Study on Capacity Matching of Upstream and Downstream Node Identification for Commuter Paths
Year: 2025
Type: article
Abstract: 针对城市道路高峰小时通勤路径中车辆排队累积并溢出至上游节点，导致上下游节点通行能力折损的问题，研究在分析四类典型通勤路径场景的基础上，综合考虑上下游间距等静态因素，以及流量流向与信号参数等动态因素，提出了上下游流量流向匹配辨识模型；进一步通过调节信号配时、相位相序及可变车道等策略，建立了上下游节点通行能力匹配模型。案例结果表明，上游直行、下游直行或左转的路径一、二匹配度均在0.79以上，效果显著；四类路径实施匹配策略后，整体通行能力匹配率提升了5.8%，其中上游直行下游左转的路径二、上游左转下游直行的路径三，通行能力匹配率提升均超过20%。因此，本研究提出的路径通行能力匹配模型具有较强的工程应用价值。The issue of vehicle queues accumulating and spilling over to upstream nodes during peak commuting hours on urban roads leads to reduced capacity at both upstream and downstream nodes. The study analyzed four typical commuter path scenarios and proposed a flow-direction matching identification model. This model considers both static factors, such as upstream-downstream spacing, and dynamic factors, like flow direction and signal parameters. Further, by adjusting signal timing, phase sequence, and variable lanes, a capacity matching model for upstream and downstream nodes was developed. Case results show that the matching degree for paths with upstream straight and downstream straight or left turns (Path 1 and 2) is above 0.79, indicating significant improvement. After implementing the matching strategy, the overall capacity matching rate increased by 5.8%. In particular, Path 2 (upstream straight, downstream left turn) and Path 3 (upstream left turn, downstream straight) saw capacity matching improvements exceeding 20%. Therefore, the proposed path capacity matching model has strong engineering application value.
Author: 佼 姚
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409306587