Mining Factors Affecting Taxi Detour Behavior From GPS Traces at Directional Road Segment Level
In the urban traffic research field, taxi detour behavior analysis can be regarded as one of the most crucial and challenging topics accounting for real-world routing network dynamics with complicated external inducement such as “avoiding congestion sections”, “unfamiliarity with road maps” or just “earning more fee under a longer travel path”. The authors carried out an interdisciplinary research framework to build a more holistic and profound view of the spatio-temporal distribution of the taxi detour behavior at directional road segment (DRS) level. First, a map matching based detour clustering method was proposed to deal with one week of taxi GPS tracing (divided into 3.4 million occupied trips). Then the authors employed an established multi-layer road index system in Shenzhen, China, to illustrate the spatio-temporal distribution variation of taxi detour features and statistics. Furthermore, three categories of DRS factors related to road structural attributes, traffic dynamics and point-of-interests (POIs) were defined to fit a selected-sample-based binary logit model. Some remarkable findings include: (i) in Shenzhen on average, 23.5 percent of taxi trips made a detour larger than 2.1 kilometers, which could be astonishingly high considering that only a very few trips yielded formal complaints for fraudulent detouring; (ii) both the level of detour intensity and ratio are affected by road features and dynamics in different spatio-temporal interaction patterns.
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
-
Supplemental Notes:
- Copyright © 2022 Institute of Electrical and Electronics Engineers (IEEE).
-
Authors:
- Wu, Zhen
-
0000-0001-7254-2990
- Li, Ye
- Wang, Xiao
- Su, J
- Yang, L
- Nie, Y
- Wang, Yutong
- Publication Date: 2022-7
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 8013-8023
-
Serial:
- IEEE Transactions on Intelligent Transportation Systems
- Volume: 23
- Issue Number: 7
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 1524-9050
- Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979
Subject/Index Terms
- TRT Terms: Data mining; Detours; Taxi services; Traffic congestion; Traffic distribution
- Geographic Terms: Shenzhen (China)
- Subject Areas: Data and Information Technology; Passenger Transportation; Safety and Human Factors;
Filing Info
- Accession Number: 01856629
- Record Type: Publication
- Files: TRIS
- Created Date: Aug 29 2022 11:33AM