Cooperative Maneuvers of Highly Automated Vehicles at Urban Intersections: A Game-theoretic Approach

TL;DR

This paper presents a game-theoretic approach for highly automated vehicles to perform cooperative maneuvers at urban intersections, aiming to enhance traffic efficiency and safety in mixed traffic environments.

Contribution

It introduces a decentralized control framework using game theory for cooperative maneuvers in urban intersections with mixed traffic, supported by a simulation-based prototype.

Findings

Promising results in traffic simulation demonstrate improved maneuver decision-making.

The approach effectively balances traffic flow efficiency and safety.

Decentralized control allows vehicles to make autonomous cooperative decisions.

Abstract

In this paper, we propose an approach how connected and highly automated vehicles can perform cooperative maneuvers such as lane changes and left-turns at urban intersections where they have to deal with human-operated vehicles and vulnerable road users such as cyclists and pedestrians in so-called mixed traffic. In order to support cooperative maneuvers the urban intersection is equipped with an intelligent controller which has access to different sensors along the intersection to detect and predict the behavior of the traffic participants involved. Since the intersection controller cannot directly control all road users and - not least due to the legal situation - driving decisions must always be made by the vehicle controller itself, we focus on a decentralized control paradigm. In this context, connected and highly automated vehicles use some carefully selected game theory concepts to make the best possible and clear decisions about cooperative maneuvers. The aim is to improve traffic efficiency while maintaining road safety at the same time. Our first results obtained with a prototypical implementation of the approach in a traffic simulation are promising.