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首页> 外文期刊>Promet-traffic & transportation >INTERSECTION SIGNAL TIMING OPTIMISATION FOR AN URBAN STREET NETWORK TO MINIMISE TRAFFIC DELAYS
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INTERSECTION SIGNAL TIMING OPTIMISATION FOR AN URBAN STREET NETWORK TO MINIMISE TRAFFIC DELAYS

机译：城市街道网络的交点信号定时优化，以最大限度地减少交通延误

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摘要

The ever-increasing travel demand outpacing available transportation capacity especially in the U.S. urban areas has led to more severe traffic congestion and delays. This study proposes a methodology for intersection signal timing optimisation for an urban street network aimed to minimise intersection-related delays by dynamically adjusting green splits of signal timing plans designed for intersections in an urban street network in each hour of the day in response to varying traffic entering the intersections. Two options are considered in optimisation formulation, which are concerned with minimising vehicle delays per cycle, and minimising weighted vehicle and pedestrian delays per cycle calculated using the 2010 Highway Capacity Manual (HCM) method. The hourly vehicular traffic is derived by progressively executing a regional travel demand forecasting model that could handle interactions between signal timing plans and predicted vehicular traffic entering intersections, coupled with pedestrian crossing counts. A computational study is conducted for methodology application to the central business district (CBD) street network in Chicago, USA. Relative weights for calculating weighted vehicle and pedestrian delays, and intersection degrees of saturation are revealed to be significant factors affecting the effectiveness of network-wide signal timing optimisation. For the current study, delay reductions are maximised using a weighting split of 78/22 between vehicle and pedestrian delays.
机译：不断增加的旅行需求超越可用的运输能力，特别是在美国城市地区导致了更严重的交通拥堵和延误。本研究提出了一种用于城市街道网络的交叉信号时序优化的方法，旨在通过动态调整与城市街道网络中的信号时序计划的绿色分配来最小化与城市街道网络中的一天中的各个小时响应于不同的流量输入交叉点。优化配方中考虑了两种选择，这涉及每周期最小化车辆延迟，并使用2010高速公路容量手册（HCM）方法计算每周期的加权车辆和行人延误。通过逐步执行区域旅行需求预测模型来导出每小时的车辆流量，该模型可以处理信号时序计划和进入交叉口的预测车辆交通之间的相互作用，再加上行人交叉数。在美国芝加哥的中央商业区（CBD）街道网络进行了计算研究。计算加权车辆和行人延迟的相对权重，以及交叉饱和度是影响网络宽信号定时优化的有效性的重要因素。对于目前的研究，使用车辆和行人延迟之间的78/22的加权分裂最大化延迟减少。

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