Abstract
Advancements in artificial intelligence and Internet of Things indicates the realization of commercial autonomous vehicles is almost ready. With autonomous vehicles comes new approaches in solving some of the current traffic problems such as fuel consumption, congestion, and high incident rates. Autonomous Intersection Management (AIM) is an example that utilizes the unique attributes of autonomous vehicles to improve the efficiency of a single intersection. However, in a system of interconnected intersections, just by improving individual intersections does not guarantee a system optimum. Therefore, we extend from a single intersection to a grid of intersections and propose a novel vehicle routing method for autonomous vehicles that can effectively reduce the travel time of each vehicle. With dedicated short range communications and the fine-grained control of autonomous vehicles, we are able to apply wire routing algorithms with modified constraints to vehicle routing. Our method intelligently avoids congestions by simulating the future traffic and thereby achieving a system optimum.