A Distributed Traffic Management System for End-to-End Dynamic Routing of Intelligent Vehicles

This webinar will discuss a proposed distributed dynamic routing system that can route the intelligent vehicles from origin to destination in dense urban areas, with the aim to optimize the network usage while minimizing the individual travel times. The proposed distributed control system generates and frequently updates a single integrated and coherent view of the network state, independent of market penetration rate and vehicle communication characteristics. The performance of the routing system is compared to a dynamic pre-trip shortest path routing in the downtown Toronto under recurrent and non-recurrent congestion conditions. Results show that the proposed routing system can reach near social optimal state, by having 56% higher throughput rate while reducing the average travel time by 40%. The proposed system manages the incidents better (15% lower travel time) and at the same time minimizes its effects on the network.