Modeling and Control of Networked Autonomous Mobility Systems

The objective of this thesis is to integrate autonomous transportation with the current transportation system, including introducing autonomous vehicles into ground transportation and utilizing urban airspace. We study the ride-sharing networks with mixed autonomy where both autonomous vehicles (AVs) and human driven vehicles (HVs) are considered, and urban airspace mobility (UAM) management for urban air vehicles (UAVs). We first explore the transition from traditional ride-sharing networks to totally automated mobility-on-demand systems, where the platform sets prices for riders, compensations for drivers of HVs, and operates AVs for a fixed price with the goal of maximizing profits. Next, in UAM networks, takeoff and landing sites, called vertiports, typically have limited landing capacity. For safety, it must be guaranteed that an air vehicle will be able to land before it can be allowed to take off. We present a model for the UAM network that accounts for uncertain travel times and limited landing capacity at vertiports. We explore the problem of scheduling UAM flights and then investigate the safety verification problem for given UAM schedules in the network with disruption, where we consider the intermittent closures of the vertiports. We develop theoretical constraints and an efficient algorithm that, given a proposed UAM schedule, verifies whether all UAVs are able to safely reach a back-up landing site in the event of a vertiport closure without violating the limited landing capacity of each vertiport in the network.Ph.D