Framework, model and algorithm for the global control of urban automated driving traffic

Abstract

Automated driving has recently attracted significant attention. While considerable research has been conducted on the technologies and societal acceptance of autonomous vehicles, investigations into the control and scheduling of urban automated driving traffic are still nascent. As automated driving gains traction, urban traffic control logic is poised for substantial transformation. Presently, both manual and automated driving predominantly operate under a local decision-making traffic mode, where driving decisions are based on the vehicle’s status and immediate environment. This mode, however, does not fully exploit the potential benefits of automated driving, particularly in optimizing road network resources and traffic efficiency. In response to the increasing adoption of automated driving, it is essential for traffic bureaus to initiate proactive dialogs regarding urban traffic control from a global perspective. This paper introduces a novel global control mode for urban automated driving traffic. Its core concept involves the central scheduling of all autonomous vehicles within the road network through vehicle-infrastructure cooperation, thereby optimizing traffic flow. This paper elucidates the mechanism and process of the global control mode. Given the operational complexity of expansive road networks, the paper suggests segmenting these networks into multiple manageable regions. This mode is conceptualized as an autonomous vehicle global scheduling problem, for which a mathematical model is formulated and a modified A-star algorithm is developed. The experimental findings reveal that (i) the algorithm consistently delivers high-quality solutions promptly and (ii) the global scheduling mode significantly reduces traffic congestion and equitably distributes resources. In conclusion, this paper presents a viable and efficacious new control mode that could substantially enhance urban automated traffic efficiency.

Graphical abstract

Keywords

automated driving / urban traffic control / global scheduling mode / autonomous vehicle route planning / A-star algorithm

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