Integrated Routing and Intersection Control for Mixed Traffic

TL;DR

This paper presents a hierarchical framework integrating macroscopic routing and microscopic intersection control for mixed traffic with CAVs, improving network throughput and reducing congestion.

Contribution

It introduces a novel hierarchical approach combining network-level routing with intersection-level control tailored for mixed traffic environments.

Findings

Significant improvement in network throughput compared to isolated control methods.

Reduction in intersection crossing delays and energy consumption.

Validated effectiveness on the Sioux Falls benchmark network.

Abstract

The rapid development of cyber-physical systems is driving a transition toward mixed traffic environments comprising both human-driven and connected and automated vehicles (CAVs). This shift presents a unique opportunity to leverage the efficient operation of CAVs to improve overall network throughput. This paper introduces a hierarchical framework designed to bridge macroscopic routing optimization at the network level with microscopic vicinity control at signalized intersections. The upper layer utilizes aggregated traffic information to provide proactive routing guidance for CAVs, aiming to minimize total travel time. The lower layer leverages local vehicle states to jointly optimize traffic light phases and individual CAV trajectories, aiming to reduce intersection crossing delays and optimize energy consumption, respectively. The effectiveness of the proposed framework is validated through SUMO on the Sioux Falls benchmark network. Results demonstrate that the integration of these macroscopic and microscopic layers yields significantly better performance compared to applying either layer in isolation, significantly improving network throughput and reducing congestion.