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

Abstract Lane-changing behaviour is one of the complex driving behaviours. The lane-changing behaviour of drivers may exacerbate congestion, however driver behavioural characteristics are difficult to accurately acquire and quantify, and thus tend to be simplified or ignored in existing lane-changing models. In this paper, the Bik-means clustering algorithm is used to analyse the urban road congestion state discrimination method. Then, simulated driving tests were conducted for different traffic congestion conditions. Through the force feedback system and infrared camera, the data of driver lane-changing behaviours at different traffic congestion levels are obtained separately, and the definitions of the start and end points of a vehicle changing lanes are determined. Furthermore, statistical analysis and discussion of key feature parameters including driver lane-changing behaviour 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 2 s, 4 s, 6 s and 7 s, while the turn-signal duration and the number of rear-view 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 mm to 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.