Intelligent Bus Scheduling Control Based on On-Board Bus Controller and Simulated Annealing Genetic Algorithm

Electronics

Haina Song¹  Xiaosong Liu²  Jinchao Xiao³  Jingfeng Yang³  Zhiguo Dong⁴  Jiehan Yu⁴  Zhendong Xie⁴  Honggang Wang⁵  Jiayi Su⁶ 

[1] Department of School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China;Guangdong Zhongke Zhenheng Information Technology Co., Ltd., Foshan 528225, China;Guangzhou Institute of Industrial Intelligence, Guangzhou 511458, China;Guangzhou Public Transport Group Co., Ltd., Guangzhou 510110, China;School of Communications and Information Engineering & School of Artificial Intelligence, Xi’an University of Posts and Telecommunications, Xi’an 710199, China;School of Humanities and Social Sciences, Beihang University, Beijing 100191, China;

关键词: bus network;    on-board controller;    intelligent scheduling;    edge computing;    simulated annealing genetic algorithm;   

DOI  :  10.3390/electronics11101520

来源: DOAJ

【 摘 要 】

The stable and fast service of a bus network is one of the important indicators of the service quality and management level of urban public transport. With the continuous expansion of cities, the bus network complexity has been increasing accordingly. The application of new technologies such as self-driving buses has made the bus network more complex and its vulnerability more obvious. Therefore, how to collect information on passenger flow, traffic flow, and transport distribution using intelligent means, and how to establish an effective intelligent bus scheduling control method have been important questions surrounding the improvement of the level of urban bus operation. To address this challenge, this paper proposes the design method of a bus controller based on data collection and the edge computing requirements of autonomous driving buses; and installs them widely on buses. In addition, an intelligent bus control scheduling method based on the simulated annealing genetic algorithm was developed according to the current scheduling requirements. The proposed method combines the strong local search ability of the simulated annealing algorithm, which prevents the search process from falling into a local optimum, and the strong search ability of the genetic algorithm in the overall search process, leading an intelligent bus control scheduling method based on the simulated annealing genetic algorithm. The proposed method was verified by experiments on the optimal scheduling of multi-destination public transport as an example, we verified the research method, and finally, simulated it using historical data. There is good model prediction of the experimental results. Therefore, the intelligent traffic control can be realized through efficient bus scheduling, thus improving the robustness of the bus network operation.

【 授权许可】

Unknown