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

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...

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Bibliographic Details
Published inSustainability Vol. 12; no. 6; p. 2574
Main Authors Yang, Taoyuan, Zhao, Peng, Yao, Xiangming
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 24.03.2020
Subjects
Behavior
Datasets
Egress
Expected utility
Methods
Passengers
Researchers
Route choice
Route selection
Schedules
Security management
Smart cards
Statistical analysis
Sustainability
Trajectory analysis
Travel
Urban rail
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Summary: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.
ISSN:2071-1050
2071-1050
DOI:10.3390/su12062574