Affiliation:
1. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China
Abstract
This study utilizes taxi trajectory data to uncover urban residents’ travel patterns, offering critical insights into the spatial and temporal dynamics of urban mobility. A fusion clustering algorithm is introduced, enhancing the clustering accuracy of trajectory data. This approach integrates the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm, modified to incorporate time factors, with kernel density analysis. The fusion algorithm demonstrates a higher noise point detection rate (15.85%) compared with the DBSCAN algorithm alone (7.31%), thus significantly reducing noise impact in kernel density analysis. Spatial correlation analysis between hotspot areas and paths uncovers distinct travel behaviors: During morning and afternoon peak hours on weekdays, travel times (19–40 min) exceed those on weekends (16–35 min). Morning peak hours see higher taxi utilization in residential and transportation hubs, with schools and commercial and government areas as primary destinations. Conversely, afternoon peaks show a trend towards dining and entertainment zones from the abovementioned places. In the evening rush, residents enjoy a vibrant nightlife, and there are numerous locations for picking up and dropping off people. A chi-square test on weekday travel data yields a p-value of 0.023, indicating a significant correlation between the distribution of travel hotspots and paths.
Funder
National Natural Science Foundation of China
Key Scientific and Technological Project of Henan Province
Reference41 articles.
1. Ma, S., Zhang, J., Chen, X., and Liao, G. (2023). Identification of Urban Functional Zones Using Taxi Temporal Data. J. Jilin Univ. (Eng. Technol. Ed.), 1–10.
2. Analysis of Urban Residents’ Spatio-Temporal Characteristics of Travel Based on Chongqing Taxi Trajectory Data;Luo;Jiangxi Sci.,2023
3. Potential and flexibility analysis of electric taxi fleets V2G system based on trajectory data and agent-based modeling;Yu;Appl. Energy,2024
4. Prediction model of rail transit passenger flow in rain and snow weather;Feng;J. Harbin Inst. Technol.,2022
5. Advancing and lagging effects of weather conditions on intercity traffic volume: A geographically weighted regression analysis in the Guangdong-Hong Kong-Macao Greater Bay Area;Lin;Int. J. Transp. Sci. Technol.,2024
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