Spatial-Temporal Correlation Prediction Modeling of Origin-Destination Passenger Flow Under Urban Rail Transit Emergency Conditions

Spatial-Temporal Correlation Prediction Modeling of Origin-Destination Passenger Flow Under Urban Rail Transit Emergency Conditions

Establishing a passenger flow prediction mechanism is necessary for quickly evacuating many passengers in an emergency, which can improve the service quality of urban rail transit (URT). To effectively forecast origin-destination (OD) passenger flows in URT under emergency conditions, 35-day automat...

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Bibliographic Details
Main Authors: Chen Li, Jianling Huang, Bo Wang, Yuyang Zhou, Yunyun Bai, Yanyan Chen
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Urban rail transit (URT) emergency
origin-destination (OD) passenger flow prediction
spatial-temporal correlation
nonlinear regression
automatic fare collection (AFC) data
Online Access:https://ieeexplore.ieee.org/document/8891689/

Internet

https://ieeexplore.ieee.org/document/8891689/

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