Analyzing detour behavior of metro passengers based on mobile phone data
Document Type
Journal Article
Publication Date
2022
Subject Area
mode - subway/metro, place - asia, place - urban, technology - passenger information, ridership - behaviour, ridership - modelling
Keywords
Path choice behaviormobile phone data, metro network, detour trips, distribution of passenger flow
Abstract
In this paper, a method of metro-passenger path extraction based on mobile phone data is presented. Paths that differ from theoretical optimal paths derived from the shortest-path model are identified as detours. According to transfer times or the effect on passenger flow of the metro network, two classification methods for detours are proposed. Based on analysis of one-month mobile phone data in Shanghai, China, 10.45% of trips are identified as detours. Without considering detours, the accuracy of the theoretical model in predicting passenger flow by segment is only 69.43%. Detours with as equal transfers as on theoretically optimal paths (ETs) occur mainly at the stations far away from the city center. Detours with more transfers (MTs) occur in the center city. Detours with fewer transfers (FTs) occur in stations on the loop line. To alleviate congestion on the metro network, FTs should be encouraged and others should be discouraged.
Rights
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Recommended Citation
Duan, Z., Liu, X., Yu, Q., & Li, Y. (2022). Analyzing detour behavior of metro passengers based on mobile phone data. Transportation Planning and Technology, Vol. 45(3), pp. 289-309.
