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Revealing spatiotemporal travel demand and community structure characteristics with taxi trip data: A case study of New York City
- Source :
- PLoS ONE, PLoS ONE, Vol 16, Iss 11 (2021), PLoS ONE, Vol 16, Iss 11, p e0259694 (2021)
- Publication Year :
- 2021
-
Abstract
- Urban traffic demand distribution is dynamic in both space and time. A thorough analysis of individuals’ travel patterns can effectively reflect the dynamics of a city. This study aims to develop an analytical framework to explore the spatiotemporal traffic demand and the characteristics of the community structure shaped by travel, which is analyzed empirically in New York City. It uses spatial statistics and graph-based approaches to quantify travel behaviors and generate previously unobtainable insights. Specifically, people primarily travel for commuting on weekdays and entertainment on weekends. On weekdays, people tend to arrive in the financial and commercial areas in the morning, and the functions of zones arrived in the evening are more diversified. While on weekends, people are more likely to arrive at parks and department stores during the daytime and theaters at night. These hotspots show positive spatial autocorrelation at a significance level of p = 0.001. In addition, the travel flow at different peak times form relatively stable community structures, we find interesting phenomena through the complex network theory: 1) Every community has a very small number of taxi zones (TZs) with a large number of passengers, and the weighted degree of TZs in the community follows power-law distribution; 2) As the importance of TZs increases, their interaction intensity within the community gradually increases, or increases and then decreases. In other words, the formation of a community is determined by the key TZs with numerous traffic demands, but these TZs may have limited connection with the community in which they are located. The proposed analytical framework and results provide practical insights for urban and transportation planning.
- Subjects :
- Computer and Information Sciences
Economics
Science
Distribution (economics)
Social Sciences
Transportation
Human Geography
Civil Engineering
Entertainment
Transport engineering
Urban Geography
Leisure Activities
Geoinformatics
Land Use
Spatial analysis
Community Structure
Geographic Areas
Transportation planning
Travel
Multidisciplinary
Ecology
Geography
business.industry
Ecology and Environmental Sciences
Community structure
Biology and Life Sciences
Outsourced Services
Complex network
Transportation Infrastructure
Spatial Autocorrelation
Roads
Community Ecology
Earth Sciences
Medicine
Human Mobility
Engineering and Technology
New York City
business
Automobiles
Finance
Research Article
Urban Areas
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 16
- Issue :
- 11
- Database :
- OpenAIRE
- Journal :
- PloS one
- Accession number :
- edsair.doi.dedup.....572b98b82a130751ad513da59369080d