Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Uncovering Taxi Mobility Patterns Associated with the Public Transportation Shutdown Using Multisource Data in Washington, D.C.
https://orcid.org/http://orcid.org/0000-0002-2595-0139
https://orcid.org/http://orcid.org/0000-0003-2220-4859
The relationship between taxi travel patterns and public transportation disruption has not been extensively explored. In this study, we investigated the impact of public transportation disruption on the taxi mobility patterns during the metro shutdown in Washington, D.C.. Multiple data source, involving taxi trips, traffic analysis zone, and point of interest (POI) information, was collected to compare the taxi travel patterns before, during, and after the metro shutdown. The number, distance, and duration of taxi trips were found to be significantly higher during the metro shutdown; specifically, the number of taxi trips was found to be 19.8% larger. Furthermore, a POI auxiliary analysis was performed to investigate the variation in community structure during the disruption of public transport using the modularity maximization approach. The results of this study will be useful for the development of taxi scheduling strategies and traffic management.
Uncovering Taxi Mobility Patterns Associated with the Public Transportation Shutdown Using Multisource Data in Washington, D.C.
https://orcid.org/http://orcid.org/0000-0002-2595-0139
https://orcid.org/http://orcid.org/0000-0003-2220-4859
The relationship between taxi travel patterns and public transportation disruption has not been extensively explored. In this study, we investigated the impact of public transportation disruption on the taxi mobility patterns during the metro shutdown in Washington, D.C.. Multiple data source, involving taxi trips, traffic analysis zone, and point of interest (POI) information, was collected to compare the taxi travel patterns before, during, and after the metro shutdown. The number, distance, and duration of taxi trips were found to be significantly higher during the metro shutdown; specifically, the number of taxi trips was found to be 19.8% larger. Furthermore, a POI auxiliary analysis was performed to investigate the variation in community structure during the disruption of public transport using the modularity maximization approach. The results of this study will be useful for the development of taxi scheduling strategies and traffic management.
Uncovering Taxi Mobility Patterns Associated with the Public Transportation Shutdown Using Multisource Data in Washington, D.C.
https://orcid.org/http://orcid.org/0000-0002-2595-0139
https://orcid.org/http://orcid.org/0000-0003-2220-4859
The relationship between taxi travel patterns and public transportation disruption has not been extensively explored. In this study, we investigated the impact of public transportation disruption on the taxi mobility patterns during the metro shutdown in Washington, D.C.. Multiple data source, involving taxi trips, traffic analysis zone, and point of interest (POI) information, was collected to compare the taxi travel patterns before, during, and after the metro shutdown. The number, distance, and duration of taxi trips were found to be significantly higher during the metro shutdown; specifically, the number of taxi trips was found to be 19.8% larger. Furthermore, a POI auxiliary analysis was performed to investigate the variation in community structure during the disruption of public transport using the modularity maximization approach. The results of this study will be useful for the development of taxi scheduling strategies and traffic management.
Uncovering Taxi Mobility Patterns Associated with the Public Transportation Shutdown Using Multisource Data in Washington, D.C.
KSCE J Civ Eng
Jia, Jianmin (Autor:in) / Zhang, Hui (Autor:in) / Shi, Baiying (Autor:in)
KSCE Journal of Civil Engineering ; 26 ; 5291-5300
01.12.2022
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Inferring trip purposes and uncovering travel patterns from taxi trajectory data
| Online Contents | 2016
| DOAJ | 2022