Convergence of Sharing and Automation: Need for Proactive Public Policy and Research Understanding

By Susan Shaheen and Adam Cohen

In recent years, on-demand passenger and courier services – known as Mobility on Demand (MOD) – have grown rapidly due to technology advancements; changing consumer patterns (both mobility and retail consumption); and a combination of economic, environmental, and social forces. MOD is an innovative concept based on the principle that transportation is a commodity where modes have economic values that are distinguishable in terms of cost, journey time, wait time, number of connections, convenience, and other attributes. Earlier this month, we wrote about innovations in goods delivery that are transforming transportation and consumer behavior as travelers increasingly turn to MOD. In this blog, we discuss four potential impacts of driverless vehicles and the need for proactive public policy to maximize the potential benefits and minimize potential adverse impacts.

Potential Impacts of Vehicle Automation

In the near future, automation could be the most transformative change transportation has seen since the advent of the automobile. While MOD is already impacting many cities, it has the potential to have even more notable impacts, particularly in four key areas:

Travel Behavior: It should be emphasized that the impacts of automation on travel behavior are uncertain and difficult to forecast due to a number of highly variable factors, most importantly societal acceptance and use. One potential outcome is that existing roadway capacity may increase due to more efficient operations associated with technology (e.g., closer vehicle spacing known as platooning, etc.). Additionally, operators could “right-size fleets,” providing consumers with vehicles sized based on the number of passengers and trip length. However, there is a possibility that automated vehicles (AVs) and shared AVs (SAVs) could induce demand by making motorized travel more convenient and affordable than personal driving. This could adversely impact congestion. Additionally, automation has the potential to fundamentally change historic relationships between public transportation and private vehicle use, which could support or detract from public transit ridership (we will discuss the future of public transportation in our next blog). In summary, the impacts of AVs on congestion will likely depend on whether the vehicles are predominantly shared or privately owned as well as public policy, such as pricing and restrictions on zero occupant vehicles.

Land Use and the Built Environment: AVs could result in reduced parking demand, particularly in urban centers that can create opportunities to repurpose urban parking with infill development. Infill development has the potential to increase urban densities and could in turn support higher-occupancy transportation modes. However, vehicle automation and telecommuting growth could also make longer commutes less burdensome, which could encourage suburban and exurban lifestyles.

Labor: Automation has the potential to reduce labor costs. However, automation is not likely to completely eliminate transportation jobs. With an aging population, we may likely need attendants to assist people with disabilities and older adults, security personnel, and a high-tech workforce to maintain an automated fleet.

Social Equity: While AVs have the potential to enhance access and economic opportunities for underserved communities, there are numerous challenges that could impact the equitable deployment of AVs. A few challenges could include: 1) affordability/payability (the services are simply too expensive for low-income households or require banking access); 2) availability (the services are not available equally in all neighborhoods); 3) accessibility (the services are not accessible to people with disabilities); and 4) digital poverty (the services require a smartphone or data plan to access). Additionally, AVs may employ machine learning and artificial intelligence that could create other equity concerns. While machine learning – if designed well — can help minimize human bias in decision making, it is also possible that such systems can also reinforce historic bias and discrimination in the transportation network. Just as humans learn to drive through experience, many perception algorithms use machine learning that is trained by events based on past experience. In a driverless vehicle future, machine learning may also impact where vehicles are pre-positioned, roam, charge, and other defining operational characteristics. Learning biases could create notable equity challenges in the future. There is a risk for discrimination when designing transportation algorithms for machine learning systems, including the potential for exclusionary transportation.

Need for Proactive Policy in a Driverless Vehicle Future

Public policy can have a notable influence on the success or potential challenges of driverless vehicles. Public agencies should consider proactively guiding public policy in four key areas to maximize the potential benefits of AVs:

Pricing: Public agencies should consider employing pricing based on occupancy, time of day, and congestion to encourage higher occupancy SAVs and discourage single- and zero-occupant vehicles.

Incentivizing Urban Growth and Urban Growth Boundaries: Metropolitan Planning Organizations, local governments, and other public agencies may want to consider policies that limit outward growth and encourage urban in-fill development to discourage the potential suburban and exurban growth pressure that AVs could create.

Workforce Development Programs: Local and state governments should develop workforce development programs designed to prepare for and respond to a driverless future. This should include a broad program encompassing job training/re-training and job placement resources to minimize the potential adverse labor impacts of vehicle automation.

A Comprehensive Equity Policy: Public agencies at all levels of government should consider a comprehensive equity policy to ensure SAVs are equally accessible and available to everyone. This should include policies that ensure access for people with disabilities, un- and under-banked households, low-income communities, households without access to smartphones or mobile data, and others. Additionally, this should include policies that prevent discrimination and bias from machine learning, artificial intelligence, and other systems that impact or guide the operations of AVs.

The public and private sectors, along with key stakeholders (e.g., non-governmental organizations, community-based organizations, and foundations) should partner to develop proactive policies to prevent and overcome these challenges. Proactive policy and research understanding will be critical to balance public goals with commercial interests and to harness and maximize the social and environmental effects of driverless vehicles.

Susan Shaheen and Adam Cohen are currently studying the impacts of connected and automated vehicles on state and local transportation agencies as part of the National Cooperative Highway Research Program (NCHRP) study 20-102(11).

Please note that this article expresses the opinions of the author and does not reflect the views of Move Forward.

 

Prioritizing People, Public Transport, and Pooling: Transitioning to Shared Automated Vehicles

Technology is reshaping cities and societies and changing the way we travel. Real-time information coupled with on-demand mobility are redefining ‘auto mobility.’ Rather than rendering cars obsolete, the convergence of on-demand shared, electric, and automated technology will make the autos more cost effective, efficient, and convenient – especially when shared. But the convergence of sharing, electrification, and automation in itself is not a silver bullet to solve our transportation challenges. To maximize the potential opportunity and minimize the challenges associated with shared automated vehicles (SAVs), we should consider 5 key issues in managing the transition toward an automated future.

 

1. Equity Challenges and Opportunities – Earlier this year, we wrote about common equity challenges impacting our transportation network. Suburbanization has been one of the great underlying trends impacting transportation in the Western hemisphere during the 20th century. While early suburbs were often built around railroad and streetcar lines, post–World War II suburbanization has become primarily an auto-driven phenomenon. In many cities, our urban centers declined as development patterns focused on mass personal vehicle ownership; the marketing of suburbia as a residential location; and the building of highways that manifested in strip malls, suburban retail and employment centers, and very low-density housing. This development pattern has resulted in an overreliance on private vehicles that has come at a high cost to household budgets, public health, and the environment. It is not uncommon for low-income households to spend upwards of 30% of their income on transportation. For those without a private vehicle, limited access to jobs, education, and health care can be a barrier to upward mobility.

 

A shared, electric, and automated mobility future has the opportunity to enhance access and mobility for underserved communities, but it could also exacerbate existing barriers and increase inequality. SAVs may be able to address spatial inequality in areas with limited alternatives to private vehicle ownership by providing additional mobility options for an entire trip or first- and last-mile connections to public transportation. The strategic placement of SAVs in communities underserved by public transportation could reduce inequities by providing innovative mobility options that have greater coverage and service availability than existing options. However, not all users may have access to a smartphone or debit/credit cards that are commonly required for payment as part of app-based and on-demand mobility services. In the future, it will be critical that policymakers ensure equitable access of SAVs for all neighborhoods and users with special needs, including access options for digitally impoverished and underbanked communities.

 

2. Environmental and Travel Behavior Impacts of Automation – While SAV impacts remain uncertain, many practitioners and researchers predict higher efficiency, affordability, and lower greenhouse gas emissions. However, the number of personally owned automated vehicles may determine to some extent SAV demand. More importantly, SAV impacts will also depend on sharing levels (concurrent or sequential) and the future modal split among public transit, SAVs, and pooled rides. It is possible that SAV fleets could become widely used without very many pooled rides. Thus, single-occupant vehicles will continue to dominate the majority of vehicle trips (e.g., users could access a shared fleet without pooling). It is also feasible that pooled rides could become more common, if automation makes route deviation more efficient, cost effective, and convenient. While the environmental and travel behavior impacts of SAVs are unknown, proactive public policy is key to guiding how SAV adoption unfolds.

 

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3. Urban Planning (Rights-of-Way Management and Zoning) – With the growth of on-demand and flexible transportation options (e.g., ridesourcing or transportation network companies, e-Hail, microtransit, etc.), public agencies should consider policies to guide shared mobility and SAV development through the allocation of public rights-of-ways (e.g., parking, curb space, and loading zones). The allocation of public rights-of-way for shared mobility today can support the development of intermodal mobility hubs today, which can be transitioned for SAVs in the future.

 

In the longer term, automation will likely result in fundamental changes to our built environment. Reduced vehicle ownership due to SAVs could impact parking needs, particularly in urban centers. The repurposing of urban parking has the potential to create some opportunities for infill development and increased densities. While SAVs may compete with public transit, infill development could create higher densities to support more public transit ridership in urban core locations.

 

4. Public Transportation in an Automated Future – Concerns that the introduction of SAVs could reduce demand for public transportation and may encourage increased vehicle use are real. However, just as SAVs have the potential to reduce driving costs, automated transit vehicles have the opportunity to reduce operational costs and pass these savings onto riders through lower fares. Reduced operational costs and lower fares could allow public transit agencies to increase the number of routes or service frequency, making public transit more competitive than other modes. While the impacts of automation on public transportation are uncertain, leveraging it to reduce overhead costs and improve public transportation efficiency is an important consideration.

 

In addition, vehicle automation could further change the nature of traditional notions of public and private transportation services. In the future, public transit agencies may opt to provide more flexible demand-responsive service in smaller vehicles, while others may opt to pursue such systems through partnerships. The emergence of SAVs could give rise to the development of hybrid quasi-public-private transportation systems that could result in a range of partnerships that vary by region.

 

5. Occupancy Pricing – Underpriced and overcrowded roadways create a “tragedy of the commons” where individual users acting independently and rationally, according to their own self-interest, behave contrary to the common good of maximizing road efficiency. In the future, single-occupant SAVs could continue to dominate the majority of vehicle trips, if users access SAVs without pooling. To minimize the risk associated with this scenario, policymakers should consider pricing policies that adjust prices based on vehicle occupancies. Public agencies may be able to improve roadway performance by providing discounts for pooling and varying prices by the time-of-day, roadway demand, and congestion.

 

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SAVs will not inherently solve today’s transportation challenges. To solve these challenges, AVs require prudent planning and public policies that balance societal goals with commercial interests. To harness and maximize the social and environmental benefits of highly automated vehicles, we need to prepare for the transition today. This includes focusing on social inequities (the digital and income divide), public transit declines, land use barriers, and pricing strategies.

 

Susan Shaheen and Adam Cohen recently co-authored the article “Is It Time for a Public Transit Renaissance? Navigating Travel Behavior, Technology, and Business Model Shifts in a Brave New World” and the U.S. Department of Transportation Mobility on Demand Operational Concept.

Please note that this article expresses the opinions of the author and does not reflect the views of Move Forward.