The Automated Mobility Policy (AMP) Project

Governing Autonomous Vehicles

Three independent forces are converging in the transportation field: sharing economy; electrification; and autonomous vehicles (AV)—together they promise to re-draw the transportation landscape as we know it. The trajectory along which they will evolve, however, remains largely uncertain. Through the Automated Mobility Policy (AMP) Project, JTL researchers bring together urban transportation planning, public policy, engineering, and behavioral science to analyze this revolution, by understanding how humans and policies interact with transportation technology: 1. Examining the formation processes of people’s preferences for autonomous vehicles; 2. Embedding shared AV services within the public transportation system, through the integration of information, price, operations, and institutions; and 3. Envisioning how municipal governments can devise AV policies to produce more equitable, sustainable, efficient, and livable cities. 

AV technology could revolutionize urban mobility—making travel cheaper and more accessible, and spurring the development of more vibrant, safer communities. These outcomes, however, are hardly guaranteed. Rather, they will require thoughtful regulatory policy to stimulate development in such a positive direction. We provide policymakers in Canada and the United States with the tools they need to design and implement just such effective, considered legislation. 

Approach

Based in the Massachusetts Institute of Technology (MIT) we approach autonomous vehicle development through an urbanist perspective and have five guiding principles:

  • AV development should accommodate the different needs, preferences, and abilities of a community’s diverse population. 
  • AV service should be available and accessible to all citizens, regardless of their income; where they live, work, and play; or the technology they own.
  • AVs should contribute to a reduction in transportation-sector greenhouse gas emissions. 
  • AV rollout should help eliminate fatal and serious traffic collisions. 
  • AV should be to make walking, biking, public transit, and sharing a ride more attractive. 

Our Policy Foundation

We have identified nine general policies to address the challenges of modern transportation systems, which are enhanced by the capabilities of autonomous technology. While these broad ideas must be refined for each local context, they form the backbone of our work.  

I. Altering the Cityscape

Limit parking provision: As the AV fleet grows, cities can reduce on-street and garage parking, decouple development projects from parking provision, and incentivize redevelopment of existing lots—to encourage commuters to choose alternative modes of travel.

Rethink the use of streetspace: By reducing road space for automobiles proportional to the decline in registered vehicles, cities can open up land for larger sidewalks and plazas, as well as dedicated transit and bike lanes—to make it more attractive to choose active and public transit. 

II. Ensuring Adequate Service

Centralize data collection and distribution: To strengthen and develop a holistic mobility system, cities can use existing technology (such as online trip planning applications and fare collection systems) to make multi-modal travel easier. 

Require minimum levels of service provision: By setting minimum levels of service provision, cities can ensure all citizens can get around within a reasonable amount of time, regardless of where they are going or coming from. 

Integrate for-hire autonomous vehicles and public transit: Enabling travellers to seamlessly transfer between public transit and for-hire services depending on travel time of day and location makes it more appealing to choose more efficient forms of transport. 

III. Harnessing Pricing

Enact distance-based road pricing: Charging users based on when and where they travel would encourage higher vehicle occupancy, particularly at peak times, and would discourage the circulation of empty autonomous vehicles on public streets.

Offer income-based subsidies: Travel is essential to citizen wellbeing, and cities can financially support those of lesser means to meet their travel needs. This assistance should not be a subsidy for AV services specifically, but for using a multi-modal network when getting around. 

IV. Limiting Externalities

Require zero-emission vehicles: Vehicles are to a great degree responsible for localized poor air quality, so limiting pollutants at the tail pipe cuts the environmental and health burdens imposed by a fossil fuel-based transportation system.

Limit empty-vehicle travel: Autonomous vehicles will have the ability to move by themselves, without passengers. In congested areas, this could add to traffic and slow travel times for people inside other vehicles. Cities can mitigate this impact by limiting empty-vehicle travel.   

 

AV Policy 

An Urban Agenda for Autonomous Vehicles: Embedding Planning Principles into Technological Deployment, Yonah Freemark, and Jinhua Zhao , Transportation Research Board 97th Annual Meeting, Washington, D.C., (2018)

The deployment of autonomous vehicles (AVs) has spawned a considerable literature on the role of national and state-level governments in regulating components of AV manufacturing, emissions, safety, licensing, and data sharing. These provide insight into how AVs can be integrated into the current transportation system. Yet the potential for local governments to shape their futures through AV policies is underexplored. This paper argues that it is both necessary and feasible for...

Driving AV Policy? A 300-City Survey of AV Policy Preparedness, Yonah Freemark, Anne Halvorsen, and Jinhua Zhao , (2018)

AVs could have significant consequences in terms of the level of vehicle travel on urban streets, the need for parking in neighborhoods, the ease of accessing employment, and the incidence of pollution. Addressing those issues is fundamental to achieving better planning, and cities could play an important role in orienting policies to ensure the best-possible outcomes. All around the world, cities hold the legal mechanisms to intervene in issues related to AVs, such as the design of streets...

Is There a Way? Is There Even a Will? Exploring the legal capacity, bureaucratic willingness and capacity, and political willingness and capacity of automated vehicle regulatory development in Toronto, Canada, Gillies, Benjamin, and Jinhua Zhao , Working paper, (2018)

Current research suggests there is a huge uncertainty as to whether automated vehicle development will engender a more equitable, efficient, and sustainable transportation network, or will exacerbate current trends of congestion, sprawl, and inequitable access to travel. Likely, the outcome will be determined by the policies governments adopt to guide development. Some of the most acute challenges of automated vehicle proliferation will be most acutely felt in areas under the purview of...

The Rules of the (Automated) Road: A Regulatory Proposal for Automated Ridehailing Operations in Toronto, Canada, and Government and Industry Feedback, Gillies, Benjamin, and Jinhua Zhao , Working paper, (2018)

A number of organizations have proposed general principles for AV development—such that it must be equitable, sustainable, and promote better city-building—but this research attempts to move further by offering concrete rules in municipal codes automated vehicle ridehailing companies must follow in order to operate in Toronto, Ontario. As the City of Toronto oversees rideshare company operations, they are legally able to adopt regulations that reflect their general planning principles....

 

AV Analytics

Transit-Oriented Autonomous Vehicle Operation with Integrated Demand-Supply Interaction, Jian Wen, Chen Leo, Nassir Neema, and Jinhua Zhao , Transportation Research Part C, (Submitted)

Autonomous vehicles (AVs) represent potentially disruptive and innovative changes to public transportation (PT) systems. However, the exact interplay between AV and PT is understudied in existing research. This paper proposes a systematic approach to the design, simulation, and evaluation of integrated autonomous vehicle and public transportation (AV+PT) systems. Two features distinguish this research from the state of the art literature: the first is the transit-oriented AV operation with...

Value of Demand Information in Autonomous Mobility-on-Demand Systems, Jian Wen, Nassir Neema, and Jinhua Zhao , Transportation Research Part A, (Submitted)

Effective management of demand information is a critical factor in successful operations of autonomous mobility-on-demand (AMoD) systems. However, the value of such information in operations is understudied in existing literature. This paper classifies, measures and evaluates the demand information in AMoD systems. First, the paper studies demand information at both individual and aggregate levels and measures two critical attributes of the demand information: dynamism and granularity. We...

Risk Preferences and Autonomous Vehicles, Shenhao Wang, and Jinhua Zhao , Transportation Research Part A, (Submitted)

While there is an increasingly large body of research on the potential demand for autonomous vehicles (AV), an understudied factor is people’s risk preference. Risk preference is important because many aspects of AVs are highly uncertain as the technology and its encompassing mobility system emerge and continue to evolve. This study analyzed how risk preferences influence the choice of AVs, and how risk preferences elicited by economic and psychometric methods differ in their impacts. We...

Integrating Shared Autonomous Vehicle in Public Transportation System: A Supply-Side Simulation of the First-Mile Service in Singapore, Yu Shen, Hongmou Zhang, and Jinhua Zhao , Transportation Research Part A, (2018)

This paper proposes and simulates an integrated autonomous vehicle (AV) and public transportation (PT) system. After discussing the attributes of and the interaction among the prospective stakeholders in the system, we identify opportunities for synergy between AVs and the PT system based on Singapore’s organizational structure and demand characteristics. Envisioning an integrated system in the context of the first-mile problem during morning peak hours, we propose to preserve high demand...

Rebalancing Shared Mobility-on-Demand Systems: a Reinforcement Learning Approach, Jian Wen, Jinhua Zhao, and Patrick Jaillet , IEEE ITSC Workshop on Intelligent Public Transport 2017, (2017)

 

Shared mobility-on-demand systems have very promising prospects in making urban transportation efficient and affordable. However, due to operational challenges among others, many mobility applications still remain niche products. This paper addresses rebalancing needs that are critical for effective fleet management in order to offset the inevitable imbalance of vehicle supply and travel demand. Specifically, we propose a reinforcement learning approach which adopts a deep Q network...

Simulating the First Mile Service to Access Train Stations by Shared Autonomous Vehicle, Yu Shen, Hongmou Zhang, and Jinhua Zhao , Transportation Research Board 96th Annual Meeting, (2017)

This paper studies the potential impacts of autonomous vehicle (AV) sharing with mobility-on demand service on the public transit system. We analyze the current travel demand in the public transit system in Singapore with a special focus on the first-/last-mile problem during morning peak hours. The first-/last-mile in this paper is defined as the gap between origin/destination and the heavy rail stations. A feasible method to integrate AV sharing in current transit system is proposed, which...

Value of Demand Information in Autonomous Mobility-on-Demand Systems, Jian Wen, Nassir Neema, and Jinhua Zhao , (2018)

Effective management of demand information is a critical factor in successful operations of autonomous mobility-on-demand (AMoD) systems. However, the value of such information in operations is understudied in existing literature. This paper classifies, measures and evaluates the demand information in AMoD systems. First, the paper studies demand information at both individual and aggregate levels and measures two critical attributes of the demand information: dynamism and granularity. We...

Dynamic Pricing in Shared Mobility on Demand Service and its Social Impacts, Han Qiu, Ruimin Li, and Jinhua Zhao , Working paper, (2017)

 

We consider a daily-level profit maximization of a shared mobility on-demand (MoD) service with request-level control, and possible government interventions to improve system efficiency. We use discrete choice models to describe traveler behavior, apply the assortment and price optimization framework to model the request-level dynamics, and leverage insights from dynamic programming to develop daily-level optimization problem. We solve this problem by designing parametric rollout...

TEAM MEMBERS

Banani Anuraj's picture
Research Engineer SMART
Yonah Freemark's picture
PhD Candidate
Jintai Li's picture
PhD Student
Zelin Li's picture
MST/MCP Student
Scott Middleton's picture
MST/MCP Student
Neema Nassir's picture
Senior Postdoctoral Associate
Yu Shen's picture
Assistant Professor at Tongji Univ.
Shenhao Wang's picture
PhD Student
Jian Wen's picture
MST Student
Hongmou Zhang's picture
PhD Candidate
Nate Bailey's picture
PhD Candidate
Leo Chen's picture
MST Student
Benjamin Gillies's picture
Research Fellow
Annie Hudson's picture
MCP Student
Jinhua Zhao's picture
Edward H. and Joyce Linde Associate Professor