Quantifying the employment accessibility benefits of shared automated vehicle mobility services: Consumer welfare approach using logsums

Highlights

• Shared AV mobility services (SAMSs) can significantly increase job accessibility.

• Job accessibility benefits from SAMSs higher for workers in lower density areas.

• Job accessibility benefits from SAMSs slightly higher for low-income workers.

• Benefits of SAMS transit feeder commute mode minimal compared to SAMS-only mode.

• Job accessibility benefits heavily dependent on per-mile costs of SAMS modes.

Abstract

The goal of this study is to assess and quantify the potential employment accessibility benefits of shared-use automated vehicle (AV) mobility service (SAMS) modes across a large diverse metropolitan region considering heterogeneity in the working population. To meet this goal, this study proposes employing a welfare-based (i.e. logsum-based) measure of accessibility, obtained via estimating a hierarchical work destination-commute mode choice model. The employment accessibility logsum measure incorporates the spatial distribution of worker residences and employment opportunities, the attributes of the available commute modes, and the characteristics of individual workers. The study further captures heterogeneity of workers using a latent class analysis (LCA) approach to account for different worker clusters valuing different types of employment opportunities differently, in which the socio-demographic characteristics of workers are the LCA model inputs. The accessibility analysis results in Southern California indicate: (i) the accessibility benefit differences across latent classes are modest but young workers and low-income workers do see higher benefits than high- and middle-income workers; (ii) there are substantial spatial differences in accessibility benefits with workers living in lower density areas benefiting more than workers living in high-density areas; (iii) nearly all the accessibility benefits come from the SAMS-only mode as opposed to the SAMS+Transit mode; and (iv) the SAMS cost per mile assumption significantly impacts the magnitude of the overall employment accessibility benefits.

Introduction

Car manufacturers, technology companies, and ridesourcing companies are currently trying to develop fully-automated or driverless vehicles (AVs) (Muoio, 2016) with which most of them initially plan to offer mobility services rather than sell the AVs to individual consumers (Waymo, 2017, Wingfield, 2017). Companies and researchers envision these shared AV mobility service (SAMS) modes to be similar to existing vehicle-based shared mobility service modes—like those provided by Didi, Uber and Lyft—except the vehicles will be driverless and completely controlled by the mobility service provider, rather than individual drivers (Fagnant and Kockelman, 2014, Hyland and Mahmassani, 2018, Spieser et al., 2014). Researchers expect SAMS to be considerably cheaper than existing vehicle-based mobility services due mainly to the elimination of driver costs (Fagnant and Kockelman, 2015).

The recent academic (Fagnant and Kockelman, 2015, Mahmassani, 2016) and non-academic (Hars, 2010, Thompson, 2016) literature identifies significant potential economic and environmental benefits of AVs and SAMS modes, as well as potential pitfalls. These potential benefits and the major transportation system implications of AVs and SAMS modes have motivated significant research in recent years related to understanding the impacts of AVs and SAMS modes on: trip generation (Truong et al., 2017); land-use, energy, and emissions (Wadud et al., 2016); residential location choice (Zhang and Guhathakurta, 2018); and vehicle miles traveled and associated emissions (Auld et al., 2017, Fagnant and Kockelman, 2014, Hyland and Mahmassani, 2020). The present study aims to understand and quantify another potentially substantial impact of SAMS modes, namely, improved access to employment opportunities.

One of the main design objectives of transportation systems is to connect people to their jobs and other employment opportunities. However, many commuters face challenges accessing employment opportunities that ultimately limit their economic potential and quality of life, particularly low-income households that do not own personal vehicles and live in job-poor neighborhoods (Blumenberg and Ong, 2001). Employment accessibility challenges vary from country-to-country, state-to-state, city-to-city, and neighborhood-to-neighborhood; nevertheless, there are a few common challenges across most large non-Northeast Corridor (and non-Chicago) metropolitan areas in the United States that are particularly burdensome for workers in Southern California, including: (i) high parking costs and/or limited parking availability in dense employment and residential areas; (ii) long commute distances between residential areas and employment opportunities; and (iii) poor transit service quality in many areas. The combination of long commute distances and poor transit service quality are particularly burdensome for individuals who cannot physically operate a vehicle or cannot afford to purchase, insure, maintain, fuel, and park a personal vehicle. Moreover, the challenges have increased in recent decades for car-less workers as the spread of employment opportunities away from central business districts and into the suburbs makes planning and operating efficient transit routes challenging in many cases and unviable in others (Hu, 2015).

Fortunately, SAMS modes can potentially help address these employment accessibility challenges in the future as they (i) nearly eliminate the need to park in high parking cost areas (Zhang et al., 2015) and (ii) allow travelers to enjoy the accessibility benefits of personal vehicle travel, which Kawabata and Shen (2006) show are significant compared to transit in most areas (especially Southern California), without having to own and operate an expensive personal vehicle. While commuters will still need to pay for SAMS modes for commute trips, the purchasing, maintenance, and insurance costs associated with vehicle ownership can be spread across several SAMS users. Even operating (i.e. fuel) costs can be spread across multiple passengers if workers are willing to share rides with other travelers during the commute trip. SAMS modes also have the potential to improve employment accessibility for people who are unable to operate a personal vehicle due to various physical disabilities and impairments.

Given these beneficial aspects of SAMS modes in terms of employment accessibility, the goal of this study is to quantify the employment accessibility benefits of adding two SAMS commute modes to the transportation system (i.e. the choice set of commuters), relative to the existing transportation system, using a systematic and theoretically valid methodology that can:

• Provide a monetary measure of employment accessibility benefits for economic (e.g. cost-benefit) analyses

• Capture the key employment accessibility benefits of SAMS modes

• Incorporate heterogeneity in the population of workers with respect to the types of employment opportunities that are valuable to different segments of the working population

To meet this overarching goal and satisfy the methodological constraints, this study employs the logsum measure of accessibility, which is a welfare-based accessibility measure that can be converted to monetary terms for economic analyses. To capture the key employment accessibility benefits of SAMSs, this study adds two commute modes—SAMS-only and SAMS+Transit—to the mode choice set of workers and captures the beneficial attributes of the two SAMS modes (see Section 1.3). Lastly, to capture heterogeneity among workers, this study clusters workers based on their socio-demographic attributes using a latent class analysis (LCA) approach.

Specific objectives of the study include determining: (i) the distribution of benefits across worker segments to understand the equity implications of the SAMS commute modes; (ii) the spatial distribution of benefits across rural, suburban, and urban regions to understand the land value and associated spatial implications of the SAMS commute mode benefits; (iii) the relative accessibility benefits of the SAMS-only and the SAMS+Transit commute modes to understand the market for each; and, (iv) the implications of SAMS cost-per-mile on overall employment accessibility benefits from the SAMS commute modes.

This study analyzes the employment accessibility benefits of adding two SAMS modes to the choice set of commuters, namely, the SAMS-only and SAMS+Transit commute modes. This subsection describes these two modes and their potential commuting benefits relative to existing travel modes.

In this study, the SAMS-only commute mode is effectively a ride-hailing/ridesourcing service with driverless vehicles. From a user-perspective the main difference between SAMS and current ride-hailing services is the travel cost/price (and the fact that the vehicle does not have a driver). The study assumes, as a result of the elimination of labor/driver costs and improved operational efficiency due to central control of the AV fleet, the SAMS-only mode is considerably cheaper than current ridesourcing services and even cheaper than the average cost per mile of personal vehicle travel. From a commute mode attributes perspective, the SAMS-only mode in this study is quite similar to a personal vehicle (e.g., the same in-vehicle travel times and zero walk distances) with three notable exceptions. First, the SAMS commute mode does not include any parking costs. Second, the cost per mile of SAMS is slightly lower than the personal vehicle cost per mile. Third, on the negative side, commuters need to wait a few minutes at their residence for the SAMS vehicle to pick them up for work.

In this study, the SAMS+Transit commute mode involves an inter-modal commute trip wherein the commuter takes a SAMS ride from home to a convenient transit station/stop before using the transit network to travel from this transit stop/station to her workplace. The SAMS+Transit mode does not require the commuter to pay for parking at the transit station. Additionally, the travel times for the SAMS portion of the trip are commensurate with personal vehicle travel. However, the SAMS portion of the trip does include a short wait time. Ideally, the SAMS+Transit mode would provide a cost-effective alternative to SAMS-only and personal vehicle travel while allowing commuters to utilize the transit network for longer distance commutes, overcoming the transit first-mile problem. In addition to connecting commuters to previously inaccessible (via walking) transit stations, the SAMS+Transit mode should also reduce the total travel time and number of transfers compared to a transit-only trip. This should be particularly beneficial in low-density areas where transit stations are not accessible by walking and also in cases where commuting with transit requires a significant number of inefficient transfers between bus and/or rail lines.

In summary, in this study the SAMS-only mode is commensurate with the personal vehicle mode except it eliminates parking costs, has lower per mile costs, and involves a pickup wait time. The SAMS portion of the SAMS+Transit commute option has the same characteristics. The study assumes AV/SAMS travel times remain the same as current personal vehicle travel. The study also assumes the disutility of in-vehicle travel time is the same in AVs/SAMS as current personal vehicle travel. Hence, the employment accessibility benefit results in this study are likely conservative compared to other studies that assume reduced travel times (Meyer et al., 2017) and in-vehicle travel time disutility (Vyas et al., 2019) with SAMS modes. Finally, the study assumes that the SAMS modes impact commute mode choice and work destination locations; however, it assumes worker residences and employment locations remain fixed.

This appears to be the first study to quantify the employment accessibility benefits of SAMS modes for an entire metropolitan region using a logsum- or welfare-based approach. While Childress et al. (2015) present logsum-based accessibility measures associated with the impact of AVs on accessibility, their study provides few methodological details and only one set of computational results. The current study presents and discusses the implications of a variety of employment accessibility results; the current study also presents a detailed methodology that involves clustering workers into classes based on their socio-demographics. In addition to improving destination choice model parameter estimates, clustering workers is especially valuable for evaluation purposes as analysts, planners, and policymakers can easily see the impact(s) of SAMS modes on different worker clusters. To illustrate the usefulness of the proposed methodology, this study generates a synthetic population of workers in the six-county Southern California Association of Governments (SCAG) region, then applies the LCA, mode choice, and destination choice model parameters, which were estimated on a sample of workers from the SCAG region, to quantify the employment accessibility benefits of SAMS modes for every member of the synthetic working population.

The remainder of the paper is structured as follows. The next section provides background information related to accessibility analysis and measures in general and in the context of AVs/SAMS modes. Section 3 presents the study’s conceptual framework and modeling assumptions while Section 4 describes the data and research methodology to quantify the employment accessibility benefits of SAMS modes. Section 5 presents and discusses a variety of computational results. The final section concludes the paper with a summary of the study and a discussion of limitations and future research.