a plausible proposal for its removal. Roberts, 542 F.3d at 370-71. “Neither the estimates nor the proposal are required to be exact or detailed, for the defendant may counter the plaintiff's showing by meeting its own burden of persuasion and establishing that the costs of a plaintiff's proposal would in fact exceed the benefits. Because the concept of “readily achievable” is a broad one, either party may include in its analysis, as costs or benefits, both monetary and non-monetary considerations.” Id. at 373. (See JPFC ¶ 189).

“[O]nce a plaintiff ‘articulates a plausible proposal for barrier removal, the costs of which, facially, do not clearly exceed its benefits,' the burden shifts to the defendant to “prove that the proposals were not readily achievable.” Kreisler v. Second Ave. Diner Corp., 731 F.3d 184, 189 (2d Cir. 2013) (quoting Roberts, 542 F.3d at 373, 378). The defendant must “establish that the costs” of the barrier removal proposal “would in fact exceed the benefits.” Roberts, 542 F.3d at 372-73.

II. NYSHRL

Plaintiffs' second claim for relief against Defendant alleges, as modified by the Joint Pretrial Order (Doc. 20 ¶¶ 125-150; Doc. 421 at 4-6), disability discrimination under NYSHRL §§ 296(2)(a), 296(2)(c)(i), and 296(2)(c)(iii).²¹ Plaintiffs' claims of discrimination under the NYSHRL are governed by the same legal standards as govern their federal ADA claims. (JPFC ¶ 70 (quoting Graves v. Finch Pruyn & Co., 457 F.3d 181, 184 (2d Cir. 2006)); see also Docs. 323, 339-1, 349-1).

21 The Court notes that Plaintiffs, in the Joint Pretrial Order, purport to seek relief under each of subsections (c)(i)-(iii) of NYSHRL § 296, but only pressed claims under subsections (c)(i) and (iii). (See Doc. 421 at 22). The Court assumes this was a typographic error and in any event, Plaintiffs are not entitled to relief under a subsection they did not assert or try.

ANALYSIS

I. Plaintiffs Fail to Establish Reasonable Modifications

Plaintiffs, to succeed on the reasonable modifications theory of discrimination under the ADA and NYSHRL, bear the burden to prove that Defendant: (1) has a policy, practice, or procedure that impedes the ability of people with disabilities to access its service; and (2) fails to implement “reasonable” modification(s) to those policies, practices, or procedures. (Pl. Br. at 6).

Plaintiffs allege that Lyft denies individuals “full and equal enjoyment” of its services “in violation of Title III of the ADA” “[b]y failing to make [WAVs] adequately available through its transportation services” and “[b]y forcing users of motorized and other non-folding wheelchairs to wait significantly longer to obtain rides from [WAVs] than other users wait to obtain rides through its transportation services.” (Doc. 20 ¶¶ 136-137). Plaintiffs have also consistently taken the position that the policy, practice, or procedure at issue is Lyft's alleged “categorical[ ] block[ ]” of WAVs appearing as such on Lyft's App (see, e.g., Doc. 272, Doc. 284; see also Pl. Opp. at 9 (“Throughout this litigation, Plaintiffs have sought an order that Lyft change its policy of blocking WAV service in Westchester and allow Lyft WAVs in Westchester to pick up Lyft customers”)). At the class certification stage, this Court confirmed that Plaintiffs' theory of discrimination-the “accurate depiction of the case”-was about “reasonable modifications” to Lyft's “policies, practices, and procedures” that are “necessary to afford on-demand WAV service” “with equivalent reliability and similar wait times as inaccessible vehicles” and not about an option in the App. (Doc. 365 at 3-4, 10). Plaintiffs, at trial, shifted gears and attempted to frame the issue as Lyft's failure to provide Plaintiffs the opportunity to request a WAV-regardless if one is available-that constitutes the challenged policy, practice, or procedure. (Pl. Br. at 2-3).²²Plaintiffs' new theory (that simply adding an icon in the App constitutes “equal access” under the ADA) is inconsistent with the position it took throughout this litigation. Again, this case is about transportation, not an option in an App.²³ Plaintiffs' attempts to recast the claims asserted in this action impermissibly makes the case “a moving target that the Court declines to entertain.” See Tyson v. Town of Ramapo, 677 F.Supp.3d 173, 182 (S.D.N.Y. 2023), aff'd, No. 23-1018-CV, 2024 WL 2890395 (2d Cir. June 10, 2024).

22 To the extent Plaintiffs have suggested that Lyft's policy that does not allow any driver licensed by the TLC to pick up riders in Westchester County should be changed, Plaintiffs did not propose any such modification and have not demonstrated that such modification would be effective.

23 Defense counsel made a compelling analogy in her opening statement at trial. If the case was about riders simply being able to see the option of Access mode in the App, even if no rides are available, “[t]hat would be like requiring a bookstore, which the regulations make clear is not required to buy Braille books, to have an empty shelf showing where those Braille books would go. An icon with no rides. It's a book shelf with no books.” (Trial Tr. at 42).

The essence of the policy, practice, or procedure at issue in this litigation is that Lyft does not offer Access mode in the Non-Access Regions, thereby impeding the ability of people with disabilities who require WAVs to travel to access Lyft's transportation services. This is, for all intents and purposes, a demand that Lyft modify the services that it offers on its platform in all Regions and not necessarily a proposed modification of Lyft's policies, practices, or procedures. Title III of the ADA does not “regulate what types of goods and services should be made available” but that is precisely the relief Plaintiffs here seek here. Calcano v. Swarovski N. Am. Ltd., 36 F.4th 68, 84 (2d Cir. 2022) (Lohier, J., concurring) (citing Weyer v. Twentieth Century Fox Film Corp., 198 F.3d 1104, 1115 (9th Cir. 2000)). Courts in this Circuit-and throughout the country-“have consistently held that a business is not required to alter or modify the goods or services it offers to satisfy Title III.” Bunting v. Gap, Inc., No. 22-CV-07015, 2024 WL 343631, at *2 (E.D.N.Y. Jan. 30, 2024) (collecting cases).

In any event, even assuming that Plaintiffs have identified a policy, practice, or procedure that could be modified, they have not met their initial burden of establishing that the modifications they propose are “reasonable” in terms of effectiveness, costs, and benefits. (See JPFC ¶¶ 85, 86). Dean, 804 F.3d at 189-90; Borkowski, 63 F.3d at 138; Staron, 51 F.3d at 355-56, 358.

An “effective” modification in the context of this action is one that will provide Plaintiffs with access to transportation by WAVs. PGA Tour v. Martin, 532 U.S. 661, 688 (2001). Trial testimony made clear that Lyft's platform is premised on supply and demand. When more consumers are using the Lyft App, more drivers will drive on the Lyft App, which attracts more riders to the platform, which then attracts more drivers, and creates a “positive feedback loop or virtuous circle.” (Trial Tr. at 663-664, 709-712; JE 9 ¶¶ 5, 10). Where either or both supply and demand are lacking in a Region, the platform will fail. (Trial Tr. at 662-663). Thus, each of Plaintiffs' proposed modifications must be considered in that context: whether Plaintiffs have demonstrated, by a preponderance of the evidence, the modification will result in effective WAV transportation based upon the basic principles of supply and demand which are the bedrock of the rideshare platform industry.

Plaintiffs propose the following eight modifications:²⁴ (1) remove the current categorical preclusion (“blocker”) of WAVs on Lyft's platform in the Non-Access Regions and prevent implementation of Lyft's hidden Access mode toggle to view WAV options on the App's home screen; (2) ask all drivers on its platform in the Non-Access Regions and those onboarding in the Non-Access Regions whether they have access to WAVs and whether they are interested in driving WAVs on Lyft's platform; (3) utilize cross-dispatching (i.e., allow WAV drivers to receive and accept ride requests for different ride modes) for all drivers; (4) implement prioritization logic for Access mode (i.e., whereby Lyft prioritizes dispatching WAVs to riders seeking WAVs to ensure efficient vehicle allocation); (5) increase marketing for Access mode and WAV service, including targeted advertising; (6) offer potential drivers baseline bonuses and incentives for guaranteed periods of time; (7) include WAVs as an option in Lyft's Express Drive and FlexDrive programs; and (8) form partnerships with car rental, taxi, and other transportation companies that have WAVs. (JPFC at 26-68; Doc. 424 at 8-15; Doc. 427 at 6-10; Pl. Br. at 9-22; Lyft Opp. at 10-24; see also Doc. 421 at 4-6, 22-23).

24 The Joint Pretrial Order (Doc. 421) lists the same proposed modifications in a slightly different order than was presented in the parties' Proposed Findings of Fact and Conclusions of Law (See JPFC at 26-68) and pretrial briefing; and Plaintiffs' post-trial briefing took a different sequence from both. The Court adopts the numbering and sequence set forth in the parties' Proposed Findings of Fact and Conclusions of Law. After the trial was completed, Plaintiffs withdrew their ninth proposed modification that would direct Lyft to implement a ten-cent accessibility surcharge on all rides nationwide. (See Pl. Br. at 2 n.4).

A. Plaintiffs' First Proposed Modification

The first modification proposed by Plaintiffs is that Defendant “remove the current block in place on the App in the non-Access Regions, which prohibits Access mode from being available for drivers or riders, and prevent implementation of Lyft's toggle requirement, which hides Access mode from riders.” (JPFC ¶ 95; Doc. 421 at 3-4). As an initial matter, Plaintiffs did not present any evidence that anything is being “blocked.” Thus, the requested modification can just as easily be described as “turn[ing] on” or “displaying” or “launching” Access mode and eliminating the toggle feature. (See, e.g., Trial Tr. at 449-450 (Mr. Elegudin referencing the “launch” of the TLC Accessible Dispatch program, when TLC “turned on the mode” and the “specific feature was now available” and suggesting that by Lyft “having the mode be available, would be a way to increase supply.”)).

Semantics aside, this proposed modification at first blush would seem sensible and fair, considering Standard mode appears as an available service in every one of more than 300 Regions in which Lyft operates. Essentially, Plaintiffs propose that Lyft display Access mode as an available option just like Standard mode; eliminate the feature which prevents the App from displaying Access mode in Access Regions unless the user toggles it on; and then wait and see what happens. Plaintiffs' burden of proof, however, requires that they establish the effectiveness of the proposed modification, one that accommodates the plaintiff's disabilities, and affords access to the service allegedly denied. “No federal court has ever held that an iterative, experimental, or trial-and-error proposal constituted a reasonable modification to a policy, practice, or procedure under Title III.” Independent Living Resource Center San Francisco v. Lyft, Inc. (“ILRC”), No. C-19-01438, 2021 WL 3910719, at *10 (N.D. Cal. Sept. 1, 2021).

Plaintiffs' offer of proof consisted of Mr. Elegudin's opinion that “removing the blocker” would increase supply and demand (Trial Tr. at 445-446); Ms. Stern's charts purportedly demonstrating there were more than 500 WAV drivers in Lyft's system driving into Westchester and Nassau counties in January 2021 (Id. at 318-323; Tr. Exs. 110, 111); and the testimony of Messrs. Bussani and Ruprecht concerning the existence of WAV retro-fitting dealers in and around Westchester County (Trial Tr. at 246-249). (See Pl. Br. at 9-12).

Mr. Elegudin did not offer any quantification of supply beyond his speculation that WAVs driving in NYC routinely travel to Nassau, Suffolk, and Westchester counties. He did not offer any quantification of demand, instead offering his ultimate opinion, which was based on his experience with the TLC and his review of data from the Access Regions. While the Court does not discount Mr. Elegudin's experience with the TLC (he was qualified as an expert in disability services, regulations, compliance, and accessibility), it important to highlight the difference between that experience and the opinion being offered: the TLC is a regulatory agency that regulates access to transportation in NYC. (Trial Tr. at 380:14-19). The availability of WAV supply in NYC is due in large part to the regulatory scheme in place there. Because there is a TLC licensing requirement in place, the TLC took the steps required to increase the number of WAVs in the market; and with a combination of regulations, significantly increased the overall number of TLC-licensed WAVs in NYC. (JE 9 ¶ 25; Trial Tr. at 168-169, 491-492). That experience with the TLC is unlike the circumstance presented by the proposed modification here, which has no tether to any regulation, requirement, or other rule which requires the increase of WAV supply.

Mr. Elegudin offered no opinion as to the quality of any transportation that might result from simply turning on Access mode in Non-Access Regions, such as how many drivers with WAVs would drive on Lyft's platform or what the wait times or completion rates for WAV rides would be if this change were made.

With respect to Ms. Stern, the Court gives no weight to the charts that she prepared and which were discussed at trial and cited by Plaintiffs to support the proposed modifications. Based upon her own testimony, the charts were incomplete summaries predicated upon assumptions not verified by the creator of the underlying data.²⁵ For example, as regards Exhibits 110 and 111 which were cited for the proposition that there were at least 500 WAVs on Lyft's platform in Westchester in January 2021, data concerning the sum of hours spent by WAV drivers in NonAccess Regions was not included or calculated, despite its production and availability. Mr. Bozorgirad testified that the reason those WAV drivers appeared in the Non-Access Region was likely because they were dropping off riders from NYC (an Access Region) to their destination in Westchester (a Non-Access Region). (JE 10 ¶ 10). Without understanding the nature and circumstance of those WAVs appearing in Westchester County, the raw fact that they were there does not prove that those drivers were able and willing to pick up riders and provide WAV rides at the time they were in Westchester County.

25 These include Trial Exhibits 6, 10, 11, 15, 29, 106, 107, 108, 110, 111, 112, 113, 114, and 115.

Testimony that some number of WAVs may exist in Westchester County does not establish that it is more likely than not that the existence of such unquantified supply would enable effective transportation by WAVs utilizing Lyft's platform. Plaintiffs offered no empirical support to tie the potential supply of WAVs in Westchester County to evidence of effective WAV transportation via Lyft's App. In other words, there is no credible proof in this record of the number of drivers with WAVs that would pick up passengers on Lyft's platform if Access mode were to be turned on in Non-Access Regions.²⁶ The concept of “turn it on and see what happens” is the kind of experimental, trial-and-error proposal that does not constitute a reasonable modification to a policy, practice, or procedure under Title III. This reality is especially so when considering the nature of this action as a class. Plaintiffs want Lyft to turn on Access mode throughout the United States. The lack of proof concerning the reasonableness of this modification is overwhelming; and is fatal to the first proposed modification.

26 With respect to the toggle, Plaintiffs established that when the TLC, using its regulatory powers, recommended that Lyft eliminate the toggle feature, and Lyft did so, the trip volumes went up by 500 percent. (Trial Tr. at 428). This does not establish that eliminating the toggle in Non-Access Regions would yield the same results as NYC, as conditions in NYC are unique due in large part to the regulatory mechanisms in place as discussed supra. Population density in NYC is also a factor. Further, Plaintiffs did not suggest or establish that eliminating the toggle will create WAVs. Rather, it would arguably increase demand in regions where Access mode is already an available option. In other words, a direction that Lyft eliminate the toggle requires that Plaintiffs establish as a threshold condition that Access mode is turned on such that WAVs are already present on the Lyft platform.

Even if Plaintiffs had shown by a preponderance of the evidence that turning on Access mode would lead to the transportation requested by Plaintiffs, Defendant has offered proof that rebuts the initial burden and establishes the first proposed modification would be neither effective nor reasonable in cost. Dr. Rysman's testimony confirmed that simply turning on Access mode would not create effective WAV transportation due to the low population density of WAV users; and without sufficient supply or demand, the platform would fail. Although Dr. Rysman's opinions are predicated upon data which is not without its flaws, the Court is convinced, by a preponderance of the evidence (and equally because it is simply intuitive), that where there are less people there is less supply and less demand, longer wait times, and lower completion rates. Lyft also established that where it has implemented Access mode, it has had to independently supplement the WAV supply to ensure that rides can take place, as an organic WAV supply needed to support a functioning platform does not otherwise exist. (JE 2 ¶¶ 16-19, 32; JE 9 ¶ 29). For example, in NYC, even with a regulatory increase in the number of IC drivers, Lyft still used W-2 drivers and even experimented with a rental model in an effort to reach the WAV service metrics required of it. (Trial Tr. at 754; JE 2 ¶¶ 22-25; JE 9 ¶¶ 20-25).

Before Lyft can launch Access mode in any region based on an IC model (as Plaintiffs have proposed in this first modification), it must put in place operational processes necessary to ensure that the drivers actually have a WAV that meets the necessary requirements for operation on a ridesharing platform, that the vehicle meets the ADA technical standards and/or similar local regulations, and that drivers have received the proper training. See 49 C.F.R. § 37.7(a) (“a vehicle shall be considered to be readily accessible to and useable by individuals with disabilities if it meets the requirements of this part and the standards set forth in part 38 of this title”); id. § 37.173 (requiring training to ensure safe operation of equipment and appropriate assistance to riders with disabilities). (See also Trial Tr. at 160-161; JE 2 ¶¶ 35-36).

In other words, were Lyft to turn on Access mode in Non-Access Regions and WAVs were found in a region, Lyft must have administrative mechanisms in place for driver training and vehicle inspection in that region. And as Mr. Elegudin testified based on his review of the regulations in the nine Access Regions, most Access Regions have training regulations. (Trial Tr. at 413; see also id. at 67-70). Additionally, were Lyft to turn on Access mode in a Non-Access Regions and WAVs were not found, it is logical to conclude that WAV riders would be disappointed that they cannot get a ride despite the presence of a WAV option on the Lyft App, resulting in reputational damage and the prospect of lawsuits. (JE 2 ¶ 35). Indeed, in this action, Plaintiffs' offer of proof in support of their theory of discrimination included anecdotes of WAV-riders becoming stranded, unable to obtain a ride home from their destination because no WAVs were available. (See JE 4 ¶¶ 37-45). And class members have testified that such a circumstance makes service unreliable and would deter them from using Lyft. (JE 11 at 2-4; Trial Tr. at 687, 691-692). Although Plaintiffs offered evidence that some service is better than no service (see e.g., Trial Tr. at 208-209 (“any service is better than none”); id. at 427), as set forth supra, Plaintiffs did not nor quantify or qualify their reasoning for this proposition, nor did they establish how the option of merely displaying an icon in the App would create any service at all.

The evidence at trial also established that the number of WAVs are small, as the number of people who rely on WAVs is 1% or less of the population. (Trial Tr. at 189-190, 713-714). The evidence also established that WAVs are expensive and unique. A WAV is not manufactured. WAVs are created in the after-market by taking a standard minivan and modifying it to add accessible equipment. (JE 7 at 2; JE 8 ¶ 13; Trial Tr. at 240-241, 685-686). Given the higher acquisition, maintenance, and fuel costs, Lyft would have to offer incentives to WAV drivers to ensure that providing WAV rides makes economic sense. (JE 2 ¶ 36). A lack of IC WAV supply would require Defendant to artificially create a supply through the W-2 model at an hourly rate with the partner that will vary by city and by company. (SF ¶ 40). In short, merely “opening up” Access mode will not provide transportation, as it cannot be accomplished without related costs and burdens to manage, create, regulate, and incentivize WAV supply.

Put simply, directing Lyft to make Access mode an available option in Non-Access Regions (and eliminating the toggle when the Access mode option is available) has not been shown to be effective in providing WAV transportation. Nor has it been shown that the modification is reasonable in cost. Accordingly, Plaintiffs have not demonstrated that the failure to make the first proposed modification is discriminatory within the meaning of the ADA or NYSHRL.²⁷

27 Given this conclusion, the Court need not reach Lyft's affirmative defense of fundamental alteration. The Court notes, however, that two other courts that have considered the fundamental alteration defense with respect to expanding WAV service reached the conclusion that because the rideshare company provides WAV service in certain regions, providing WAV service in additional regions would not constitute a fundamental alteration of its business. ILRC, 2021 WL 3910719, at *8; Crawford v. Uber Techs., Inc., 616 F.Supp.3d 1001, 1009 (N.D. Cal. 2022), aff'd, No. 22-16292, 2023 WL 7123772 (9th Cir. Oct. 30, 2023).

B. Plaintiffs' Second Proposed Modification

Plaintiffs' second proposed modification is to “ask all drivers on Lyft's platform and those onboarding whether they have access to WAVs.” (JPFC ¶ 114; Doc. 421 at 4). But asking the question will not create WAVs that do not otherwise exist. Plaintiffs did not offer any evidence estimating the number of drivers with WAVs that Lyft might be able to identify if this question were added to its onboarding flow in any Non-Access Region. The evidence to which Plaintiffs refer in support of this proposed modification is a false syllogism: Lyft asks Standard mode drivers about the make and model of their vehicles and checks the public databases to ensure that the drivers' descriptions are accurate. Standard mode drivers cannot drive on Lyft's platform unless they have answered questions about their vehicles and the vehicle has checked out. Plaintiffs suggest therefore that requiring drivers to answer questions about whether they have access to WAVs will increase WAV supply. (Pl. Br. at 15). Asking the question may not address the supply issue because there is no public database establishing that a new vehicle has been modified to become a WAV. Mr. Elegudin did not quantify the supply that this proposed modification would yield. Rather, he explained, with reference to his experience with the TLC, that in connection with implementing new regulations, the TLC required as a licensing requirement that drivers identify whether they had a WAV. (Trial Tr. at 451). As with the first proposed modification, there is a stark difference between a regulatory body's licensing requirement, and directing that an inquiry be made by a private on-demand transportation platform with no way of verifying the driver's answer.

The only other witness offered by Plaintiffs who testified on this subject was Ms. Gerundio, who testified that in response to promotional messages (asking drivers whether or not they owned a WAV) sent to over 26,000 drivers in August 2020 in the Philadelphia and Delaware markets, only one additional driver began driving a WAV on the platform in Philadelphia. (JE 2 ¶ 18).

Even if Plaintiffs had shown by a preponderance of the evidence that asking drivers whether they have WAVs would lead to the transportation requested by Plaintiffs in all Regions, Defendant has offered proof that rebuts the initial burden. Dr. Rysman explained that providing WAV rides creates no economic incentive for drivers because Lyft does not charge more for WAV rides, drivers collect the same amount as in Standard mode, and WAV rides are shorter on average but take more time than Standard mode rides. (Trial Tr. at 725). Shorter WAV rides taking more time than Standard mode rides means more driver time not being utilized, driving down revenue, with higher costs. (Id.).

Mr. Bozorgirad's testimony provides more clarity on why asking drivers whether they have WAVs would not necessarily increase WAV supply at all. Drivers with WAVs can elect to accept rides in Access mode or in Standard mode, but most of these IC WAV drivers spend their time servicing Standard mode and clustering in areas with the highest density of Standard mode demand. (JE 10 ¶¶ 16-23). The sum total of this reality is that when WAV drivers are not available because they are engaged in a Standard ride, the WAV rider will have a worse user experience, wait longer for a ride, or not be matched with a ride at all, and if that happens enough, they will stop using Lyft. (Id. ¶ 24).

As discussed supra, WAVs are small in number, and expensive. Given the limited number of WAVs on the road, the high cost of retro-fitting one ($16,000-25,000), and lack of economic benefit to drivers, the notion that simply asking the question of Lyft drivers would be effective in creating a WAV supply is pure speculation belied by the evidence at trial. Accordingly, Plaintiffs have not demonstrated that the failure to make the second proposed modification is discriminatory within the meaning of the ADA or NYSHRL.

C. Plaintiffs' Third Through Eighth Modifications

Plaintiffs' expert, Mr. Elegudin, opined that other than turning off the blocker and asking drivers whether they have a WAV, none of the other proposed modifications are essential. (Trial Tr. at 429, 468). He explained that the other proposed modifications “have to do with efficiency” as they “would allow Lyft to provide access mode service in a more efficient manner, it would allow service levels to ramp up in a faster manner, and would ultimately help the economics of the service.” (Id. at 468). In other words, as Plaintiffs' expert witness is not of the opinion that the third through eighth modifications afford the WAV service Plaintiffs request in this action, the Court could conclude that Defendant's failure to make such modifications does not constitute discrimination under the ADA or NYSHRL. In any event and notwithstanding Plaintiffs' expert's testimony, the Court has considered the third through eighth proposed modifications and concludes that Plaintiffs have not established their implementation would result in effective WAV transportation.

The third and fourth proposed modifications propose that Lyft utilize cross-dispatching and prioritization logic for all drivers on Lyft's platform. These modifications presuppose that Plaintiffs established, as a threshold condition, that Access mode needs to be turned on in NonAccess Regions and WAVs will already be present and available on the Lyft platform. Clearly, an IC driver cannot be cross-dispatched to Access mode unless Access mode exists in the first place. “Cross-dispatching goes hand-in-hand with prioritization logic.” (Pl. Br. at 18). Plaintiffs' evidence established that Lyft utilizes cross-dispatching of IC drivers in some of the existing Access Regions and also uses prioritization logic. (Trial Tr. at 107-108, 111, 457-458; JE 10 ¶ 16). But Plaintiffs have not established that Lyft must turn Access mode on in the Non-Access Regions, as set forth supra with respect to their first proposed modification.

Even if Plaintiffs had established that threshold condition, they have not established how directing Lyft to utilize cross-dispatching and prioritization logic for all drivers on the platform would create effective WAV transportation. Mr. Elegudin's testimony that his proposed modifications of increasing and utilizing cross-dispatching and prioritization logic for WAVs would increase supply was based upon his experience at the TLC-which again, involved regulatory intervention in NYC. These proposed modifications are also based upon his review of data in this case with Ms. Stern's assistance, which he believes demonstrates that when Lyft utilized cross-dispatch it improved the economics of the cost per trip (it decreased) and there was minimal change in service levels. (Trial Tr. at 453-456). Ms. Stern testified that the summary chart data she prepared based costs per trip on the lowest 50% of the data for all Regions (Trial Tr. at 372-373), which the Court has determined renders the conclusions in the modeling unreliable. Selectively choosing data to obtain a conclusion favorable to Plaintiffs is not a valid basis on which to conclude anything. Ms. Stern also testified that the cross-dispatching analysis she performed was for W-2 drivers who are on the platform by contract, such that cross-dispatching those drivers would not increase the supply of WAVs. (Tr. Tr. at 355-356).²⁸

28 Plaintiffs also rely on the designated deposition testimony of Mr. Gupta, who confirmed that he wrote the following sentence in an email in 2017: “I do believe enabling some sort of cross-dispatch of WAV vehicles would make it easier to onboard drivers and increase utilization.” (Trial Tr. 577:19-578:2). Mr. Zhou had testified that Lyft found the positive financial effects of cross-dispatching W-2 drivers was the completion of more rides, which for the business meant one extra driver available in the market, and helped the driver who normally sat around idle keep more attentive in their job. (Id. at 616-617). He also testified that those findings were “incremental but small” and meant “slightly more . . . money coming in.” (Id. at 617:11-20). In other words, permitting those contracted drivers of WAVs to pick up Standard mode passengers produces some unquantified benefit to Lyft - but it does not mean there are more WAV rides or more WAV supply. This evidence does not establish that cross-dispatching all drivers and utilizing prioritization logic would increase the supply of WAV drivers on the Lyft platform, or by how much, to achieve effective WAV transportation.

In any event, Defendant offered proof that cross-dispatching W-2 drivers would make those drivers unavailable for WAV rides. Specifically, Lyft's experimentation revealed that crossdispatching W-2 drivers showed they were not able to complete as many Access mode rides and therefore, in most markets, the benefit of cost savings from cross-dispatching was outweighed by the negative impact on service levels. (JE 10 ¶¶ 16, 28-32, 35; Trial Tr. at 107-108, 644). Plaintiffs have failed to prove that their third and fourth modifications would result in effective WAV transportation.

Plaintiffs' fifth proposed modification is that Lyft increase “some level of advertising and marketing” for Access mode and WAV service, “[t]o supplement the first modification.” (Pl. Br. at 14). Plaintiffs offered Mr. Elegudin's testimony that when he worked at the TLC, they “invested significantly for [the Accessible Dispatch Program]” which increased demand. (Trial Tr. at 447448). Lyft spends hundreds of millions of dollars to market their services in Standard mode, which “clearly shows its purpose for increasing demand.” (Id. at 448). Plaintiffs also offered Mr. Zhou's testimony in which he explained that advertising temporarily increases demand but does not provide an accurate picture of steady supply. That result, Mr. Zhou suggests, is problematic because without an accurate picture, supply cannot be matched to demand for WAVs as it can be in Standard mode. (Trial Tr. at 590-593). The sum total of this evidence is that directing Lyft to engage in “some” marketing (perhaps hundreds of millions of dollars of marketing), would likely increase demand for WAV service without consideration of commensurate supply. There is no evidence that marketing would result in a larger supply of WAVs or WAV drivers. Nor have Plaintiffs provided any cost estimate for the unspecified marketing they request, let alone a “plausible” cost estimate. Roberts, 542 F.3d at 370-72. Here too, Plaintiffs have failed to prove that this modification would result in effective WAV transportation.

With respect to the sixth proposed modification, that Lyft offer potential drivers baseline bonuses and incentives, Plaintiffs have not come forward with evidence that doing so would increase the supply of WAV drivers or lead to effective transportation. Plaintiffs did not provide evidence of any cost, including what the amount of each bonus or subsidy would be, or for how long such bonus or incentive would have to be paid. The lack of evidence precludes evaluation of the reasonableness of the proposal. Roberts, 542 F.3d at 370-72. Defendant came forward with evidence of the per-ride incentive Lyft pays to IC WAV drivers for every WAV ride completed; and demonstrated that Lyft loses money on almost every ride, meaning that “the more rides that are completed by IC WAV drivers, the more money that Lyft loses.” (JE 9 ¶ 32). Plaintiffs have failed to prove that the sixth modification would result in effective WAV transportation.

Plaintiffs' seventh proposed modification is that Lyft include WAVs as options in its Express Drive and FlexDrive programs. As an initial matter, Plaintiffs did not produce any detail about the programs, such as where Lyft currently offers the Express Drive program or FlexDrive programs, what it would cost Lyft to provide WAVs for rental through either Express Drive or FlexDrive, or what would happen if independent drivers did not want to rent these vehicles. In other words, while adding WAVs to a rental fleet would, obviously, create more vehicles, there is no evidence that it would create more drivers or riders of those WAVs. This failure of proof precludes any meaningful evaluation of the reasonableness of the proposed modification. Defendant established that it offered a rental program in NYC and ultimately terminated the program due to its high cost and lack of effectiveness. (Trial Tr. at 103-105, 187; JE 2 ¶¶ 22-25; JE 9 ¶ 22). Plaintiffs have failed to establish that the seventh modification would result in effective WAV transportation.

With respect to the eighth proposed modification, that Lyft explore and form partnerships with car rental, taxi, non-emergency medical transportation, and other transportation companies that have WAVs, Plaintiffs failed to establish this would result in effective transportation and failed to produce any evidence of cost. Plaintiffs established that in some Access Regions, Lyft employs the W-2 model which relies on contracting with third-party transportation companies to provide WAVs and WAV drivers, whereby Lyft pays the third-party companies a negotiated hourly rate. (SF ¶¶ 39-40). Plaintiffs also established that Messrs. Bussani and Ruprecht would be willing to negotiate and partner with Lyft. (JE 8 ¶¶ 20-22; JE 6 ¶ 18). However, neither were able to testify to the terms of any such partnership and were clear that they would only engage in such partnership if it had the potential to earn their companies a profit. (Trial Tr. at 245-246; JE 7 at 5-6). These were the only two partner transportation companies with WAVs that Plaintiffs identified. Defendants established that Lyft might have to start with as many as 20 contracted partner drivers if it were ordered to provide service in Westchester County alone, as it does in Los Angeles, a city close in square mileage to Westchester. (Trial Tr. at 124-125). Defendant also established that the costs of partnerships have ranged from $40-$65 per hour per vehicle. (JE 9 ¶ 22; JE 2 ¶ 21).

In addition to the lack of proof here, the law is very clear. The ADA does not require Lyft to provide WAVs. Noel v. N.Y.C. Taxi & Limousine Comm'n, 687 F.3d 63, 73 (2d Cir. 2012) (“In sum, Title II(A) does not obligate the TLC to use its licensing and regulatory authority over the New York City taxi industry to require that taxi owners provide meaningful access to taxis with persons with disabilities.”); see also Toomer v. City Cab, 443 F.3d 1191, 1195 (10th Cir. 2006). Title III of the ADA-the title under which Plaintiffs have brought their claims-governs private entities, and “expressly exempts taxi providers from purchasing or leasing ‘accessible automobiles.'” Noel, 687 F.3d at 73 (citing 49 C.F.R. § 37.29(b)). Thus, the proposed modification that would direct Lyft to partner with transportation companies to provide WAVs likewise fails.

Accordingly, Plaintiffs have not demonstrated that the failure to make the third through eighth proposed modifications is discriminatory within the meaning of the ADA or NYSHRL.

II. Plaintiffs Fail to Meet the Burden of Proof on the Barrier Removal Theory

Plaintiffs, to succeed on the barrier removal theory of discrimination under the ADA and NYSHRL, must identify a “barrier” defined in the statute and articulate a plausible proposal for its removal, the costs of which do not exceed its benefits. Kreisler, 731 F.3d at 189 (quoting Roberts, 542 F.3d at 373, 378). (JPFC ¶ 188).²⁹ Plaintiffs' theory is that Lyft imposes a barrier in the Non-Access Regions by blocking WAV service and not allowing Access mode to be displayed as an available service option.

29 Plaintiffs had previously argued that if Lyft demonstrated that the removal of a barrier under 42 U.S.C. §§ 12182(b)(2)(A)(iv) was not readily achievable, then Plaintiffs may establish the “alternative methods” prong of a discrimination claim: “a failure to make such goods, services, facilities, privileges, advantages, or accommodations available through alternative methods if such methods are readily achievable.” 42 U.S.C. §§ 12182(b)(2)(A)(v), 12184(b)(2)(C). Plaintiffs did not press this at trial, offer any evidence of “alternative methods,” or make any such argument in their post-trial memoranda. Because Plaintiffs' only theory concerning barrier removal is their proposal to display Access mode in the App and prevent implementation of the toggle, the Court need not and does not consider whether there exist any “alternative methods” to remove the purported barrier.

As an initial matter, Plaintiffs have not satisfied the Court of the existence of a barrier as defined in the statute. First, and as discussed supra in connection with Plaintiffs' first proposed modification, Plaintiffs did not present any evidence that anything is being “blocked” by Lyft. Second, the cases upon which Plaintiffs rely to support their argument that the “blocker” is a recognized barrier are not applicable to the claims at issue in this case. (Pl. Br. at 23 (citing Walters v. Fischer Skis U.S., LLC, No. 21-CV-01115, 2022 WL 3226352, at *7 (N.D.N.Y. Aug. 10, 2022); Duncan v. Skin Bar NYC, LLC, No. 19-CV-05188, 2021 WL 9204082, at *4 (S.D.N.Y. May 18, 2021); Robles v. Domino's Pizza, LLC, 913 F.3d 898, 905 (9th Cir. 2019))). These cases arise under 42 U.S.C. § 12182(b)(2)(A)(iii), which governs a private entity's responsibility to offer “auxiliary aids and services” to individuals with disabilities.³⁰ This is significant, as “auxiliary aids and services” is defined as equipment or services intended to assist individuals with hearing or visual impairments. See 42 U.S.C. § 12103(1); N.Y. Exec. Law § 296(2)(d)(ii). Even if Plaintiffs had established that Lyft was employing a digital “blocker” to block Access mode from appearing on the Lyft App, they have not cited any authority for the proposition that such a “blocker” applies to the types of barriers subject to removal under 42 U.S.C. §§ 12182(b)(2)(A)(iv) and 12184(b)(2)(C).

30 The Court in Duncan, in recommending the entry of default judgment against the defendant, did cite the barrier removal theory in addition to the “auxiliary aids and services” clause. 2021 WL 9204082, at *4. The access barrier at issue in that case, however, specifically concerned “access barriers to blind and visually impaired persons” and there is no allegation in this case that the Lyft App itself poses an access barrier to blind or visually impaired persons.

Additionally, and even if Plaintiffs had identified a barrier as defined in the statute, they have not articulated a plausible proposal for its removal, the costs of which do not exceed its benefits. With respect to the benefits of removing the blocker, as discussed supra in connection with the first proposed modification, Plaintiffs have not shown they would achieve effective WAV transportation. The only benefit Plaintiffs have shown they would receive is an icon on the Lyft App, which they characterize as the opportunity to request a WAV-regardless if one is available. Again, the discrimination claims here are about equal access to transportation services, not access to an icon in the Lyft App.

Even if access to an icon in the Lyft App constituted some benefit, Defendant established that the risks and costs outweigh any such benefit. As discussed supra in connection with the first proposed modification, the risks and costs to Lyft include reputational damage and the prospect of lawsuits, such as this one, which result when a service or product is held out to the public as available but ultimately is not and cannot be delivered.

Accordingly, Plaintiffs have not demonstrated that the failure to allow Access mode to be displayed as an available service option in Non-Access Regions is discriminatory within the meaning of the ADA or NYSHRL.

CONCLUSION

All can agree that expanding transportation options for people with disabilities is of great importance. While it appears that Lyft has been able to launch Access mode in nine Regions where the population is dense, business partners are available and willing, or regulations require WAVs and WAV drivers in order for Lyft to do business, Plaintiffs have not established under the ADA or NYSHRL that any of the proposed modifications would result in effective WAV transportation in Westchester County, New York State, or across Lyft's 300 other Non-Access Regions. Likewise, Plaintiffs have not established their barrier removal theory.

The Clerk of Court is respectfully directed to enter judgment for Defendant, dismiss Plaintiffs' Complaint with prejudice, and close this case.

SO ORDERED.