Courteous Behavior of Automated Vehicles at Unsignalized Intersections via Reinforcement Learning

TL;DR

This paper introduces a reinforcement learning-based method for automated vehicles to improve traffic flow at unsignalized intersections in mixed traffic, demonstrating significant efficiency gains over traditional traffic signal controls.

Contribution

The paper presents a novel reinforcement learning approach enabling automated vehicles to yield appropriately at unsignalized intersections, optimizing traffic flow in mixed traffic conditions.

Findings

Significantly improved traffic flow in simulations.

Outperforms traditional traffic signal controllers.

Effective in diverse traffic scenarios.

Abstract

The transition from today's mostly human-driven traffic to a purely automated one will be a gradual evolution, with the effect that we will likely experience mixed traffic in the near future. Connected and automated vehicles can benefit human-driven ones and the whole traffic system in different ways, for example by improving collision avoidance and reducing traffic waves. Many studies have been carried out to improve intersection management, a significant bottleneck in traffic, with intelligent traffic signals or exclusively automated vehicles. However, the problem of how to improve mixed traffic at unsignalized intersections has received less attention. In this paper, we propose a novel approach to optimizing traffic flow at intersections in mixed traffic situations using deep reinforcement learning. Our reinforcement learning agent learns a policy for a centralized controller to let connected autonomous vehicles at unsignalized intersections give up their right of way and yield to other vehicles to optimize traffic flow. We implemented our approach and tested it in the traffic simulator SUMO based on simulated and real traffic data. The experimental evaluation demonstrates that our method significantly improves traffic flow through unsignalized intersections in mixed traffic settings and also provides better performance on a wide range of traffic situations compared to the state-of-the-art traffic signal controller for the corresponding signalized intersection.