Cooperative Schedule-Driven Intersection Control with Connected and Autonomous Vehicles

TL;DR

This paper introduces a cooperative traffic control algorithm that leverages connected and autonomous vehicles to optimize intersection scheduling, reducing delays and improving urban traffic flow.

Contribution

It presents a novel cooperative algorithm integrating CAVs with schedule-driven control to dynamically adjust vehicle platoon arrivals at intersections.

Findings

Algorithm reduces vehicle wait times compared to previous methods

Enhanced traffic flow efficiency demonstrated in real-time simulations

CAV communication enables proactive traffic management

Abstract

Recent work in decentralized, schedule-driven traffic control has demonstrated the ability to improve the efficiency of traffic flow in complex urban road networks. In this approach, a scheduling agent is associated with each intersection. Each agent senses the traffic approaching its intersection and in real-time constructs a schedule that minimizes the cumulative wait time of vehicles approaching the intersection over the current look-ahead horizon. In this paper, we propose a cooperative algorithm that utilizes both connected and autonomous vehicles (CAV) and schedule-driven traffic control to create better traffic flow in the city. The algorithm enables an intersection scheduling agent to adjust the arrival time of an approaching platoon through use of wireless communication to control the velocity of vehicles. The sequence of approaching platoons is thus shifted toward a new shape that has smaller cumulative delay. We demonstrate how this algorithm outperforms the original approach in a real-time traffic signal control problem.