Yang Quantao, Lu Feng, Ma Jun, Niu Xuejun, Wang Jingsheng
Department of Traffic Management School, People's Public Security University of China, Beijing, 100038, China.
Sci Rep. 2021 Nov 11;11(1):22047. doi: 10.1038/s41598-021-00262-1.
Vehicle lane-changing on urban roads is the most common traffic behavior, in which the driver changes the direction or increases the speed of the vehicle by changing its trajectory. However, in high-density traffic flow, when a vehicle changes lanes, a series of vehicles following the target vehicle in the target lane will be delayed. In this study, DJI Phantom 4 drones were used to vertically record the traffic on a road section. Tracker software was then used to extract vehicle information from the video taken by the drones, including the vehicle operating speeds, etc. SPSS 22 and Origin analysis software were then employed to analyze the correlations between different vehicle operating parameters. It was found that the operating speed of the first vehicle following the target vehicle in the target lane is related to the speeds and positions of both the target vehicle and the vehicle preceding it. Under the condition of high-density traffic flow, when the target vehicle is inserted into the target lane, the speed of the vehicles following the target vehicle in the target lane will change. To model this process, the corresponding Sine and DoseResp models were constructed. By calculating the delays of vehicles following the target vehicle in the target lane, it was concluded that the overall delay of the fleet is 3.9-9.5 s.
城市道路上的车辆变道是最常见的交通行为，在此过程中驾驶员通过改变车辆轨迹来改变车辆行驶方向或提高车速。然而，在高密度交通流中，当一辆车变道时，目标车道内跟随目标车辆的一系列车辆都会被延误。在本研究中，使用大疆精灵4无人机垂直记录某一路段的交通情况。然后利用追踪软件从无人机拍摄的视频中提取车辆信息，包括车辆行驶速度等。接着运用SPSS 22和Origin分析软件分析不同车辆运行参数之间的相关性。研究发现，目标车道内跟随目标车辆的第一辆车的行驶速度与目标车辆及其前车的速度和位置有关。在高密度交通流条件下，当目标车辆插入目标车道时，目标车道内跟随目标车辆的车辆速度会发生变化。为了模拟这一过程，构建了相应的正弦模型和剂量反应模型。通过计算目标车道内跟随目标车辆的车辆延误情况，得出车队的总延误为3.9 - 9.5秒。
