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Analysis of Merging Behavior Parameters Using NGSIM Data Sets

机译:使用NGSIM数据集分析合并行为参数

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A merging event involves three vehicles: the merging vehicle and the putative leading and following vehicles on the mainline. Understanding the interactions of the subject vehicle with the surrounding vehicles is fundamental to the study of the safety and modeling of merging behavior. This research studies the statistical properties of 8 lane changing parameters. These parameters describe the gaps, times to collision between vehicles and the merging vehicle's speed. Visual angle parameters are first analyzed during the merging situation. The parameter values were extracted from the vehicle trajectory data in the NGSIM data sets. The results show that: (ⅰ) some of the parameters are highly correlated; (ⅱ) visual angles are highly correlated with other parameters except the time-to-collisions; (ⅲ) the visual angles are best described by the Gamma distribution; (ⅳ) the gaps are best described by the log-logistic distribution; (ⅴ) the times to collisions and speed are best described by the logistic distribution. The results can help promote temporal and spatial accuracy of merging behavior models.
机译:合并事件涉及三种媒介:合并媒介以及主线上的假定的领先和后继媒介。了解主题车辆与周围车辆的相互作用是研究合并行为的安全性和建模的基础。本研究研究了8个车道变换参数的统计特性。这些参数描述了间隙,车辆之间的碰撞时间以及合并车辆的速度。在合并过程中,首先分析视角参数。从NGSIM数据集中的车辆轨迹数据中提取参数值。结果表明:(ⅰ)一些参数是高度相关的; (ⅱ)视角与碰撞时间以外的其他参数高度相关; (ⅲ)最好用Gamma分布描述视角; (ⅳ)差距最好用对数逻辑分布来描述; (ⅴ)逻辑分布最好地描述了碰撞时间和速度。结果可以帮助提高合并行为模型的时间和空间准确性。

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