Visual Analysis of Travel Behavior for Urban Rail Transit

Analyzing travel behavior of inhabitant can provide guidance and suggestions for urban traffic management and planning, land use planning, etc. In this paper, we designed a system to analyze the travel behavior of inhabitant using the smart card data of urban rail transit from two aspects, spatial visualization analysis and temporal visualization analysis. In spatial visualization analysis, we first conducted spatial and temporal aggregation for the whole city's smart card data. Then, we designed a spatial chord glyph to display the aggregated data. In temporal visualization analysis, we first proposed an algorithm to determine the degree and direction of cross-regional flow. Then, we study the degree of stability based on the algorithm. We conducted experiments based on urban rail transit in Beijing, the results show that our system can provide appropriate advice and support for urban traffic management and planning as well as land use planning.

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Publication Details

Published
2024-09-23
DOI
https://doi.org/10.1109/mass62177.2024.00087
Primary Topic
Human-Automation Interaction and Safety
Type
article
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article

Visual Analysis of Travel Behavior for Urban Rail Transit

Zhi Cai, Kexin Li, Hai-Ming Liu
Human-Automation Interaction and Safety
article

Visual Analysis of Travel Behavior for Urban Rail Transit

Zhi Cai, Kexin Li, Hai-Ming Liu
article en

Abstract

Analyzing travel behavior of inhabitant can provide guidance and suggestions for urban traffic management and planning, land use planning, etc. In this paper, we designed a system to analyze the travel behavior of inhabitant using the smart card data of urban rail transit from two aspects, spatial visualization analysis and temporal visualization analysis. In spatial visualization analysis, we first conducted spatial and temporal aggregation for the whole city's smart card data. Then, we designed a spatial chord glyph to display the aggregated data. In temporal visualization analysis, we first proposed an algorithm to determine the degree and direction of cross-regional flow. Then, we study the degree of stability based on the algorithm. We conducted experiments based on urban rail transit in Beijing, the results show that our system can provide appropriate advice and support for urban traffic management and planning as well as land use planning.

Beijing Jiaotong University (CN), Beijing University of Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 76%
Human-Automation Interaction and Safety
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