A Multi-Level Speed Guidance Cooperative Approach Based on Bidirectional Periodic Green Wave Coordination Under Intelligent and Connected Environment
Luxi Dong, Xiaolan Xie, Lieping Zhang, Shuiwang Li, Zhiqian Yang
TL;DR
This paper introduces a new traffic control method that uses speed guidance and green wave coordination to reduce delays and improve intersection efficiency in smart cities.
Contribution
A novel bi-level combinatorial optimization method combining deep Q learning and genetic algorithms for green wave coordination.
Findings
The proposed method reduces average delay by 20.76% compared to conventional strategies.
It also decreases the number of stops by 44.49% in coordinated intersections.
The method improves green light time utilization in intelligent and connected environments.
Abstract
To maximize arterial green wave bandwidth utilization, this study aims to minimize average travel delays at coordinated intersections and maximize vehicle throughput. In view of the aforementioned points, the present paper sets out a collaborative optimization method for the control of related intersection groups. The method combines multi-level speed guidance with green wave coordinated control. In an intelligent and connected environment (ICE), the driving trajectory of the initial vehicle is determined in each optimization cycle following the receipt of active speed guidance. Subsequently, the driving trajectories of subsequent vehicles are calculated, with an assessment made as to whether they can leave the intersection before the end of the green light. The subsequent step involves the calculation of a characteristic index, comprising the average speed of the arterial coordination…
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Taxonomy
TopicsTraffic control and management · Transportation Planning and Optimization · Traffic and Road Safety