2013 Poster Sessions : Modelling and Experimental Analysis of Mobility-on-Demand Systems

Student Name : Rick Zhang
Advisor : Marco Pavone
Research Areas: Information Systems
Abstract:
The goal of our research is to enable a new paradigm of personal mobility through autonomous driving. As autonomous vehicles become more practical, the problem of optimally coordinating these vehicles to maximize throughput remains largely unexplored. Among the many challenges of coordinating autonomous vehicles, we have been studying the vehicle rebalancing problem in Mobility-on-Demand (MOD) systems. The goal is to develop optimal rebalancing policies that will ensure a satisfactory quality of service in the MOD system. We have developed an analysis technique based on Jackson networks to evaluate the performance of rebalancing policies as well as to optimize the rebalancing policy for a stationary MOD system. We also developed an experimental test-bed using a fleet of small mobile robots to simulate the behavior of a MOD system. The test-bed allows us to evaluate the performance of various rebalancing policies under real-world conditions such as traffic congestion.

Bio:
Rick Zhang received his BASc. degree in Engineering Science from the University of Toronto in 2011 and his M.S. degree in Aeronautics & Astronautics from Stanford University in 2013. He is currently pursuing a Ph.D. at the Autonomous Systems Lab in the department of Aeronautics & Astronautics. His research interests include decision and control in networked systems, autonomous vehicles, and robotics. His other interests include classical piano and rock climbing.