Issue |
E3S Web Conf.
Volume 213, 2020
2nd International Conference on Applied Chemistry and Industrial Catalysis (ACIC 2020)
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Article Number | 03026 | |
Number of page(s) | 5 | |
Section | Environmental Chemical Research and Energy-saving Technology Application | |
DOI | https://doi.org/10.1051/e3sconf/202021303026 | |
Published online | 01 December 2020 |
Research on passenger flow forecast of Urban Rail Transit
Department of Transportation, CUCD, Beijing, 100088, China
Urban rail transit has the characteristics of large traffic volume, fast and convenient, so it has become the urban passenger transport mode which is given priority in the planning and design of each city. The prediction and analysis of rail transit passenger flow is a very important part in the planning and design stage. And it also provides important basic data for urban rail planning, construction and operation. When the rail transit network needs to be adjusted, the passenger flow forecast is also an essential step. In this paper, Taking Dongguan urban rail transit line 2 as an example, based on the full consideration of the uniqueness of Dongguan urban rail transit and the prediction of various social and economic indicators of Dongguan City, the “four step method” is adopted to forecast passenger flow. Through the investigation of resident’s travel survey, we can master the current travel distribution of all modes. Based on the analysis of land use change, traffic development policy and related influencing factors of Dongguan City, the trip distribution of each characteristic year is predicted. Then, the OD matrix of public transport (including subway and conventional public transport) is obtained through the study of traffic mode division model, and the predicted rail passenger flow is obtained through the allocation model of cooperation and competition. In the stage of passenger flow assignment, the influence of various factors on travel route selection is comprehensively considered in the public transport allocation model. Finally, the prediction index and sensitivity of rail passenger flow are analyzed.
© The Authors, published by EDP Sciences, 2020
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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