Planning and Dynamic Management of Autonomous Modular Mobility Services
Yanfeng Ouyang, George Krambles Endowed Professor in Rail and Public Transit – The University of Illinois at Urbana-Champaign
Paul F. Kent Endowed Faculty Scholar – The University of Illinois at Urbana-Champaign
Donald Biggar Willett Faculty Scholar – The University of Illinois at Urbana-Champaign
Director – Chinese-American Railway Transportation Joint Research Center
Associate Director for Mobility – Illinois Center for Transportation
As we enter the next era of autonomous driving, robo-vehicles (which serve as low-cost and fully compliant drivers) are being used to replace conventional chauffeured services in the mobility market. During just the last few years, companies like Waymo, inc. and Cruise, inc. have already offered fully driverless robo-taxi services to the general public in cities like Phoenix and San Francisco. The rapid evolution of autonomous vehicles is anticipated to reshape the shared mobility market very soon.
This project aims to address the following open questions.
- At the operational level, how should modular units be allocated across multiple categories of customers (e.g., passenger and freight cabins), and how should they be matched in real time? How to enhance system efficiency by dynamic relocation and swap of modular chassis?
- At the strategic or tactical level, how should the rolling stock resources (modular chassis, passenger and freight cabins) be planned, and where shall chassis swapping sites be located? How could any potential transaction cost for a chassis swap, such as the time required for a modular chassis to be assembled with a customized cabin, affect the optimal strategy and system performance?
- How can customer priorities (e.g., passenger vs. freight) affect system performance, and how can service providers manage demand by specific pricing scheme or discriminative customer service strategies?
We will conduct the following research tasks: (i) analytically derive systems of implicit nonlinear equations in the closed form, including a set of differential equations, to analyze the modular autonomous mobility system, and to estimate the expected system performance in the steady state; (ii) conduct a series of agent-based simulation experiments to verify the accuracy of the proposed analytical formulas and to demonstrate the effectiveness of the proposed modular chassis services; (iii) design policy instruments to enhance transportation system performance; (iv) prepare a research report that documents the findings from the project, data, analysis methodology, case study results, and implementation recommendations.
Institution(s): University of Illinois at Urbana-Champaign
Award Year: 2023
Research Focus: Mobility