A Speed Guidance Method at Signalized Intersections Based on Vehicle Infrastructure Cooperation
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摘要: 针对现有的车速引导模型存在未综合考虑车辆跟驰行为、引导场景划分较粗略等问题，研究了4种基于车路协同环境下实时优化各车的车速引导模型。对车辆进行所属车辆列队划分，考虑车速引导影响对FVD跟驰模型进行改进。以车辆列队为引导单元，将车辆可能面临的交通状况细分为8种引导场景，以引导车辆不停车或少停车通过交叉口为目标，直接优化车辆加/减速度，建立车辆列队后车根据改进的跟驰模型计算目标跟驰加/减速度，并与头车组成列队以同一目标车速通过交叉口停车线的4种车速引导模型。以南昌市海棠北路/枫林西大街交叉口为例进行仿真验证，结果表明，所提出的车速引导模型能使车辆行程时间减少18.9%，最大排队长度减少58.8%，延误减少60.8%，燃油消耗减少36.4%，且适用于不同交通饱和状态，对提高信号交叉口通行效率和减少车辆燃油消耗有显著效果。Abstract: The existing speed guidance models for vehicles are not comprehensively considering the car-following behaviors and the roughdivision of guidance scenes. This paper studies four speed guidance models based on real-time optimization of eachvehicle in vehicle infrastructure cooperation. The vehicles are divided into queues, and the FVD car-following model is improved considering the influences of speed guidance. The vehicle platoon is used as the guidance unit, and the traffic conditions are subdivided into eight guidance scenarios. Withthe goals of optimizing the operating efficiency of the intersection without stopping or withless stopping, four vehicle speed guidance models are established to optimize vehicle acceleration/deceleration by calculating the target acceleration/deceleration based on the improved car-following model, that the following vehicles can cross the intersection stop line in a platoon at the same target speed withthe leading vehicle. The intersection between Haitang NorthRoad and Fenglin West Street in Nanchang is taken as a case study for verification. The results show that the proposed model can reduce vehicle travel time by 18.9%, maximum queue lengthby 58.8%, delay by 60.8%, and fuel consumption by 36.4%. It is suitable for different traffic saturation conditions, significantly improving the traffic at signalized intersections and reducing vehicle fuel consumption.
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图 2 不同场景下目标车辆列队速度引导轨迹示意
Figure 2. The speed guide trajectory of the target fleet in different scenarios
图 4 有无速度引导Vissim仿真场景对比
Figure 4. Comparison of Vissim simulation scenarios withor without speed guidance
图 5 无速度引导场景车辆时空轨迹(部分)
Figure 5. Space-time trajectory of vehicles in the scene without speed guidance (partial)
图 6 本文模型引导车辆时空轨迹(部分)
Figure 6. Space-time trajectory of vehicles by the proposed model (partial)
表 1 拟合系数取值
Table 1. The values of the regression
ki, je 取值 ki, je 取值 k0, 0e -0.679 439 k1, 2e -0.000 020 535 k0, 1e 0.135 273 k1, 3e 5.540 928 5x10-8 k0, 2e 0.015 946 k2, 1e 0.000 083 329 k0, 3e -0.001 189 k2, 2e 0.000 000 937 k1, 0e 0.029 665 k2, 3e -2.479 644x10-8 k2, 0e -0.000 276 k3, 1e -0.000 061 321 k3, 0e 0.148 7x10-6 k3, 2e 0.000 000 304 k1, 1e 0.004 808 k3, 3e -4.467 234x10-9 
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表 2 仿真及模型计算主要参数设置
Table 2. Main parameter settings of simulation and model calculation
参数 取值 参数 取值 速度引导区长度Lg/m 260 舒适加速度a/(m/s2) 2 车辆编队区长度Lp/m 100 舒适减速度d/(m/s2) 1 最大速度Vmax/(m/s) 17 标准车头间距hd/m 15 最小速度Vmin(m/s) 2 标准车头时距ht/s 2 最大加速度amax/(m/s2) 2.5 反应时间td/s 1.5 最大减速度dmax(m/s2) -2.5 仿真时长/s 3 600
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表 3 交叉口现状信号配时方案
Table 3. Status signal timing plan at intersection
第一相位 第二相位 第三相位 第四相位 东西直行 东西左转 北直左 南直左 绿灯时长/s 38 18 28 28 周期/s 121
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表 4 交叉口现状流量
Table 4. Status fiow at intersection
pcu/h 交叉口 东进口 西进口 南进口 北进口 左 直 右 左 直 右 左 直 右 左 直 右 流量 188 374 190 154 344 140 129 244 112 117 271 106 合计 752 638 485 494
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表 5 车队头车识别结果(部分)
Table 5. Recognition results of the leader of the fleet (partial)
序号 头车到达速度引导区时刻/s 头车ID 序号 头车到达速度引导区时刻/s 头车ID 1 36 13 11 202 143 2 49 22 12 212 155 3 78 49 13 216 156 4 93 58 14 224 171 5 107 70 15 276 215 6 122 77 16 287 218 7 125 79 17 309 233 8 147 96 18 329 255 9 166 112 19 348 272 10 194 135 20 353 279
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表 6 车辆行程时间仿真结果
Table 6. Vehicle travel time simulation results
仿真时间/s 行程时间/s 对比/% 无速度引导 本文模型 300 110.8 86.3 -22.11 600 106.4 84.5 -20.58 900 119 90.1 -24.29 1 200 113.4 95.5 -15.78 1 500 113.5 88.4 -22.11 1 800 102.4 99.3 -3.03 2 100 112.5 99.5 -11.56 2 400 101.4 77.2 -23.87 2 700 117 100.1 -14.44 3 000 119.3 95.8 -19.70 3 300 124.2 91.5 -26.33 3 600 95.6 73.3 -23.33 平均 111.3 90.1 -18.93
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表 7 不同饱和状态下运行指标结果对比
Table 7. Comparison of operating index results underdifferent saturation conditions
饱和度 平均行程时间/s 平均延误/s 平均停车次数 无引导 本文模型 无引导 本文模型 无引导 本文模型 0.2 111.3 90.1 39.1 15.2 0.9 0.4 0.4 114.3 97.4 43.1 25.3 1.2 0.8 0.6 246.5 197.7 173.5 137.1 9.6 3.3 0.8 305.7 290.5 251.0 215.0 16.6 4.9
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