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Forecasting the Peak-Period Station-to-Station Origin–Destination Matrix in Urban Rail Transit System: Case Study of Chongqing, China

Cheng, Y; Ye, X; Zhou, L; (2018) Forecasting the Peak-Period Station-to-Station Origin–Destination Matrix in Urban Rail Transit System: Case Study of Chongqing, China. In: Proceedings of the Transportation Research Board 97th Annual Meeting. National Academy of Sciences Green open access

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Abstract

The maximum one-direction section passenger flow within peak hour is an important indicator for planning and design of urban rail transit. To determine it, it is necessary to forecast passengers’ departure time and route choice during peak period. As the basis of this process, the peak-period station-to-station origin-destination (OD) matrix reflects the passengers’ travel needs. This paper tests traditional gravity models in forecasting the peak-period station-to-station origin and destination (OD) matrix in urban rail transit with a real-world case study of Chongqing, China. To solve its over-estimation when deterrence between two stations is too little, the gravity-model-based Peak Period Coefficient (PPC) model is introduced. Comparing results show that with the same dataset, the PPC model is superior to the gravity model. Its standard deviation is only 12.90 passengers, reduced by 56.02%.

Type: Proceedings paper
Title: Forecasting the Peak-Period Station-to-Station Origin–Destination Matrix in Urban Rail Transit System: Case Study of Chongqing, China
Event: Transportation Research Board 97th Annual Meeting
Location: Washington (DC), United States
Dates: 7th-11th January 2018
Open access status: An open access version is available from UCL Discovery
Publisher version: https://trid.trb.org/view/1495294
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Urban rail transit, Station-to-station ridership, Gravity model, Peak period coefficient, Deterrence function
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10064498
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