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摘要: 为了改善交通网络运行状况,根据车流密度的差异对宏观路网进行子区划分,提出了面向多个宏观基本图(Macroscopic fundamental diagram,MFD)子区的边界协调控制方法.根据划分的多个子区间邻接关系和流入流出交通流率,建立了路网车流平衡方程.通过与最佳累积车辆数进行比较,确定了拥挤度高的子区边界交叉口最佳流入与流出的交通流量;进而建立了以整个路网旅行完成流率最大、平均行程时间和平均延误最小的多目标边界协调优化模型,并通过自适应遗传算法对多目标函数进行求解.以存在4个MFD子区的实际路网为分析对象,对比仿真结果表明所提方法可有效提高路网运行效率、缓解拥堵状况.Abstract: In order to improve the service level of urban road network, the macro traffic network is divided into multiple macroscopic fundamental diagram (MFD) sub-regions on the basis of different traffic densities, and then a coordinated perimeter control method is proposed. According to the relations of traffic flows among multiple MFD sub-regions, a balance equation of network traffic flow is established. Compared with the optimal cumulative traffic volume of the network, the optimal traffic inflow and outflow at the crowded intersections of sub-regions perimeter are determined. Moreover, a multi-objective programming model is set up, which takes the maximum average trip completion flow of vehicles, the minimum average travel time and the average delay of road network as the objectives. Adaptive genetic algorithm is used to solve the multi-objective function. An actual road network with 4 MFD sub-regions is tested, and the result shows that the proposed strategies are effective in improving the network efficiency and alleviating traffic congestion.1) 本文责任编委 王占山
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表 1 子区路网基本参数
Table 1 Discrete modes of the normal traffic behavior
子区编号 路网面积 (km2) 主要路段数 路段主要长度 (m) 交叉口数量 路网交叉口周期时长 (s) 边界控制交叉口数量 边界交叉口周期时长 (s) 对外交通的路段数 整个路网 23.0 36 200 ~ 1 500 157 60 ~ 180 58 120 53 子区1 7.0 20 200 ~ 1 500 51 60 ~ 180 17 120 40 子区2 5.5 12 200 ~ 1 500 37 60 ~ 180 12 120 25 子区3 5.5 12 200 ~ 1 500 36 60 ~ 180 18 120 24 子区4 5.0 12 200 ~ 1 500 33 60 ~ 180 11 120 22 表 2 路网子区仿真参数标定
Table 2 Simulation parameters calibration of sub-regions in road network
子区编号 ai bi ci di R2 整个路网 4.5521 × 10−12 −2.7189 × 10−6 4.2024 × 10−3 −2.6534 0.6542 子区1 3.4734 × 10−11 −7.4891 × 10−7 4.3854 × 10−3 −0.0421 0.9456 子区2 3.6318 × 10−11 −7.0694 × 10−7 3.6828 × 10−3 0.6893 0.9000 子区3 1.7598 × 10−10 −2.4750 × 10−6 9.4675 × 10−3 −1.8034 0.9633 子区4 5.8298 × 10−11 −1.1125 × 10−7 5.7969 × 10−3 −0.2909 0.9646 表 3 子区基本仿真参数与边界控制参数
Table 3 Basic simulation parameters and perimeter control parameters of sub-regions
子区编号 仿真时间 (min) 仿真次数 路网初始累积车辆数 (veh) 路网最佳累积车辆数 (veh) εi(veh) 路网最大累积车辆数 (veh) 路网平均增加交通流量 (veh/min) 平均自由流速度 (km/h) 整个路网 300 150 4 000 12 000 240 38 000 100 ~ 250 50 子区1 300 150 1 000 4 090 82 10 000 50 ~ 100 50 子区2 300 150 1 000 3 660 73 9 000 10 ~ 80 50 子区3 300 150 1 000 2 700 54 7 000 20 ~ 70 50 子区4 300 150 1 000 3 660 73 10 000 20 ~ 807 50 表 4 子区平均累积车辆数统计表
Table 4 Statistics of the average accumulation in sub-regions
控制方法 子区平均累积车辆数 (veh) 子区1 子区2 子区3 子区4 整个路网 NPC 4 353 2 616 2 061 2 937 11 966 PC 3 345 2 379 2 280 3 126 11 220 CPC 3 597 2 656 2 113 2 986 11 352 表 5 路网平均旅行车辆完成流率和旅行车辆完成车辆数统计
Table 5 Statistics of the average trip completion flow and the average completion volume in road network
控制方法 路网平均旅行车辆完成流率 (veh/s) 路网平均旅行车辆完成车辆数 (veh) 子区1 子区2 子区3 子区4 整个路网 子区1 子区2 子区3 子区4 整个路网 NPC 6.9001 4.1933 7.8741 7.3487 6.2507 13 837 9 696 12 876 16 310 52 719 PC 7.0079 3.5725 8.4664 7.5583 6.6512 15 003 9 024 13 384 16 493 53 904 CPC 7.4269 4.2599 8.1628 8.0085 6.9646 15 901 10 760 13 348 17 774 57 783 表 6 子区平均行程时间之和与路网平均延误之和统计
Table 6 Statistics of sum of the total travel time in sub-regions and the average delay time of the road network
控制方法 部分子区之间的行程时间之和 (h) 路网平均延误之和 (h) t12 t13 t14 t24 整个路网 子区1 子区2 子区3 子区4 整个路网 NPC 44.80 33.60 56.00 43.24 44.41 54.82 24.63 24.24 22.60 31.57 PC 38.33 28.75 47.92 45.90 40.23 42.75 24.79 26.95 25.88 29.84 CPC 38.32 28.74 47.90 42.30 39.32 42.82 25.00 24.78 22.56 28.79 -
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