Analysis of taxi passenger travel characteristics combining POI and passenger hotspots
Abstract
Using taxi GPS data and Points of Interest (POI) data from Xi'an City, China, this study employs an improved DBSCAN algorithm (enhanced with k-distance curve) incorporating POI types to analyze the clustering characteristics of passenger pick-up and drop-off points on both weekdays and rest days. GIS technology is utilized for spatial visualization and analysis of travel patterns. The findings provide a basis for optimizing urban taxi operation scheduling and better meeting passenger travel demand.
Fields of Study & Subjects
Transportation Planning and Optimization
Human Mobility and Location-Based Analysis
Transportation and Mobility Innovations
Publication details
- Journal / source
- International Conference on Smart Transportation and City Engineering (STCE)
- Pages
- 88–88
- Publication date
- 3 March 2026
- Language
- EN