基于轨迹数据的舒适距离汽车跟随模型研究

Han Xing, Shuyi Wang, Zifan Yang, Yao Ren, Nan Jia, Yi Liu
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引用次数: 0

摘要

汽车跟随模型通常假设每个驾驶员倾向于与自己前面的车辆保持最小的安全距离,或者倾向于以理想的速度行驶。通过对NGSIM数据的分析发现,当驾驶员与领头车保持相似的速度时,领头车与跟随车之间的距离往往不是最小安全距离。此外,由于对前车速度的感知缺失,导致后车的期望速度与前车的期望速度不相等,尤其是在前车速度变化较大的情况下。本文提出了以舒适行驶距离代替传统跟车模型中的最小安全距离,并给出了理想行驶速度的计算方法。采用Logistic函数对弹簧-阻尼器汽车跟随模型中的线性函数进行了改进,使模型能更好地拟合跟随车辆行驶速度的变化。仿真结果验证了所建模型的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on comfortable distance based car-following model with trajectory data
Car following models usually assume that individual drivers tend to keep a minimum safe distance from the vehicle in front of themselves, or tend to drive at a desired velocity. Through the analysis of NGSIM data, it is found that the distance between leader car and follower car is often not the minimum safe distance when the driver maintains similar velocity with the leading vehicle. Moreover, due to miss perception of leading vehicle's velocity, the following vehicle's desired velocity is not equal to the leading vehicle's, especially when the leading vehicle's velocity changes greatly. In this paper, the comfortable driving distance is proposed to replace the minimum safe distance in the traditional car-following model, and the calculation method of the desired velocity is given. Logistic function was used to improve the linear function in the spring-damper car-following model, which fit the changing of driving velocity of follower vehicles better. Simulation results are provided to validity the model developed in this paper.
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