13th Asia Pacific Transportation Development Conference
Research on Short-Term Passenger Flow Forecast of Urban Rail Transit
Publication: Resilience and Sustainable Transportation Systems
ABSTRACT
With the continuous expansion of the subway network, timely and accurate short-term passenger flow prediction is of great significance to improve the operation efficiency of the station. From the perspective of historical passenger flow data, wavelet analysis is used to remove the noise of related unconventional fluctuations. Combined with the theory of time series prediction, a suitable model is selected for passenger flow prediction after denoising. Through the example verification, the combined model after wavelet decomposition and reconstruction has high prediction accuracy, which provides the possibility for the practical promotion of short-term passenger flow prediction.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
Bai, L. (2017). “Study on normal and abnormal short-term passenger flow prediction methods of urban rail transit.” Transportation system engineering and information, 17(01), 127-135.
Guo, H Y (2011) “Research on passenger flow prediction of Guangzhou Shenzhen railway”. Journal of Xihua University, 30(02), 5-7
Wang, B., Zhan, M. H., and Lu, F. (2012). “The impact of the opening of new urban rail transit lines on the operation of existing lines.” Urban rapid rail transit, 25(06), 60-64.
Xie, D. Y., Zhao, S. P., and Wang, H. Y. (2019) “Forecasting analysis of Chongqing rail transit passenger flow based on seasonal index”. Smart city, 5(15), 158-159
Yao, E. J., Zhou, W. H., and Zhang, Y.S. (2018). “Prediction of real-time passenger flow in and out of new urban rail transit stations at the initial stage of opening.” China Railway Science, 39(02), 119-127.
Yuan, J., and Wang, P. (2017). “Prediction method of urban rail transit passenger flow based on space-time characteristics.” Journal of Beijing Jiaotong University, 41(06), 42-48.
Zou, W., Lu, B.C., and Deng, J. (2014). “Research on passenger flow prediction based on genetic algorithm and wavelet neural network” Journal of Wuhan University of Technology 38(05), 1148-1151 + 1157
Information & Authors
Information
Published In
Resilience and Sustainable Transportation Systems
Pages: 346 - 352
Editors: Fengxiang Qiao, Ph.D., Texas Southern University, Yong Bai, Ph.D., Marquette University, Pei-Sung Lin, Ph.D., University of South Florida, Steven I Jy Chien, Ph.D., New Jersey Institute of Technology, Yongping Zhang, Ph.D., California State Polytechnic University, and Lin Zhu, Ph.D., Shanghai University of Engineering Science
ISBN (Online): 978-0-7844-8290-2
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Jun 29, 2020
Published in print: Jun 29, 2020
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.