Shared Autonomous Fleet Services and Multimodal Urban Mobility: Optimization, Prediction and Dynamic Network Modeling

Hani Mahmassani
Northwestern University

Transportation is undergoing deep and significant transformation, seeking to fulfill the promise of connected mobility for people and goods, while limiting its carbon footprint. Autonomous vehicles are potentially changing the economics ownership and use of private automobiles, likely accelerating trends towards greater use of app-based ride hailing and/or sharing by private TNCs (Transportation Network Companies). Several potential business models with varying degrees of ride sharing and public vs. private involvement in the delivery of mobility as a service are presented. Algorithms for shared autonomous fleet management and autonomous car sharing are discussed and illustrated on a small case application. These are then integrated in an intermodal dynamic network modeling framework, which incorporates an agent-based microsimulation of a transit urban network system with shared-ride autonomous vehicles (SAV) as first-mile feeders. The integrated mode choice and dynamic traveler assignment-simulation modeling framework is applied to the Chicago region to evaluate the mobility impact of new services.