Publication Type
Journal Article
Version
acceptedVersion
Publication Date
3-2024
Abstract
Taxi drivers often take much time to navigate the streets to look for passengers, which leads to high vacancy rates and wasted resources. Empty taxi cruising remains a big concern for taxi companies. Analyzing the pick-up point selection behavior can solve this problem effectively, providing suggestions for taxi management and dispatch. Many studies have been devoted to analyzing and recommending hotspot regions of pick-up points, which can make it easier for drivers to pick-up passengers. However, the selection of pick-up points is complex and affected by multiple factors, such as convenience and traffic management. Most existing approaches cannot produce satisfactory results in real-world applications because of the changing travel demands and the lack of interpretability. In this paper, we introduce a visual analytics system, T-PickSeer, for taxi company analysts to better explore and understand the pick-up point selection behavior of passengers. We explore massive taxi GPS data and employ an overview-to-detail approach to enable effective analysis of pick-up point selection. Our system provides coordinated views to compare different regularities and characteristics in different regions. Also, our system assists in identifying potential pick-up points and checking the performance of each pick-up point. Three case studies based on a real-world dataset and interviews with experts have demonstrated the effectiveness of our system.
Keywords
Taxi travel behavior, pick-up point selection, visual analysis
Discipline
Numerical Analysis and Scientific Computing | Operations Research, Systems Engineering and Industrial Engineering | Transportation
Research Areas
Intelligent Systems and Optimization
Publication
Journal of Visualization
First Page
1
Last Page
18
ISSN
1343-8875
Identifier
10.1007/s12650-024-00968-0
Publisher
Springer
Citation
GU, Shuxian; DAI, Yemo; FENG, Zezheng; WANG, Yong; and ZENG, Haipeng.
T-PickSeer: Visual analysis of taxi pick-up point selection behavior. (2024). Journal of Visualization. 1-18.
Available at: https://ink.library.smu.edu.sg/sis_research/8706
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/s12650-024-00968-0
Included in
Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Transportation Commons