Car-Following Headways on Freeways Interpreted by the Semi-Poisson Headway Distribution Model
Car-Following Headways on Freeways Interpreted by the Semi-Poisson Headway Distribution Model
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DOI：
10.1287/trsc.13.1.36
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发表时间：
1979-02
影响因子：
4.6
通讯作者：
P. Wasielewski
中科院分区：
文献类型：
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作者：
P. Wasielewski
这项工作的目标是调查司机跟车模式的高速公路上，特别是作为一个功能的交通流量水平，使用车头时距分布模型。一些作者已经开发了“双分量”车头时距分布模型，该模型假设道路上的车辆可以根据它们是否与前方车辆相互作用而分为两组。这种类型的模型，"半泊松"模型提出的巴克利，被施加到一个数据库，包括42,000观察车头时距从一个单一的车道的城市高速公路的流量范围从900到2,000辆车每车道每小时。先前开发的计算方法允许直接从观察到的总车头时距分布通过数值求解积分方程来计算跟随者车头时距分布，而不引入用于跟随者分布的参数形式。由此产生的追随者车头时距分布被认为是独立的流量与平均值为1.32秒和0.52秒的标准偏差。模型结果与实测数据之间没有统计学显著差异。半泊松模型的理论基础进行了讨论，并与其他模型进行比较，以评估的解释与汽车跟随的可解释性。
The goal of this work is to investigate driver car-following patterns on freeways, particularly as a function of traffic flow level, using a headway distribution model. A number of authors have developed “two-component” vehicular headway distribution models that assume vehicles on a road can be divided into two groups according to whether or not they are interacting with the vehicle ahead. A model of this type, the “semi-Poisson” model proposed by Buckley, is applied to a data base consisting of 42,000 observed headways from a single lane of an urban freeway over a range of flow from 900 to 2,000 vehicles per lane per hour. A previously developed computational method allows the distribution of followers headways to be calculated directly from the observed total headway distribution by numerically solving an integral equation without introducing a parametric form for the followers distribution. The resulting followers headway distribution is found to be independent of the flow with a mean of 1.32 s and a standard deviation of 0.52 s. No statistically significant discrepancies are found between the model results and the observed data. The theoretical basis for the semi-Poisson model is discussed and compared with those of other models in order to assess the plausibility of the interpretation with respect to car following.