Issue |
E3S Web Conf.
Volume 372, 2023
2023 4th International Conference on Urban Engineering and Management Science (ICUEMS2023)
|
|
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Article Number | 01012 | |
Number of page(s) | 5 | |
Section | Urban Planning Management and Ecological Construction | |
DOI | https://doi.org/10.1051/e3sconf/202337201012 | |
Published online | 06 March 2023 |
Optimization design of real-time scheduling scheme for city bus vehicles based on BP neural network
1
School of Transportation Engineering, East China Jiaotong University, Nanchang, Jiangxi, China, Department of Road Traffic Management, Sichuan Police College, Luzhou, Sichuan, China, Intelligent Policing Key Laboratory of Sichuan Province, Luzhou, Sichuan, China
2
School of Transportation Engineering, East China Jiaotong University, Nanchang, Jiangxi, China
3
Department of Road Traffic Management, Sichuan Police College, Luzhou, Sichuan, China, Intelligent Policing Key Laboratory of Sichuan Province, Luzhou, Sichuan, China
* 2022139082300003@ecjtu.edu.cn
a 17360445752@163.com
b 2371207413@qq.com
c 947714851@qq.com
Urban public transportation is inseparably related to people’s travel and life. Prioritizing the development of public transportation is a major national policy proposed by the Chinese government, especially to actively promote the development of intelligent public transportation systems. Developing and building advanced intelligent public transport operation and scheduling management system, designing efficient, flexible and low-cost operation and scheduling mode, improving the management level and service quality of public transport enterprises, and thus improving the road traffic condition of the whole city, is undoubtedly the future development direction of public transport enterprises. This paper combines the problems of bus operation and scheduling in China at the present stage, and proposes the operation and scheduling model and method of the intelligent urban public transportation planning system, with a view to realizing a flexible public transportation operation model suitable for different service situations and providing systematic theoretical support for solving the imbalance between supply and demand of public transportation.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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