Speed estimation model during lane-changing decision

In order to research the driver's estimation characteristic for rear-vehicle speed during lane-changing decision, small passenger car was used as test platform and established by using microwave radar, vehicle CAN-bus data logger, audio-video monitoring system. 15 drivers were recruited, and the estimation test of rear-vehicle speed was carried out in a normal highway. The speeds of test vehicle were set as 60, 70, 80, 90 km·h-1 separately, and 1 625 sets of data were obtained finally. The impact characteristics of relative speed, rear-vehicle speed, and relative distance on driver's speed estimation behavior were analyzed by using significance analysis method. A driver's speed estimation model was established by using multiple linear regression theory, and the model was examined. Analysis result shows that 60% of absolute values of speed estimate errors are no more than 10 km·h-1, and the driver's speed estimation error follows a normal distribution. Driver's speed estimation error decreases with the increase of relative speed and rear-vehicle speed, when the relative speed or rear-vehicle speed is lower, rear-vehicle speed is overestimated, and when the relative speed or rear-vehicle's speed is higher, rear-vehicle speed is underestimated. When the relative distance of vehicles increase, the driver's speed estimation error change very small. However, when the relative distance is smaller, rear-vehicle speed is overestimated by driver. The average estimation errors of speed estimation model is -0.56 km·h-1, so the model is feasible. © 2015, Editorial Department of Journal of Traffic and Transportation Engineering. All right reserved.