Streaming route assignment for connected autonomous vehicles (systems paper)

Abstract

In the coming era of connected autonomous vehicles, data-driven traffic optimization will reach its full potential. By collecting highly detailed real-time traffic data from sensors and vehicles, a traffic management system will have the full view of the entire road network, allowing it to plan traffic in a virtual world that replicates the real road network. This will bring significant innovations to transport-domain applications. We prototype a traffic management system that can perform traffic optimization with connected autonomous vehicles. We propose two route assignment algorithms that aim to reduce traffic delays by reducing intersecting routes. The proposed algorithms and two state-of-the-art route assignment algorithms are implemented in the prototype system. We evaluate the algorithms with both synthetic and real road networks. The experimental results show that the proposed algorithms outperform competitors in terms of the travel times of the routes.