The Characteristics of Driver Lane-Changing Behavior in Congested Road Environments

Abstract

Abstract Lane changing behavior is a more complex driving behavior among driving behaviors. The lane changing behavior of drivers may exacerbate congestion, however, driver behavioral characteristics are difficult to be accurately acquired and quantified, and thus tend to be simplified or ignored in existing lane changing models. In this paper, the Bik-means clustering algorithm is used to analyze the urban road congestion state discrimination method. Then, simulated driving scenarios under different traffic congestion conditions for simulated driving tests. Through the force feedback system and infrared camera, the data of driver lane-changing behaviors at different traffic congestion levels are obtained separately, and the definitions of the starting and ending points of a vehicle changing lanes are determined. Furthermore, statistical analysis and discussion of key feature parameters including driver lane-changing behavior data and visual data under different levels of traffic congestion were conducted. It is found that the average lane change intention times in each congestion state are 2s, 4s, 6s and 7s, while the turn signal duration and the number of rearview mirror observations have similar patterns of change to the data on lane-changing intention duration. Moreover, drivers’ pupil diameters become smaller during the lane-changing intention phase, and then relatively enlarge during lane-changing, the range of pupil variation is roughly 3.5-4 mm. The frequency of observing the vehicle in front of the target lane increased as the level of congestion increased, and the frequency of observation in the driver's mirrors while changing lanes approximately doubled compared to driving straight ahead, and this ratio increased as the level of congestion increased.