A Method to Estimate URT Passenger Spatial-Temporal Trajectory with Smart Card Data and Train Schedules

Taoyuan Yang, Peng Zhao and Xiangming Yao
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Taoyuan Yang: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Peng Zhao: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Xiangming Yao: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

Sustainability, 2020, vol. 12, issue 6, 1-13

Abstract: Precise estimation of passenger spatial-temporal trajectory is the basis for urban rail transit (URT) passenger flow assignment and ticket fare clearing. Inspired by the correlation between passenger tap-in/out time and train schedules, we present a method to estimate URT passenger spatial-temporal trajectory. First, we classify passengers into four types according to the number of their routes and transfers. Subsequently, based on the characteristic that passengers tap-out in batches at each station, the K-means algorithm is used to assign passengers to trains. Then, we acquire passenger access, egress, and transfer time distribution, which are used to give a probability estimation of passenger trajectories. Finally, in a multi-route case of the Beijing Subway, this method presents an estimation result with 91.2% of the passengers choosing the same route in two consecutive days, and the difference of route choice ratio in these two days is 3.8%. Our method has high accuracy and provides a new method for passenger microcosmic behavior research.

Keywords: urban rail transit; passenger; spatial-temporal trajectory; route choice; smart card data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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