eprintid: 10064498
rev_number: 25
eprint_status: archive
userid: 608
dir: disk0/10/06/44/98
datestamp: 2018-12-19 11:13:03
lastmod: 2021-09-30 22:39:34
status_changed: 2018-12-19 11:13:03
type: proceedings_section
metadata_visibility: show
creators_name: Cheng, Y
creators_name: Ye, X
creators_name: Zhou, L
title: Forecasting the Peak-Period Station-to-Station Origin–Destination Matrix in Urban Rail Transit System: Case Study of Chongqing, China
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F44
keywords: Urban rail transit, Station-to-station ridership, Gravity model, Peak period coefficient, Deterrence function
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
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%.
date: 2018-01-08
date_type: published
publisher: National Academy of Sciences
official_url: https://trid.trb.org/view/1495294
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1614086
language_elements: English
lyricists_name: Cheng, Yan
lyricists_id: CYANX81
actors_name: Cheng, Yan
actors_id: CYANX81
actors_role: owner
full_text_status: public
publication: Transportation Research Board 97th Annual Meeting
event_title: Transportation Research Board 97th Annual Meeting
event_location: Washington (DC), United States
event_dates: 7th-11th January 2018
institution: Transportation Research Board 97th Annual Meeting
book_title: Proceedings of the Transportation Research Board 97th Annual Meeting
citation:        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   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10064498/1/Cheng_Forecasting%20the%20Peak-Period%20Station-to-Station%20Origin%E2%80%93Destination%20Matrix%20in%20Urban%20Rail%20Transit%20System.%20Case%20Study%20of%20Chongqing%2C%20China_AAM.pdf