An Analysis of Driver's Route Choice Behavior in Urban Road Networks Based on GPS Data

Abstract

This paper studies drivers' route choice behavior in urban road networks by analyzing the results of a drivers' route choice survey. The survey data are GPS vehicle location data recorded from 4900 GPS equipped probe vehicles in central district of Guangzhou city, so drivers' real route choice behavior in different situations can be well reflected. Among many factors affecting drivers' route choice behavior, distance, road category, intersection, turn and traffic signal control are considered as major factors to discuss. Statistics and data mining method are used to analyze the survey data, including correlation analysis, frequent pattern mining and cluster analysis. The analysis results show that most drivers prefer the route with least turn count, and the preference between distance and arterial ratio depends on different drivers. The empirical analysis results provide a good foundation of