摘要 : As one of the most frequently occurred driving behaviors, the lane-changing’s impact on surrounding traffic is important. From the aspect of macro-traffic flows, its impact on traffic efficiency and safety has been investigated. H... 展开 As one of the most frequently occurred driving behaviors, the lane-changing’s impact on surrounding traffic is important. From the aspect of macro-traffic flows, its impact on traffic efficiency and safety has been investigated. However, as a non-essential lane-changing type, a single discretionary lane-changing’s impact on surrounding traffic is still difficult to be quantified by real-word traffic data. To solve this problem, this paper first proposes a trajectory data-based analytic method to calculate response time of the lane-changing vehicle and its following vehicles, then develops a time sequence data processing method based on feature points to analyze the change pattern of the variable minimum space, and then a lane-changing’s temporal and spatial on surrounding traffic can be captured by the decreasing-increasing pattern of minimum space. Besides, a high-precision trajectory data set, called Zen-traffic, is employed to demonstrate the effectiveness of the proposed methods and reach conclusions. Given the condition that the speed of a discretionary lane-changing vehicle is between 6 to 20 m/s, i.e., the traffic condition at which lane changes more likely occur, the results of the paper include (1) on average, 4 or 5 vehicles are usually impacted by a discretionary lane change; (2) the average impact time is 12 to 13 seconds and it has little relationship with the distance between the lane-changing vehicle and the following vehicle on the target/initial lane; (3) the lateral movement direction (i.e., changing to left or to right) of a lane change has a significant impact on the number of the vehicles affected. 收起