Multi-objective optimization method of traffic signal based on CTM
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摘要: 研究了城市交通信号的控制与优化问题, 以整个网络延误、油耗以及路网机动车尾气排放量为优化目标, 推导了基于元胞传输模型的网络延误、油耗以及路网机动车尾气排放量计算公式, 建立了一种基于元胞传输模型的城市交通信号控制的多目标优化方法, 并利用多目标遗传算法进行了优化求解。仿真结果表明: 应用此方法在轻度、中度、重度交通流状况下形成了绿波带, 可以实现对交通信号的协调控制, 同时实现了对路口交通信号的优化设置。Abstract: The signal control and optimization problems of urban traffic were studied. The total delay, fuel consumption and vehicle exhaust emission of road network were taken as optimization objectives, their calculation formulas were derived based on cell transmission model (CTM), and a multi-objective optimization method based on CTM for urban traffic signal control was presented. The solution of traffic signal was optimized by using multi-objective genetic algorithm. Simulation result shows that green wave bands form under mild, moderate and heavy traffic flow conditions, the coordination control of traffic signals can be achieved, and the optimization settings of intersection traffic signals are realized.
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表 1 初始参数
Table 1. Initial parameters
自由流速度/ (km·h-1) 48 反向传播速度/ (km·h-1) 48 拥挤密度/ (pcu·km-1) 124 饱和流量/ (pcu·h-1) 1 800 时间步/s 10 信号周期时间/s 40 最小绿灯或红灯时间/s 10 最大绿灯或红灯时间/s 30 建模时间范围/s 0~240 表 2 三种方案的动态装载
Table 2. Dynamic loads of three scenarios
方案 网络初始状态 装载持续时间/s 需求/ (pcu·h-1) 路段1 路段4 路段6 轻度 空网络 10~240 720 360 360 中度 具有1/4拥挤密度 10~240 1 080 360 360 重度 具有拥挤密度 10~120 1 800 360 360 130~240 0 0 0 表 3 轻度交通流信号配置方案
Table 3. Signal optimization project under mild traffic flow
时间步 车辆数/pcu 路口A信号设置 车辆数/pcu 路口B信号设置 车辆数/pcu 元胞(1, 1) 元胞(1, 2) 元胞(1, 3) 元胞(2, 1) 元胞(2, 2) 元胞(2, 3) 元胞(3, 1) 1 48 ×× ×× 2 46 2 ×× -- 3 44 2 2 -- -- 4 42 2 2 -- 2 -- 5 40 2 2 ×× 2 2 ×× 6 38 2 4 ×× 2 2 -- 7 36 2 6 -- 2 -- 2 8 34 2 3 -- 5 ×× 4 9 32 2 2 ×× 3 5 ×× 4 10 30 2 4 ×× 3 5 -- 4 11 28 2 6 -- 3 -- 9 12 26 2 3 -- 5 ×× 12 13 24 2 2 ×× 3 5 ×× 12 14 22 2 4 ×× 3 5 -- 12 15 20 2 6 -- 3 -- 17 16 18 2 3 -- 5 ×× 20 17 16 2 2 ×× 3 5 ×× 20 18 14 2 4 ×× 3 5 -- 20 19 12 2 6 -- 3 -- 25 20 10 2 3 -- 5 ×× 28 21 8 2 2 -- 3 5 ×× 28 22 6 2 2 ×× 2 3 5 -- 28 23 4 2 4 -- 2 3 -- 33 24 2 2 -- 4 2 -- 36 表 4 中度交通流信号配置方案
Table 4. Signal optimization project under moderate traffic flow
时间步 车辆数/pcu 路口A信号设置 车辆数/pcu 路口B信号设置 车辆数/pcu 元胞(1, 1) 元胞(1, 2) 元胞(1, 3) 元胞(2, 1) 元胞(2, 2) 元胞(2, 3) 元胞(3, 1) 1 72 4 4 ×× 4 4 4 ×× 2 69 3 8 ×× 4 8 ×× 3 66 3 11 ×× 12 -- 4 63 3 14 -- 7 -- 5 5 60 3 12 -- 5 2 ×× 10 6 57 3 10 -- 5 5 2 ×× 10 7 54 3 8 ×× 5 5 7 -- 10 8 51 3 11 -- 5 7 -- 15 9 48 3 9 -- 5 7 -- 20 10 45 3 7 -- 5 5 2 ×× 25 11 42 3 5 ×× 5 5 7 -- 25 12 39 3 8 -- 5 7 -- 30 13 36 3 6 -- 5 7 -- 35 14 33 3 4 -- 5 5 2 ×× 40 15 30 3 3 ×× 4 5 7 -- 40 16 27 3 6 -- 4 7 -- 45 17 24 3 4 -- 5 6 -- 50 18 21 3 3 -- 4 5 1 ×× 55 19 18 3 3 ×× 3 4 6 -- 55 20 15 3 6 -- 3 5 -- 60 21 12 3 4 -- 5 3 -- 65 22 9 3 3 -- 4 5 ×× 68 23 6 3 3 ×× 3 4 5 -- 68 24 3 3 6 -- 3 4 -- 73 表 5 重度交通流信号配置方案
Table 5. Signal optimization project under heavy traffic flow
时间步 车辆数/pcu 路口A信号设置 车辆数/pcu 路口B信号设置 车辆数/pcu 元胞(1, 1) 元胞(1, 2) 元胞(1, 3) 元胞(2, 1) 元胞(2, 2) 元胞(2, 3) 元胞(3, 1) 1 60 17 17 ×× 17 17 17 ×× 2 60 17 17 ×× 17 17 17 ×× 3 60 17 17 ×× 17 17 17 -- 4 60 17 17 -- 17 17 12 -- 5 5 60 17 17 ×× 17 12 12 ×× 10 6 60 17 17 ×× 12 12 17 ×× 10 7 60 17 17 ×× 7 17 17 -- 10 8 60 17 17 -- 7 17 12 -- 15 9 60 17 12 ×× 12 12 12 -- 20 10 60 12 17 ×× 7 12 12 ×× 25 11 55 17 17 ×× 2 12 17 -- 25 12 55 17 17 -- 14 12 -- 30 13 55 17 12 ×× 5 9 12 ×× 35 14 55 12 17 ×× 9 17 ×× 35 15 50 17 17 ×× 9 17 -- 35 16 50 17 17 -- 9 12 -- 40 17 50 17 12 -- 5 4 12 -- 45 18 50 12 12 ×× 5 5 11 ×× 50 19 45 12 17 ×× 5 16 -- 50 20 40 17 17 -- 4 12 -- 55 21 40 17 12 -- 5 0 11 -- 60 22 40 12 12 -- 5 5 6 ×× 65 23 35 12 12 ×× 5 5 11 -- 65 24 30 12 17 -- 5 11 -- 70 -
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