Automatic Vehicles' Trajectories Optimization on Highway Exclusive Lanes. (29th June 2022)

• Record Type: Journal Article
• Authors: Chen, Lingjuan; Ruan, Yangbo; Gou, Yiquan
• Other Names: Lambert Alain Academic Editor.
• Is Part Of: Journal of advanced transportation. Volume 2022(2022)
• Publication Date: 2022-06-29
• Subjects: Transportation -- Periodicals; 388.05
• DOI: 10.1155/2022/3582355
• Languages: English
• ISSNs: 0197-6729

Abstract

Abstract : The rapid development of V2X communication has made it possible to optimize and control the trajectories of vehicles from the whole traffic flow's perspective and improve traffic performance. Therefore, this paper discusses the trajectories management problem on highway facilitated with lanes exclusively for autonomous vehicles (AVs). The paper proposes a model that aims to search for optimal trajectories and minimize total travel time for AVs with multiple initial and target states while averting crashes and conforming to vehicles' kinetic. Dividing the time zone into discrete pieces, the model is analyzed as a large-scale discrete problem influenced by the randomness of the sequence of vehicles. A two-phase algorithm combined with upper evolution strategies and lower dynamic programming is developed to diminish stochastics and reduce computation step by step and solve the trajectories optimization model. Numerical experiments validate that the proposed method is capable of generating optimal trajectories for multiple AVs and approaching to system optimum by simultaneously solving all the spatial and temporal values of the trajectories. The two-phase algorithm can be applied efficiently in practice to obtain a feasible approximate solution for trajectories optimization by presetting appropriate algorithm parameters.