Consumers are purchasing and using partially automated vehicles, yet little research has been conducted to understand how and if these vehicles are changing travel behavior. Fully automated, or driverless, vehicles are receiving much more research and policy attention but are still many years from market introduction. Research on fully automated vehicles has shown that, without proper policies in place, these vehicles could increase vehicle miles travelled (VMT). Tesla vehicle models with the ‘Autopilot’ feature are some of the most common partially automated vehicles on the road today. A partially automated vehicle provides advanced driver assistance by controlling steering, acceleration/ deceleration, and braking; however, the human driver is still considered to be in control of the vehicle and is expected to be attentive. A previous UC Davis study found that Tesla vehicle owners with the Autopilot feature drove more than those without Autopilot, but the study did not determine whether higher VMT was caused by Autopilot. To better understand whether Autopilot influences how much individuals drive, the UC Davis research team interviewed 36 Tesla Autopilot users to evaluate whether they experienced changes to their travel, and the reasons for any reported changes. Key findings from the interviews are presented in this brief.

Related Publications

published journal article

Investigating the decision to travel more in a partially automated electric vehicle

research report

Travel Behavior Changes Among Users of Partially Automated Vehicles

policy brief

E-commerce is Reshaping the Warehousing Landscape – and it May Impact Disadvantaged Communities

Publication Date

May 1, 2020

Associated Project(s)

E-commerce, Warehousing and Distribution Facilities in California: A Dynamic Landscape and the Impacts on Disadvantaged Communities

Author(s)

Miguel Jaller, Xiaodong Quan, Xiuli Zhang

Areas of Expertise

Freight, Logistics, & Supply Chain

View policy brief

Abstract

Prior to the last decade, the logistics industry trended towards the development of mega-warehouse facilities in suburban settings far from core markets, creating a phenomenon known as logistics sprawl. This trend is particularly prominent in Southern California (Figure 1). Since the 2008-2009 economic crisis, however, the trend has shifted. The rise of e-commerce may have influenced supply chain decisions to locate warehouses and distribution centers closer to denser urban areas to enable faster deliveries to consumers. The changes in size and spatial distribution of warehouses and distribution centers as well as the environmental and equity implications of these changes are not fully understood. As warehouses and distribution centers locate in denser urban areas, they may introduce additional diesel truck traffic into disadvantaged and low-income communities.To gain a better understanding of how the spatial distribution and size of freight facilities are changing and the implications of these changes for disadvantaged and low-income communities, researchers at the University of California, Davis analyzed aggregate data about the number of warehouses and distribution centers and disaggregate real estate data of purchases and leases during the last three decades in California. They also analyzed the relationship between freight facilities and communities of concern using the California Environmental Protection Agency’s CalEnviroScreen 3.0 tool. The research focused on the San Diego, Los Angeles, San Francisco, San Joaquin Valley, and Sacramento regions. Key findings from the research are presented in this brief.

Related Publications

research report

E-commerce, Warehousing and Distribution Facilities in California: A Dynamic Landscape and the Impacts on Disadvantaged Communities

policy brief

Shared Autonomous Mobility Services Show Promise for Increasing Access to Employment in Southern California

Publication Date

May 1, 2020

Associated Project(s)

Assessment of the Employment Accessibility Benefits of Shared Autonomous Mobility Services

Author(s)

Arash Ghaffar, Michael Hyland, Navjyoth Sarma , Suman Mitra, Tanjeeb Ahmed

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data Safety, Public Health, & Mobility Justice

View policy brief

Abstract

Workers in Southern California currently face transportation related challenges accessing employment opportunities, including but not limited to high parking costs and/or limited parking availability in dense employment and residential areas; long commute distances between residential areas and employment opportunities; and poor transit service quality in many areas. These challenges are particularly burdensome for low-income households that may not have access to a personal vehicle and/or live in job-poor neighborhoods, as having a personal vehicle may be the only viable way to get to work.

Related Publications

published journal article

Quantifying the Employment Accessibility Benefits of Shared Automated Vehicle Mobility Services: Consumer Welfare Approach Using Logsums

research report

Assessment of the Employment Accessibility Benefits of Shared Autonomous Mobility Services

research report

Assessment of the Employment Accessibility Benefits of Shared Autonomous Mobility Services

Publication Date

May 1, 2020

Associated Project(s)

Assessment of the Employment Accessibility Benefits of Shared Autonomous Mobility Services

Author(s)

Arash Ghaffar, Michael Hyland, Navjyoth Sarma , Suman Mitra, Tanjeeb Ahmed

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data Safety, Public Health, & Mobility Justice

View research report

Abstract

The goal of this study is to assess and quantify the potential employment accessibility benefits of Shared Autonomous Mobility Service (SAMS) commute modes across a large diverse metropolitan region considering heterogeneity in the working population. To meet this goal, this study employs a welfare-based (i.e. log sum-based) measure of accessibility, obtained via estimating a hierarchical work destination-commute mode choice model. The employment accessibility log sum measure incorporates the spatial distribution of worker residences and employment opportunities, the attributes of the available commute modes, and the characteristics of individual workers. This research further captures the heterogeneity of workers using latent class analysis (LCA). The latent class analysis model inputs include the socio-demographic characteristics of workers to subsequently account for different worker clusters valuing different types of employment opportunities differently. The accessibility analysis results 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.

Related Publications

published journal article

Quantifying the Employment Accessibility Benefits of Shared Automated Vehicle Mobility Services: Consumer Welfare Approach Using Logsums

policy brief

Shared Autonomous Mobility Services Show Promise for Increasing Access to Employment in Southern California

research report

Travel Behavior Changes Among Users of Partially Automated Vehicles

Publication Date

May 1, 2020

Associated Project(s)

Travel Behavior Changes Among Users of Partially Automated Vehicles

Author(s)

Scott Hardman

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data Travel Behavior, Land Use, & the Built Environment

View research report

Abstract

Partially automated battery electric vehicles (BEVs) are being sold to and used by consumers. Estimates indicate that as of the end of 2019, there were over 700,000 Partially Automated Tesla Vehicles—the subject of this study—on the roads globally. Despite this, little research has been done to understand how they may be changing travel behavior. In this study, qualitative interviews with 36 users of Tesla battery electric vehicles with Autopilot were conducted. The goal of this was to understand how Autopilot is used, user experiences of the system, and whether the system has any impact on drivers’ travel behavior. The focus of the last of these aims was to determine whether Autopilot could cause or was causing an increase in vehicle miles traveled (VMT) among the study participants. Results from the interviews showed that partial automation leads to consumers traveling by car more and being more willing to drive in congested traffic. These changes are due to increased comfort, reduced stress, and increased relaxation due to the partial automation system, and because of the lower running costs of a BEV. The results also point to a need for further research of partially automated vehicles that are already on the market, as 11 of 17 reasons for increased vehicle miles traveled that have been identified in modeling studies of fully automated vehicles (not yet commercially available) applied to users of Autopilot.

Related Publications

published journal article

Investigating the decision to travel more in a partially automated electric vehicle

policy brief

Drivers of Partially Automated Vehicles are Making More Trips and Traveling Longer Distances

research report

Learning to Collaborate: Lessons Learned from Governance Processes Addressing the Impacts of Sea Level Rise on Transportation Corridors Across California

Publication Date

May 1, 2020

Associated Project(s)

Learning to Collaborate: Lessons Learned from Governance Processes Addressing the Impacts of Sea Level Rise on Transportation Corridors Across California

Author(s)

Francesca Pia Vantaggiato, Mark Lubell

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience

View research report

Abstract

This study was designed to identify lessons learned from experiences of multi-stakeholder collaboration in governance processes focused on adaptation to sea level rise for specific transportation corridors/assets across different areas of California. Four transportation assets in California were selected as case studies: State Route 37 in the Bay Area; the Cardiff Beach Living Shorelines Project and the LOSSAN railroad at Del Mar in San Diego County; and the Port of Long Beach in Los Angeles County. The study methods included attendance of policy meetings; document analysis; and interviews of staff at (local, regional, and state) government bodies, transportation agencies, climate collaboratives, etc. The study identified three major governance challenges shared among these cases: (1) stakeholder involvement or collaboration with ‘unusual’ partners; (2) jurisdictional fragmentation; and (3) lack of funding. The lessons learned to address these challenges were: (a) include a wide range of stakeholders early on in the project; (b) identify an intermediary or facilitator with relevant knowledge and social capital with the stakeholders; (c) establish a forum for negotiations and information exchange; (d) draft a memorandum of understanding with the rules of collaboration; (e) appoint a project manager to tie all the project parts and stakeholders together and sustain engagement; (f) structure the collaboration in tiers from technical/operational to executive/political; (g) explore options to make any given project a multi-benefit project; (h) advocate for a multi-year stream of funding rather than a lump sum; (i) leverage collaboration for funding and highlight, to potential funders, the collaborative element as a means to increase the efficiency of their investment. Issues to consider when deriving lessons from other jurisdictions were: differences in capacity, or available resources and staff; the numbers of actors involved; pre-existing positive collaborative relationships between the actors; exposure of transportation assets to sea-level rise; existing vulnerabilities of the corridor/asset; and the economic relevance of the corridor/asset.