Collection Auctions-Based Autonomous Intersection Management

• Published in: Machines (Basel) Vol. 11; no. 5; p. 573
• Main Authors: Li, Jinjian, Yin, Biao, Fang, Yong
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.05.2023; MDPI
• Subjects: Algorithms; Auctions; Autonomous vehicles; Communication; Computational linguistics; Computer Science; Computing time; Control algorithms; Control centres; Control systems; Driverless cars; Efficiency; Engineering Sciences; Infrastructure; Intelligence; Language; language intelligence; Language processing; Natural language interfaces; Natural language processing; Operations Research; optimization; Other; personal preference; social credit; Traffic assignment; Traffic congestion; Traffic control; Traffic delay; Traffic flow; Traffic information; Traffic intersections; Traffic management; traffic management system; Vehicle-to-infrastructure; Vehicles; social credit; language intelligence; personal preference; optimization; traffic management system
• ISSN: 2075-1702; 2075-1702
• DOI: 10.3390/machines11050573

The traffic management system holds immense importance due to its significant impact on human living standards. With the advent of advanced technologies such as natural language processing and autonomous vehicles, this study proposes a novel cooperative traffic management system based on collection auctions at an isolated unsignalized intersection, taking into account the users’ preferences for passing the intersection while being subject to their social credits. Once vehicles enter the vehicle-to-infrastructure communication zone, drivers provide the intersection control center with their bidding information, which reflects their urgency for right-of-way. According to the traffic and biding information, the vehicles’ passing sequence is optimized by the control center, in order to maximize the drivers’ average satisfaction. To demonstrate the effectiveness of the proposed system, a series of simulation experiments were conducted under varying traffic volumes. The simulation results were then compared with several other traffic control systems from the literature. It was shown that the proposed algorithm demonstrates superior performance in terms of computational time, traffic delay, and drivers’ personal satisfaction.