A Hierarchical Passenger Mobility Prediction Model Applicable to Large Crowding Events
Predicting individual mobility of subway passengers in large crowding events is crucial for subway safety management and crowd control. However, most previous models focused on individual mobility prediction under ordinary conditions. Here, we develop a passenger mobility prediction model, which is...
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Format: | Article |
Language: | English |
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Wiley
2022-01-01
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Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2022/7096153 |
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author | Bao Guo Hu Yang Fan Zhang Pu Wang |
author_facet | Bao Guo Hu Yang Fan Zhang Pu Wang |
author_sort | Bao Guo |
collection | DOAJ |
description | Predicting individual mobility of subway passengers in large crowding events is crucial for subway safety management and crowd control. However, most previous models focused on individual mobility prediction under ordinary conditions. Here, we develop a passenger mobility prediction model, which is also applicable to large crowding events. The developed model includes the trip-making prediction part and the trip attribute prediction part. For trip-making prediction, we develop a regularized logistic regression model that employs the proposed individual and cumulative mobility features, the number of potential trips, and the trip generation index. For trip attribute prediction, we develop an n-gram model incorporating a new feature, the trip attraction index, for each cluster of subway passengers. The incorporation of the three new features and the clustering of passengers considerably improves the accuracy of passenger mobility prediction, especially in large crowding events. |
format | Article |
id | doaj-art-5229c5f5657c468a83796a36010b3288 |
institution | Kabale University |
issn | 2042-3195 |
language | English |
publishDate | 2022-01-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Advanced Transportation |
spelling | doaj-art-5229c5f5657c468a83796a36010b32882025-02-03T01:06:50ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/7096153A Hierarchical Passenger Mobility Prediction Model Applicable to Large Crowding EventsBao Guo0Hu Yang1Fan Zhang2Pu Wang3School of Traffic and Transportation EngineeringSchool of Traffic and Transportation EngineeringShenzhen Institutes of Advanced TechnologySchool of Traffic and Transportation EngineeringPredicting individual mobility of subway passengers in large crowding events is crucial for subway safety management and crowd control. However, most previous models focused on individual mobility prediction under ordinary conditions. Here, we develop a passenger mobility prediction model, which is also applicable to large crowding events. The developed model includes the trip-making prediction part and the trip attribute prediction part. For trip-making prediction, we develop a regularized logistic regression model that employs the proposed individual and cumulative mobility features, the number of potential trips, and the trip generation index. For trip attribute prediction, we develop an n-gram model incorporating a new feature, the trip attraction index, for each cluster of subway passengers. The incorporation of the three new features and the clustering of passengers considerably improves the accuracy of passenger mobility prediction, especially in large crowding events.http://dx.doi.org/10.1155/2022/7096153 |
spellingShingle | Bao Guo Hu Yang Fan Zhang Pu Wang A Hierarchical Passenger Mobility Prediction Model Applicable to Large Crowding Events Journal of Advanced Transportation |
title | A Hierarchical Passenger Mobility Prediction Model Applicable to Large Crowding Events |
title_full | A Hierarchical Passenger Mobility Prediction Model Applicable to Large Crowding Events |
title_fullStr | A Hierarchical Passenger Mobility Prediction Model Applicable to Large Crowding Events |
title_full_unstemmed | A Hierarchical Passenger Mobility Prediction Model Applicable to Large Crowding Events |
title_short | A Hierarchical Passenger Mobility Prediction Model Applicable to Large Crowding Events |
title_sort | hierarchical passenger mobility prediction model applicable to large crowding events |
url | http://dx.doi.org/10.1155/2022/7096153 |
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