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【背景】现有的潮汐车道设置方法多针对平原城市，缺乏对山地城市复杂地形的特定考虑，并且大多侧重于单车道的控制优化，尚未充分探讨多条潮汐车道的协同控制问题。【目标】提出一种适用于山地城市的潮汐车道设置方法，通过优化车道位置选择、车道数分配和协同控制等，缓解潮汐现象引发的单向交通拥堵问题。【方法】在考虑道路条件和交通流量特征约束基础上，筛选出符合所有约束条件的路段作为潮汐车道设置的备选路段，以最小化路网总运行成本和优化流量分配为目标，构建了潮汐车道设置的双层规划模型，并通过遗传算法与Frank-Wolfe算法求解，确定潮汐车道的位置和车道数分配。然后，量化相邻交叉口的路径关联度，构建潮汐车道关联区划分模型，实现潮汐车道协同控制。【结果】对重庆某区域路网进行仿真分析，结果表明：潮汐车道设置后，方向不均衡系数降低了3.04%，饱和度降低了4.19%，有效缓解了潮汐交通造成的拥堵现象。【应用】本文提出的潮汐车道设置方法为山地城市的交通管理提供了理论支持，对优化路网运行效率具有指导意义。
Abstract：[Background] Existing methods for setting tidal lanes mainly focus on flat citiesanddo not specifically consider the complex terrain of mountainous cities. Moreover, most studies concentrate on optimizing single-lane control, with insufficient exploration of the collaborative control of multiple tidal lanes.[Objective] Propose a method for establishing tidal lanes in mountainous cities,aiming to alleviate the one-way traffic congestion caused by tidal phenomena by optimizing lane position selection, lane number allocation, and collaborative control. [Methods] Candidate sections for tidal lane settings were identified based on constraints related to road conditions and traffic flow characteristics. A bi-level programming model was developed to minimize the total network operational cost and optimize traffic flow distribution. The genetic algorithms and Frank-Wolfe algorithms were used to solve the model and determine tidal lanes location and allocation. Furthermore, a tidal lane correlation partitioning model was established by quantifying the degree of path correlation between adjacent intersections, thereby achieving collaborative control of tidal lanes.[Results] Simulation analyses of a road network in a specific area of Chongqing showedthat after the implementation of tidal lanes, the directional imbalance coefficient is reduced by 3.04%, and the saturation is reduced by 4.19%, effectively alleviating the congestion caused by tidal traffic.[Application] The proposed method provides support for traffic management of tidal lanes in mountainous cities and offers guidance for optimizing network operation efficiency.
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基本信息:
DOI：10.19961/j.cnki.1672-4747.2024.11.011
中图分类号:U491.22
引用信息:
[1]林婧,姜涛,蔡晓禹等.山地城市潮汐车道设置方法[J].交通运输工程与信息学报,2025,23(02):1-15.DOI:10.19961/j.cnki.1672-4747.2024.11.011.
基金信息:
重庆市教委科学技术研究项目（KJZD-M202300702）; 重庆交通大学自然科学类揭榜挂帅重点项目（XJ2023000801）;重庆交通大学研究生科研创新项目（2022B0008）; 道路交通安全管控技术国家工程研究中心开放课题（2024GCZXKFKT01）; 重庆市高等教育教学改革研究项目（182028）