城市交叉口三左转车道流量均衡性及影响因素
发布时间：2018-12-10 22:02
【摘要】：根据多车道流量分布与驾驶员车道选择行为之间的关系,提出多车道设施流量均衡性的建模与分析方法.以城市道路信号控制交叉口三左转车道为例,使用成分数据结构组织各左转车道流量,选取可能对车道流量分布具有潜在影响的7个因素.在单形中建立以三左转车道流量成分数据为因变量、所选影响因素为自变量且满足车道流量占比约束的成分方差分析模型,设计单形操作法进行模型估计.研究结果表明,模型可识别对左转车流分布具有显著性影响的因素,并定量估计各因素对每条左转车道流量占比的影响程度.信号周期长度、交叉口内转弯曲线长度、展宽车道的设置、上游路段长度、上游左转车道标志标线位置和其他流向车道数等因素可在特定设置条件下使车流分布接近均衡.
[Abstract]:According to the relationship between multi-lane flow distribution and driver's lane selection behavior, a modeling and analysis method for traffic balance of multi-lane facilities is proposed. Taking the three left lane of the urban road signal control intersection as an example, using the component data structure to organize the flow of each left turn lane, 7 factors which may have potential influence on the lane flow distribution are selected. An analysis of variance model based on three left lane traffic component data is established in a simplex, and the influence factor is independent variable and meets the restriction of lane flow ratio. The simplex operation method is designed to estimate the model. The results show that the model can identify the factors that have significant influence on the left-turn traffic distribution and quantitatively estimate the influence of each factor on the flow ratio of each left-turn lane. Signal cycle length, curve length of intersections, setting of widening lane, length of upstream section, marking position of upper left turn lane and number of other flow lanes can make the traffic flow distribution close to equilibrium under certain setting conditions.
【作者单位】： 同济大学道路与交通工程教育部重点实验室;同济大学交通运输工程学院;佛罗里达大学城市与区域规划系;上海交通大学船舶海洋与建筑工程学院;云南省交通规划设计研究院陆地交通气象灾害防治技术国家工程实验室;
【基金】：“十二五”国家科技支撑计划(2014BAG01B02) 上海市自然科学基金(17ZR1431800)
【分类号】：U491.23
，
本文编号：2371273
[Abstract]:According to the relationship between multi-lane flow distribution and driver's lane selection behavior, a modeling and analysis method for traffic balance of multi-lane facilities is proposed. Taking the three left lane of the urban road signal control intersection as an example, using the component data structure to organize the flow of each left turn lane, 7 factors which may have potential influence on the lane flow distribution are selected. An analysis of variance model based on three left lane traffic component data is established in a simplex, and the influence factor is independent variable and meets the restriction of lane flow ratio. The simplex operation method is designed to estimate the model. The results show that the model can identify the factors that have significant influence on the left-turn traffic distribution and quantitatively estimate the influence of each factor on the flow ratio of each left-turn lane. Signal cycle length, curve length of intersections, setting of widening lane, length of upstream section, marking position of upper left turn lane and number of other flow lanes can make the traffic flow distribution close to equilibrium under certain setting conditions.
【作者单位】： 同济大学道路与交通工程教育部重点实验室;同济大学交通运输工程学院;佛罗里达大学城市与区域规划系;上海交通大学船舶海洋与建筑工程学院;云南省交通规划设计研究院陆地交通气象灾害防治技术国家工程实验室;
【基金】：“十二五”国家科技支撑计划(2014BAG01B02) 上海市自然科学基金(17ZR1431800)
【分类号】：U491.23
，
本文编号：2371273
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