Understanding taxi travel patterns

Taxis play important roles in modern urban transportation systems, especially in mega cities. While providing necessary amenities, taxis also significantly contribute to traffic congestion, urban energy consumption, and air pollution. Understanding the travel patterns of taxis is thus important for...

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Main Authors: Cai, Hua, Zhan, Xiaowei, Zhu, Ji, Jia, Xiaoping, Chiu, Anthony S.F., Xu, Ming
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Published: Animo Repository 2016
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/3462
https://animorepository.dlsu.edu.ph/context/faculty_research/article/4464/type/native/viewcontent/j.physa.2016.03.047
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-44642021-09-09T02:44:33Z Understanding taxi travel patterns Cai, Hua Zhan, Xiaowei Zhu, Ji Jia, Xiaoping Chiu, Anthony S.F. Xu, Ming Taxis play important roles in modern urban transportation systems, especially in mega cities. While providing necessary amenities, taxis also significantly contribute to traffic congestion, urban energy consumption, and air pollution. Understanding the travel patterns of taxis is thus important for addressing many urban sustainability challenges. Previous research has primarily focused on examining the statistical properties of passenger trips, which include only taxi trips occupied with passengers. However, unoccupied trips are also important for urban sustainability issues because they represent potential opportunities to improve the efficiency of the transportation system. Therefore, we need to understand the travel patterns of taxis as an integrated system, instead of focusing only on the occupied trips. In this study we examine GPS trajectory data of 11,880 taxis in Beijing, China for a period of three weeks. Our results show that taxi travel patterns share similar traits with travel patterns of individuals but also exhibit differences. Trip displacement distribution of taxi travels is statistically greater than the exponential distribution and smaller than the truncated power-law distribution. The distribution of short trips (less than 30 miles) can be best fitted with power-law while long trips follow exponential decay. We use radius of gyration to characterize individual taxi's travel distance and find that it does not follow a truncated power-law as observed in previous studies. Spatial and temporal regularities exist in taxi travels. However, with increasing spatial coverage, taxi trips can exhibit dual high probability density centers. © 2016 Elsevier B.V. All rights reserved. 2016-09-01T07:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/3462 info:doi/10.1016/j.physa.2016.03.047 https://animorepository.dlsu.edu.ph/context/faculty_research/article/4464/type/native/viewcontent/j.physa.2016.03.047 Faculty Research Work Animo Repository Taxicabs--China--Beijing Commuters--China--Beijing Operations Research, Systems Engineering and Industrial Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Taxicabs--China--Beijing
Commuters--China--Beijing
Operations Research, Systems Engineering and Industrial Engineering
spellingShingle Taxicabs--China--Beijing
Commuters--China--Beijing
Operations Research, Systems Engineering and Industrial Engineering
Cai, Hua
Zhan, Xiaowei
Zhu, Ji
Jia, Xiaoping
Chiu, Anthony S.F.
Xu, Ming
Understanding taxi travel patterns
description Taxis play important roles in modern urban transportation systems, especially in mega cities. While providing necessary amenities, taxis also significantly contribute to traffic congestion, urban energy consumption, and air pollution. Understanding the travel patterns of taxis is thus important for addressing many urban sustainability challenges. Previous research has primarily focused on examining the statistical properties of passenger trips, which include only taxi trips occupied with passengers. However, unoccupied trips are also important for urban sustainability issues because they represent potential opportunities to improve the efficiency of the transportation system. Therefore, we need to understand the travel patterns of taxis as an integrated system, instead of focusing only on the occupied trips. In this study we examine GPS trajectory data of 11,880 taxis in Beijing, China for a period of three weeks. Our results show that taxi travel patterns share similar traits with travel patterns of individuals but also exhibit differences. Trip displacement distribution of taxi travels is statistically greater than the exponential distribution and smaller than the truncated power-law distribution. The distribution of short trips (less than 30 miles) can be best fitted with power-law while long trips follow exponential decay. We use radius of gyration to characterize individual taxi's travel distance and find that it does not follow a truncated power-law as observed in previous studies. Spatial and temporal regularities exist in taxi travels. However, with increasing spatial coverage, taxi trips can exhibit dual high probability density centers. © 2016 Elsevier B.V. All rights reserved.
format text
author Cai, Hua
Zhan, Xiaowei
Zhu, Ji
Jia, Xiaoping
Chiu, Anthony S.F.
Xu, Ming
author_facet Cai, Hua
Zhan, Xiaowei
Zhu, Ji
Jia, Xiaoping
Chiu, Anthony S.F.
Xu, Ming
author_sort Cai, Hua
title Understanding taxi travel patterns
title_short Understanding taxi travel patterns
title_full Understanding taxi travel patterns
title_fullStr Understanding taxi travel patterns
title_full_unstemmed Understanding taxi travel patterns
title_sort understanding taxi travel patterns
publisher Animo Repository
publishDate 2016
url https://animorepository.dlsu.edu.ph/faculty_research/3462
https://animorepository.dlsu.edu.ph/context/faculty_research/article/4464/type/native/viewcontent/j.physa.2016.03.047
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