Accessibility
Chapter 7
The TNC Access for All Act (Senate Bill No. 1376) directs the CPUC to “establish a program relating to accessibility for persons with disabilities, including wheelchair users who need a wheelchair-accessible vehicle (WAV)”. Under the program, TNCs collect a fee on each trip which is remitted to an Access Fund to be used to pay for “on-demand transportation [...] to meet the needs of persons with disabilities, including wheelchair users who need a WAV”. TNCs may request an offset, or be exempted from remitting the fee, if they demonstrate that they meet standards established by the CPUC.
The CPUC is authorized by the TNC Access for All Act to collect data to manage the program. Accessibility data is regularly reported by TNCs to the CPUC in two ways: in the form of “Advice Letters” filed by a company when they seek an offset or exemption for a specific county and quarter, and in the Annual Reports. Additional accessibility data is also filed on an ad-hoc basis at the direction of the CPUC. The Annual Reports include the number of requests for WAVs, the statewide number of fulfilled requests, and the percent of fulfilled requests by month in the Accessibility Report. This section compares 2020 Public Annual Reports data from September 2019 to August 2020 with Advice Letter data that was reported for the same period.
How many requests for WAVs were received? How many were accepted?
Table 31 shows the number of TNC WAV requests and completed WAV trips by each company. Uber provided nearly all TNC WAV service in the state, receiving 95% of the nearly 230,000 WAV requests and providing 94% of the nearly 108,000 completed WAV trips. Uber completed 47% of the trip requests it received and Lyft completed 53%. As noted in Chapter 3, there were between 218 million and 277 million total TNC trips, so the 108,000 completed WAV trips account for less than 0.05% of all trips.
Metric | Uber | Lyft | Total |
---|---|---|---|
WAV Requests | 217,935 | 11,605 | 229,540 |
Completed WAV Trips | 101,594 | 6,158 | 107,752 |
Completion Rate | 47% | 53% | 47% |
How much WAV service is being provided?
Table 32 shows the amount of WAV service measured by average monthly hours of WAV service and number of WAV vehicles, compared to the WAV trips provided. The service reported by each company is dramatically different from each other and suggests that the companies are not reporting data consistently. For example, Uber reports nearly 20,000 times the hours of WAV service than Lyft. The data also suggests highly improbable service. Lyft’s data suggests that each vehicle provides approximately 19 seconds of service each month, compared to Uber’s much more logical 73 hours per vehicle. On the other hand, Uber’s data suggests they are providing 924 hours (nearly 38 days) of WAV vehicle hours for each trip they provide. Both companies report deploying far more WAVs than the actual number of WAV trips completed. Uber reports an average of 108,000 WAVs each month, about 13 vehicles for every WAV trip. Lyft reports an average of 79,000 WAVs each month, about 155 vehicles for every WAV trip. The lack of adequately defined or enforced data reporting requirements prevents a clear understanding of WAV service and undermines confidence that it is being regulated properly.
Metric | Uber | Lyft |
---|---|---|
Hours of WAV Service | 7,818,750 | 419 |
Number of WAV Vehicles | 107,542 | 79,471 |
WAV Trips | 8,466 | 513 |
Hours of WAV Service per Vehicle | 72.7 | 0.005 |
Hours of WAV Service per Trip | 923.5 | 0.8 |
WAV Vehicle per Trip | 12.7 | 154.9 |
Is the Annual Report WAV data consistent with data reported under the Access for All Act?
Both the Annual Reports and Advice Letters filed under the Access for All program contain data on the number of WAV requests. The Annual Reports include the total statewide WAV requests received by month, while the Advice Letters only contain data for selected counties and quarters in which a TNC is seeking an offset or exemption. While the data contained in the Annual Reports and the Advice letters will not match due to their different reporting parameters, they should be consistent and non- contradictory with each other.
Table 33 shows the amounts requested in offsets for the costs incurred in providing WAV service from October 2019 to June 2020, the period that the Advice Letters align with the TNC Annual Reports. Lyft was granted $3 million in offsets, an average of $772 for each completed WAV trip. Uber was granted $6.2 million in offsets, an average of $369 per trip. Lyft was awarded about twice the amount of offsets per completed WAV trip than was Uber.
Company | Original Requested | Final Requested | Total Approved | Completed Trips | Offsets / Trip |
---|---|---|---|---|---|
Uber | $6,706,249.37 | $6,150,320.55 | $6,150,320.55 | 16,689 | $368.53 |
Lyft | $3,272,905.77 | $2,261,560.70 | $2,261,560.71 | 2,930 | $771.86 |
Tables 34 through 37 compare WAV data in the Annual Reports and Advice Letters. Because the Advice Letters are not filed for every county and quarter, the Advice Letter totals should always be less than the Accessibility Report totals. These tables show that Uber’s Annual Reports are consistent with and do not contradict their Advice Letters, but that Lyft’s Annual Reports are inconsistent with the Advice Letters.
Table 34 compares Uber’s WAV requests in the Annual Report and Advice Letters. Uber’s Advice Letters contained 44% – 45% of the total WAV requests reported in the Annual Report.
Quarter | Accessibility Report | Advice Letters | Share of Annual Report Totals Reported in Advice Letters |
---|---|---|---|
2019 Q4 | 82,089 | 35,902 | 44% |
2020 Q1 | 65,053 | 28,952 | 45% |
2020 Q2 | 23,047 | 10,386 | 45% |
Table 35 compares Lyft’s WAV requests in the Annual Report and Advice Letters. The WAV requests in Lyft’s Advice Letters, submitted only for San Francisco and Los Angeles counties, exceeded the statewide totals of Lyft’s Annual Report for 2 of 3 quarters, which should not be possible. Lyft’s Annual Reports and Advice Letters reporting of WAV requests are inconsistent. This suggests the possibility that the Advice Letter data used as the basis for awarding Lyft $3 million in offsets may not comply with the requirements of the Access for All Program.1
Quarter | Accessibility Report | Advice Letters | Share of Annual Report Totals Reported in Advice Letters |
---|---|---|---|
2019 Q4 | 4252 | 392 | 9% |
2020 Q1 | 3344 | 3853 | 115% |
2020 Q2 | 1307 | 1572 | 120% |
Table 36 compares Uber’s completed WAV trips in the Annual Report and Advice Letters. Uber’s Advice Letters contained 16% – 32% of the total completed WAV trips in the Annual Report.
Quarter | Accessibility Report | Advice Letters | Share of Annual Report Totals Reported in Advice Letters |
---|---|---|---|
2019 Q4 | 38,119 | 6,189 | 16% |
2020 Q1 | 32,706 | 6,044 | 18% |
2020 Q2 | 14,032 | 4,456 | 32% |
Table 37 compares Lyft’s completed WAV trips in the Annual Report and Advice Letters. Lyft’s Advice Letters contained 17% – 100% of the total completedWAV trips in the Annual Report.
Quarter | Accessibility Report | Advice Letters | Share of Annual Report Totals Reported in Advice Letters |
---|---|---|---|
2019 Q4 | 1,923 | 318 | 17% |
2020 Q1 | 1,679 | 1,679 | 100% |
2020 Q2 | 933 | 933 | 100% |
How many accessibility complaints were received?
The CPUC has not standardized reporting requirements for accessibility complaints. In the absence of clear and consistent requirements, each company decides for themselves how they report accessibility complaints.
Table 38 compares the taxonomies Uber and Lyft use to report accessibility complaints and resolutions. Uber uses 4 codes to describe accessibility complaints, each describing a type of service denial. Lyft uses 6 codes to describe accessibility complaints. One of these codes is a combination of an alleged violation and a driver consequence, two are a combination of an alleged violation with a determination of the validity of the allegation, two are simple categories of service denial allegations, and the final code is, ambiguously, “wheelchair_accessibility_policy”. Uber uses 5 codes to describe the resolution, each of which describes a determination of the validity of the alleged violation, but does not describe corrective actions taken against the driver. Lyft uses 3 codes to describe the resolution, each of which is describes a corrective action taken against the driver.
Type | Uber | Lyft |
---|---|---|
Complaint |
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|
Resolution |
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While Uber and Lyft report complaints using different taxonomies, each identifies complaints that involve users of wheelchairs or other assistive devices and complaints that involve service animals. Table 39 shows the total complaints in these categories by company. Uber and Lyft collectively received 1,957 accessibility complaints, of which 1,743 (89%) were reported by Uber and 213 (11%) were reported by Lyft. Service denials to users of wheelchairs or other assistive devices totaled 191 complaints, service denials to people with service animals totaled 1,161, and other service denials totaled 604.
Complaint Type | Uber | Lyft | Total |
---|---|---|---|
Wheelchair or assistive device | 183 | 8 | 191 |
Service animal | 956 | 205 | 1,161 |
Other | 604 | 604 | |
Total | 1,743 | 213 | 1,956 |
The CPUC’s lack of standardized reporting requirements for the various types of accessibility complaints prevents a clear understanding of accessibility issues and hinders analysis and oversight.
< 6. Environment 8. Conclusions >
“We find that Lyft’s Advice Letter submittals that included pre-scheduled WAV trip data failed to comply with the requirements of the Access for All Program. Lyft unilaterally devised its own interpretation and calculation of ‘response time’ to apply to pre-scheduled WAV trips. More significantly, by including negative response times in its Advice Letter submittals, Lyft likely lowered its total aggregate response time amounts for all WAV trips in a given quarter and geographic area. This calls into question Lyft’s eligibility for offsets or exemptions after removal of the pre-scheduled WAV trips and the negative response time values.” Ruling on Data Submission for Pre-Scheduled Trips, p. 16 – 17 ↩︎