Car-Following Behavior Analysis from Microscopic Trajectory Data
Car-Following Behavior Analysis from Microscopic Trajectory Data
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DOI：
10.1177/0361198105193400102
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发表时间：
2005
影响因子：
1.7
通讯作者：
Saskia Ossen;S. Hoogendoorn
中科院分区：
文献类型：
--
作者：
Saskia Ossen;S. Hoogendoorn
由于缺乏适当的微观数据，在汽车跟随领域建立准确、鲁棒的模型受到了很大的影响。由于缺乏这方面的研究，人们对驾驶员-车辆组合之间车辆跟随行为的差异知之甚少。本文利用从直升机采集的高分辨率高频数字图像中提取的车辆轨迹数据，研究了驾驶员个体的跟车行为。通过估计不同规格的Gazis-Herman-Rothery汽车跟随规则的参数来进行分析。这一分析表明，刺激和反应之间的关系可以在80%的情况下建立。本文的主要贡献在于可以识别个体驾驶员的跟车行为之间的相当大的差异。这些差异表现为反应时间和灵敏度的最优参数值不同，以及根据驾驶员个体数据得出的最优跟车模型不同。
The development of accurate and robust models in the field of car following has suffered greatly from the lack of appropriate microscopic data. Because of this lack, little is known about differences in car-following behavior between individual driver–vehicle combinations. This paper studies the car-following behaviors of individual drivers by making use of vehicle trajectory data extracted from high-resolution digital images collected at a high frequency from a helicopter. The analysis was performed by estimating the parameters of different specifications of the well-known Gazis–Herman–Rothery car-following rule for individual drivers. This analysis showed that a relation between the stimuli and the response could be established in 80% of the cases. The main contribution of this paper is that considerable differences between the car-following behaviors of individual drivers could be identified. These differences are expressed as different optimal parameter values for the reaction time and the sensitivity, as well as different car-following models that appear to be optimal on the basis of the data for individual drivers.