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作 者:郭丹丹 朱美宣 Dandan Guo;Meixuan Zhu(Traffic Management Department of Shanghai Hongqiao International Airport Co.,Ltd.,Shanghai;Seventh Management Department of Shanghai Pudong New Area Construction(Group)Co.,Ltd.,Shanghai)
机构地区:[1]上海虹桥国际机场有限责任公司交通管理部,上海 [2]上海市浦东新区建设(集团)有限公司第七项管部,上海
出 处:《建模与仿真》2025年第1期1168-1176,共9页Modeling and Simulation
摘 要:一种基于双层规划模型的单向交通组织优化方法,旨在通过最小化车辆绕行系数来提高交通效率。上层模型以车辆绕行系数和交通效率为优化目标,并引入主干道和微循环支路的饱和度约束。下层模型基于随机用户平衡配流模型(SUE),通过计算路径阻抗,模拟驾驶员在路网中的行为分配过程。为了求解该双层模型,采用遗传算法加Frank-Wolfe算法进行交通流分配。仿真结果表明,本文提出的模型能够有效优化单向交通方案,显著降低绕行系数,分流交通流量,提升交通效率,并为城市交通管理提供新的理论支持。This paper presents an optimization method for unidirectional traffic organization based on a bi-level programming model,aiming to improve traffic efficiency by minimizing the vehicle detour coefficient and maximizing the number of parking spaces.The upper-level model takes the vehicle detour coefficient and traffic efficiency as optimization objectives,and introduces constraints on the saturation of main roads and microcirculation branch roads.The lower-level model,based on the Stochastic User Equilibrium(SUE)model,simulates the behavior allocation process of drivers in the road network by calculating path impedance.To solve this bi-level model,a genetic algorithm combined with the Frank-Wolfe algorithm is used for traffic flow allocation.Simulation results show that the model proposed in this paper can effectively optimize unidirectional traffic schemes,significantly reduce the detour coefficient,divert traffic flow,enhance traffic efficiency,and provide new theoretical support for urban traffic management.
分 类 号:U491[交通运输工程—交通运输规划与管理]
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