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为适应交叉口交通流的多态性,基于混合Erlang分布稠密性,采用期望最大化算法准确拟合交叉口主路交通流到达车头时距数据.以次路让行主路交叉口为研究对象,统计交叉口次路穿越主路的可接受间隙概率,提出基于混合Erlang分布的无信号交叉口通行能力模型.以实际交叉口调查车头时距为例,采用负指数分布、Erlang分布和混合Erlang分布分别拟合车头时距,并采用不同分布条件下无信号交叉口通行能力模型计算次路的通行能力,结果表明不仅混合Erlang分布更好拟合分布数据,所提出的无信号交叉口通行能力模型分析结果也更为准确.
In order to adapt to the polymorphism of traffic flow in the intersection, based on the mixed Erlang distribution density, the maximum-expected algorithm is used to accurately fit the traffic flow arriving at the main road to arrive at the headway distance data. , And calculate the acceptable gap probability of the secondary road crossing the main road, the traffic capacity model of the no-signal intersection based on mixed Erlang distribution is proposed. Taking the actual headway time as an example, the negative exponential distribution, Erlang distribution and mixed Erlang Distribution were fitted to the headway and the traffic capacity of the road without signalized intersections was calculated under different distribution conditions. The results show that not only the mixed Erlang distribution is better to fit the distribution data, the proposed capacity of no signalized intersection The result of model analysis is more accurate.