Analysis of Small Vehicle Lane-Changing Characteristics of Urban Expressway Based on Naturalistic Driving Trajectory Data

Car following and lane changing are important research directions in traffic flow theory, and the factors involved in lane changing behavior are more complex than following. The current analysis of lane-changing characteristics based on foreign public trajectory datasets can hardly cover the lane-changing behavior characteristics in line with Chinese drivers, and at the same time, most of the domestic and foreign dataset collection sources are concentrated on highways, which does not consider the influence of different road types on the characteristics of lane-changing behavior. In order to study the characteristics of vehicle lane-changing behavior on typical urban roads in China, an unmanned aerial vehicle(UAV)was used to photograph the traffic flow on the straight section of the urban expressway in Wuhan, to obtain the natural driving data in line with the characteristics of urban roads and drivers in China, and to perform lane-changing identification and parameter extraction on the dataset. The video captured by the UAV contains 8 609 small vehicles, and based on whether the lane number where the vehicle is located changes and the number of changes as the recognition standard for lane-changing vehicles, a total of 6 897 vehicle trajectory data are extracted from the following vehicles(no change in the lane number where the vehicle is located), and 1 712 single lane-changing vehicle trajectory data are extracted(the lane number where the vehicle is located changes only once). Based on the extracted trajectory data of the following vehicles, obtain the average speed of the road traffic flow and the average distance between the following vehicles, so as to analyze the real-time operation state of the traffic flow; based on the extracted trajectory data of the single lane-changing vehicles, adopt a fixed time window as the basis for judging the starting and ending points of the lane-changing, and on this basis, obtain the longitudinal displacement of the vehicle changing the lane and the distance between it and the neighbor vehicles when the lane-changing is started, and the safety of lane-changing behavior is analyzed by combining with the real-time operation state of the traffic flow. The safety analysis of lane-changing behavior is carried out by combining the real-time operation status of traffic flow. Through the distribution fitting and statistical analysis of the obtained traffic parameters of following and lane changing, the results show that the average value of road traffic speed is 19.257 1 m/s, the average value of vehicle following distance is 45.910 7 m, the average value of vehicle longitudinal displacement is 115.515 m, and the distribution of the distance between the vehicle and peripheral cars at the time of lane changing is in line with the lognormal distribution. Among them, the average value of the lane change vehicle time distance from the vehicle in front of the target lane is significantly higher than the average value of the vehicle time distance from the vehicle in front of the initial lane. It is also found that some drivers still choose to change lanes when the distance from the rear vehicle in the target lane is small, which reflects the aggressive driving of some drivers. This study can provide a reference for analyzing the characteristics of lane-changing on urban expressways in China and developing a lane-changing behavior model suitable for Chinese traffic characteristics.