多态交通条件下无信号交叉口通行能力模型

Capacity model of unsignalized intersection under multi-state flow conditions

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 nmlti-state characteristic of traffic flow in intersections, based on the denseness of mixture Erlang distribution, the arriving headway data of main road is fitted accurately by means of expectation maximization algorithm. Taking intersection in wlhich the flow in minor road should give way to the one in main road as the research object and gathering the probabilities of minor road acceptable gaps, a capacity model of unsignalized intersection is put forward based on mixture Erlang distribution. Taking the actual survey headway of intersection as example, headway is fitted by using negative exponential distribution, Erlang distribution and mixture Erlang distribution, and then the minor road capacity is calculated with the capacity model of unsignalized intersection under different distribution conditions. The result indicates that mixture Erlang distribution shows better fitness, and the analysis result of proposed capacity model of unsignalized intersection is more accurate.