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

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 humanoperated 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.

Performance Evaluation of Onboard Processing Capability Reduction in Cooperative Vehicles Using 5G and Artificial Intelligence

“…Tis precise information allows vehicles to have complete knowledge of their surroundings. For example, Cooperative Awareness Message (CAM) sends maneuver coordination information, while Maneuver Coordination Message (MCM) sends maneuvers between vehicles [36][37][38].…”

“…Te authors assume that an intelligent trafc management system (TMS) is deployed with a complete view of the environment. Using this information, they generate movement recommendations for vehicles without directly controlling them [40].…”