摘要
为了探究城市信号交叉口非机动车干扰机动车行驶的问题,通过调查分析各进口道机动车运行特性,对直行和直左的进口道机动车饱和车头时距及通行能力计算方法进行研究。首先,从进口道停车线出现4种不同跟驰模型的概率出发,构建车辆起始阶段混合车头时距模型,结合实际数据得到车头时距的修正系数;然后,分析采集数据得到非机动车数量对驶入信号交叉口的机动车混合车头时距的影响,采用回归分析法构建对应的特征模型;最后结合交叉口实际信号灯时间计算通行能力。研究结果表明:所采用的通行能力计算方法与实测值的误差更小,较《城市道路设计规范》法及HCM(highway capacity manual)通行能力计算法的误差更低,提高了信号交叉口通行能力计算结果的精准度。
In order to explore the problem that non motor vehicles interfere with motor vehicle driving at urban signalized intersections, the calculation method of saturated headway and capacity of motor vehicles on straight and straight left entry lanes is studied by investigating and analyzing the operation characteristics of motor vehicles on each entry lane. Firstly, starting from the probability of four different car following models on the parking line of the entrance road, the hybrid headway model at the initial stage of the vehicle is constructed, and the correction coefficient of the headway is obtained combined with the actual data. Then, the influence of the number of non motor vehicles on the head time distance of motor vehicles entering the signal intersection is obtained by analyzing the collected data, and the corresponding characteristic model is constructed by regression analysis method. Finally, the traffic capacity was calculated according to the actual signal time of the intersection. The research results show that the error between the capacity calculation method used in this paper and the measured value is lower, and the error is smaller than that of the code for urban road design method and HCM(highway capacity manual) capacity calculation method, which improves the accuracy of the capacity calculation results of signalized intersections.
作者
黄艳国
张升升
谭卢敏
HUANG Yan-guo;ZHANG Sheng-sheng;TAN Lu-min(College of Electrical Engineering and Automation,Jiangxi University)
出处
《科学技术与工程》
北大核心
2022年第27期12192-12200,共9页
Science Technology and Engineering
基金
国家自然科学基金(72061016)
江西省教育厅科技项目(GJJ160608)
留学基金委资助项目(201908360225)。
关键词
通行能力
信号交叉口
跟驰模型
混合车头时距
回归分析法
traffic capacity
signalized intersection
following model
hybrid headway
regression analysis method
