Multi-modal Travel Simulation and Travel Behavior Analysis: Case Study in Shanghai
This study aims to investigate the multi-modal travel behavior and obtain quantitative results for various indicators by building an eqasim/MATSim model, using Shanghai as the study area. Travel demand is mainly generated using mobile phone signaling data. For each mode, a travel cost model is formu...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2024-03-01
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| Series: | Journal of Highway and Transportation Research and Development |
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| Online Access: | https://www.sciopen.com/article/10.26599/HTRD.2024.9480003 |
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| author | Yue Hu Chao Yang Kay W Axhausen |
| author_facet | Yue Hu Chao Yang Kay W Axhausen |
| author_sort | Yue Hu |
| collection | DOAJ |
| description | This study aims to investigate the multi-modal travel behavior and obtain quantitative results for various indicators by building an eqasim/MATSim model, using Shanghai as the study area. Travel demand is mainly generated using mobile phone signaling data. For each mode, a travel cost model is formulated. Additionally, an MNL (Multinomial Logit) model is integrated into eqasim through the DMC (Discrete Mode Choice) module. The results demonstrate that using mobile phone signaling data to generate travel demand yields a high-quality representation of travel demand. Users prefer public transport over cars when travel distances are similar. Furthermore, for longer-distance travel, the combined bus and subway mode significantly reduces walking distance, travel time, and travel costs. The spatial accessibility of public transport strongly depends on the availability and coverage of the public transport infrastructure. In areas where public transport services are limited, cars can complement public transport by providing accessibility to areas with scarce public transport options. From a transportation system perspective, car trips during rush hours are similar to public transport and biking, while walking is consistently used throughout the day due to the shortest travel time. Home-based trips, particularly commuting trips, have the highest share. Understanding these travel patterns is essential for optimizing transportation planning and effectively addressing peak-hour travel demand. This study demonstrates the effectiveness of using mobile phone signaling data for studying multi-modal travel behavior. The results provide valuable insights for transportation planners and policymakers in developing efficient and sustainable transportation systems that meet the preferences and needs of travelers. |
| format | Article |
| id | doaj-art-c7c6c0fce2b44d95a2384cad12f52d0e |
| institution | DOAJ |
| issn | 2095-6215 |
| language | English |
| publishDate | 2024-03-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Journal of Highway and Transportation Research and Development |
| spelling | doaj-art-c7c6c0fce2b44d95a2384cad12f52d0e2025-08-20T02:56:51ZengTsinghua University PressJournal of Highway and Transportation Research and Development2095-62152024-03-01181172610.26599/HTRD.2024.9480003Multi-modal Travel Simulation and Travel Behavior Analysis: Case Study in ShanghaiYue Hu0Chao Yang1Kay W Axhausen2The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, ChinaThe Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, ChinaInstitute for Transport Planning and Systems, ETH Zurich, Zurich 8093, SwitzerlandThis study aims to investigate the multi-modal travel behavior and obtain quantitative results for various indicators by building an eqasim/MATSim model, using Shanghai as the study area. Travel demand is mainly generated using mobile phone signaling data. For each mode, a travel cost model is formulated. Additionally, an MNL (Multinomial Logit) model is integrated into eqasim through the DMC (Discrete Mode Choice) module. The results demonstrate that using mobile phone signaling data to generate travel demand yields a high-quality representation of travel demand. Users prefer public transport over cars when travel distances are similar. Furthermore, for longer-distance travel, the combined bus and subway mode significantly reduces walking distance, travel time, and travel costs. The spatial accessibility of public transport strongly depends on the availability and coverage of the public transport infrastructure. In areas where public transport services are limited, cars can complement public transport by providing accessibility to areas with scarce public transport options. From a transportation system perspective, car trips during rush hours are similar to public transport and biking, while walking is consistently used throughout the day due to the shortest travel time. Home-based trips, particularly commuting trips, have the highest share. Understanding these travel patterns is essential for optimizing transportation planning and effectively addressing peak-hour travel demand. This study demonstrates the effectiveness of using mobile phone signaling data for studying multi-modal travel behavior. The results provide valuable insights for transportation planners and policymakers in developing efficient and sustainable transportation systems that meet the preferences and needs of travelers.https://www.sciopen.com/article/10.26599/HTRD.2024.9480003traffic engineeringmulti-modal travelmobile phone signaling dataeqasim/matsim simulationmnl (multionmial logit) modeltravel behavior analysis |
| spellingShingle | Yue Hu Chao Yang Kay W Axhausen Multi-modal Travel Simulation and Travel Behavior Analysis: Case Study in Shanghai Journal of Highway and Transportation Research and Development traffic engineering multi-modal travel mobile phone signaling data eqasim/matsim simulation mnl (multionmial logit) model travel behavior analysis |
| title | Multi-modal Travel Simulation and Travel Behavior Analysis: Case Study in Shanghai |
| title_full | Multi-modal Travel Simulation and Travel Behavior Analysis: Case Study in Shanghai |
| title_fullStr | Multi-modal Travel Simulation and Travel Behavior Analysis: Case Study in Shanghai |
| title_full_unstemmed | Multi-modal Travel Simulation and Travel Behavior Analysis: Case Study in Shanghai |
| title_short | Multi-modal Travel Simulation and Travel Behavior Analysis: Case Study in Shanghai |
| title_sort | multi modal travel simulation and travel behavior analysis case study in shanghai |
| topic | traffic engineering multi-modal travel mobile phone signaling data eqasim/matsim simulation mnl (multionmial logit) model travel behavior analysis |
| url | https://www.sciopen.com/article/10.26599/HTRD.2024.9480003 |
| work_keys_str_mv | AT yuehu multimodaltravelsimulationandtravelbehavioranalysiscasestudyinshanghai AT chaoyang multimodaltravelsimulationandtravelbehavioranalysiscasestudyinshanghai AT kaywaxhausen multimodaltravelsimulationandtravelbehavioranalysiscasestudyinshanghai |