In this talk, I will give an overview of ongoing research in autonomy and real-time distributed control techniques for future urban mobility.
The main focus will be on Mobility on Demand services that leverage recent technological advances in vehicle autonomy, and algorithmic advances in Dynamic Vehicle Routing problem. Consider a finite group of shared vehicles, located at a set of stations. Users arrive at the stations, pick up vehicles, and drive (or are driven) to their destination station where they drop off the vehicle. When some origins and destinations are more popular than others, the system will inevitably become out of balance: Vehicles will build up at some stations, and become depleted at others. We consider a number of solutions to this problem, relying on human "rebalancers," or robotic vehicles autonomously driving between stations. Control policies and performance bounds are developed and discussed, building also on recent advances in Dynamic Pick-up and Delivery Problems. The second part of the seminar will focus on distributed algorithms for adaptive traffic light scheduling. The proposed scheduling algorithms are provably maximally stabilizing, adaptive to traffic conditions, and significantly outperform state-of-the art systems in high-fidelity simulations.