Applying choice preference to passenger flow guidance for urban rail transit under emergencies

Ran Xu; Hongbing Xiao

doi:10.1117/12.3051052

20 January 2025 Applying choice preference to passenger flow guidance for urban rail transit under emergencies

Ran Xu, Hongbing Xiao

Author Affiliations +

Proceedings Volume 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024); 134220U (2025) https://doi.org/10.1117/12.3051052
Event: Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 2024, Xi'an, China

Abstract

Under emergencies, reasonably guiding passenger flow can improve the transportation efficiency and minimize the impact of the accident on urban traffic operation. First of all, based on the psychological theory and the relevant information such as the choice preference of passengers, the passengers are classified to get the sensitivity difference of different potential mode passengers on the scheme attributes, which provides data support for path selection modeling and optimization. Secondly, the model with time index is established by using the data of the train and the passengers, and the model with comfort index is constructed by using the cubic polynomial fitting method. According to the utility maximization problem theory, the objective function including time and comfort index is constructed to provide the optimal path for different types of passengers. Finally, a case study of partial rail transit lines in Beijing is presented. The results show that, in the case of emergency, by analyzing the behavior preference of passenger's path selection, the passengers can be classified, and a more suitable route can be provided for each type of passengers, which can improve the time utilization ratio, and passengers' perception of the train's comfort.

Citation Download Citation

Ran Xu and Hongbing Xiao "Applying choice preference to passenger flow guidance for urban rail transit under emergencies", Proc. SPIE 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 134220U (20 January 2025); https://doi.org/10.1117/12.3051052

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