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Open AccessArticle

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

School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
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Sustainability 2020, 12(6), 2574; https://doi.org/10.3390/su12062574
Received: 18 February 2020 / Revised: 16 March 2020 / Accepted: 18 March 2020 / Published: 24 March 2020
(This article belongs to the Special Issue Sustainable Rail and Metro Systems)
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. View Full-Text
Keywords: urban rail transit; passenger; spatial-temporal trajectory; route choice; smart card data urban rail transit; passenger; spatial-temporal trajectory; route choice; smart card data
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Yang, T.; Zhao, P.; Yao, X. A Method to Estimate URT Passenger Spatial-Temporal Trajectory with Smart Card Data and Train Schedules. Sustainability 2020, 12, 2574.

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