Path Choice Behavior Analysis Based on Vehicle Trajectory Data

Understanding path choice behavior is important for accurately modelling and estimating traffic distribution. However, large scaled path choice data is usually difficult to obtain. Most current studies use survey data in a relatively small sample. This paper analyzes path choice behavior based on trajectory data obtained by license plate recognition from cameras. Data from Mianyang on September 1, 2018 is used in this study. Raw data includes license plate, vehicle type, time, and camera serial number. Trajectory data is obtained after data processing. Results show a surprising path choice preference, especially during the peak period. Multiple paths are shown in trips between a same OD pair, which can possibly be explained by the fact that residents in a middle size city often have multiple activities connected during peak hours. This finding may provide a new angle for modelling traffic distribution in small and medium cities.