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基于蚁群算法的城市快速路优化控制 被引量:2

Optimal Control for Urban Expressway Based on Ant Colony Algorithm
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摘要 根据城市快速路交通流的特性,以宏观稳态交通流Macro模型为基础,将快速路虚拟划分为多个路段,将车辆在快速路系统内总的服务流量最大及入口匝道车辆平均等待时间最小作为优化控制目标,设计快速路多匝道联合控制模型,并采用蚁群优化算法对设计的控制模型进行求解计算,以确定各匝道最优调节率。模拟实验结果表明,通过多匝道联合控制,能够提高城市快速路系统的运行效率,减少交通事故及交通拥堵的发生概率。 According to the traffic flow features of urban expressway,the maximum total flow and minimum average waiting time at ramp are considered as the optimization goal based on Macro-state model.Meanwhile,a joint control model is designed using multiple ramps metering.Futhermore,the Ant Colony Optimization(ACO) algorithm is used for calculating the optimal adjust rates of ramps.Simulation results show that it can improve the operational efficiency of the expressway system and reduce the probability of traffic accidents and traffic jams.
出处 《计算机工程》 CAS CSCD 北大核心 2011年第23期174-176,180,共4页 Computer Engineering
基金 国家自然科学基金资助项目(50908213) 浙江省自然科学基金资助项目(Y1100891) 浙江省交通运输厅科技基金资助项目(2010H31)
关键词 匝道控制 城市快速路 蚁群优化算法 联合控制模型 ramp control urban expressway Ant Colony Optimization(ACO) algorithm joint control model
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