Mixed Distribution Model of Vehicle Headway
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摘要: 为描述车头时距分布特性,基于二分车头时距的基本思想,将行驶车辆状态分为跟驰状态和自由流状 态,在分析其运行特征的基础上,建立了能同时描述这两类状态对应的车头时距分布特性的混合分布模型.应用 实测数据,通过EM(expectationmaximization)算法确定模型的相关参数,并结合参数取值分析了路段上、下游 和不同车道内车辆行驶统计特征的差异性,最后,进行了实例验证.研究结果表明:混合分布模型在实验路段各 处均可通过卡方检验;与负指数分布、爱尔朗分布和M3分布相比,混合分布模型对车头时距分布情况的拟合精 度平均提高10%以上,且对快速路入口匝道通行能力的计算结果与实测值较为接近.Abstract: For describing the distribution characteristics of headway, driving behaviors are classified into car-following state and free driving state by reference to the two-fluid theory. After analysis of their operation features, a mixed distribution model that can describe the headway distribution of both the two driving states was built. The model parameters were determined by expectation maximization (EM) algorithm using the measured data. Then, the differences between the statistical characteristics of the driving behaviors in up-stream section, downstream section and different lanes were analyzed and verified through a case study. The results show that the mixed distribution model can pass the chi-square test in all road situations. Compared with the negative exponential distribution, Erlang distribution, and M3 distribution, the mixed distribution model can improve the fitting accuracy of simulation by more than 10%, and obtain a more close result to the measured data in calculating the traffic capacity of an expressway on-ramp.
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Key words:
- headway /
- distribution model /
- car-following /
- free flow state
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