Governing Autonomous Vehicles

Three independent forces are converging in the transportation field: on-demand service; shared economy; and autonomous vehicles (AV)—together they promise to re-draw the transportation landscape as we know it. However, along what trajectory they will evolve remains largely uncertain. JTL brings the behavioral perspective to bear on this revolution through the lens of how humans interact with transportation technology. We focus on three areas of inquiry: 1. examining the formation process of people’s preference for autonomous vehicles, and monitoring the emotional and physiological responses during the AV ride; 2. embedding the shared AV service within the public transportation system, including information, price, operation and institution integration; and 3. envisioning how municipal governments can devise AV policies to produce more equitable, sustainable, efficient, and livable cities.       

Integrating Shared Autonomous Vehicle in Public Transportation System, Yu Shen, Hongmou Zhang, and Jinhua Zhao , Transportation Research Part A, (Submitted)

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

An Urban Agenda for Autonomous Vehicles: Embedding Planning Principles into Technological Deployment, Yonah Freemark, and Jinhua Zhao , Working paper, (2017)

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...

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, (Submitted)

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 and...

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...

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...

Team Members

Banani Anuraj's picture
Research Engineer SMART
Yonah Freemark's picture
PhD Candidate
Zelin Li's picture
MST/MCP Student
Neema Nassir's picture
Senior Postdoctoral Associate
Yu Shen's picture
Postdoc Associate (SMART FM)
Shenhao Wang's picture
PhD Student
Jian Wen's picture
MST Student
Hongmou Zhang's picture
PhD Student
Nate Bailey's picture
PhD Candidate
Leo Chen's picture
MST Student
Benjamin Gillies's picture
MCP Student