基于车路协同环境的信号交叉口车速引导方法

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。
- 交通工程 /
- 信号交叉口 /
- 车速引导 /
- 改进跟驰模型 /
- 车路协同
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.
- traffic engineering /
- signalized intersection /
- vehicle speed guidance /
- improved car-following model /
- vehi cle-infrastructure cooperation

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图 1 分区控制示意图

Figure 1. Schematic diagram of zone control

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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

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图 3 车速引导算法逻辑

Figure 3. Speed guidance algorithm logi

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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

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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)

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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)

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图 7 车辆总燃油消耗量对比

Figure 7. Comparison of total vehicle fuel consumption

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图 8 最大排队长度对比

Figure 8. Comparison of the maximum queue length

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图 9 车辆延误对比

Figure 9. Comparison of vehicle delays

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表 1 拟合系数取值

Table 1. The values of the regression

k_{i, j}^e	取值	k_{i, j}^e	取值
k_{0, 0}^e	-0.679 439	k_{1, 2}^e	-0.000 020 535
k_{0, 1}^e	0.135 273	k_{1, 3}^e	5.540 928 5x10^-8
k_{0, 2}^e	0.015 946	k_{2, 1}^e	0.000 083 329
k_{0, 3}^e	-0.001 189	k_{2, 2}^e	0.000 000 937
k_{1, 0}^e	0.029 665	k_{2, 3}^e	-2.479 644x10^-8
k_{2, 0}^e	-0.000 276	k_{3, 1}^e	-0.000 061 321
k_{3, 0}^e	0.148 7x10^-6	k_{3, 2}^e	0.000 000 304
k_{1, 1}^e	0.004 808	k_{3, 3}^e	-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L_g/m	260	舒适加速度a/(m/s²)	2
车辆编队区长度L_p/m	100	舒适减速度d/(m/s²)	1
最大速度V_max/(m/s)	17	标准车头间距h_d/m	15
最小速度V_min(m/s)	2	标准车头时距h_t/s	2
最大加速度a_max/(m/s²)	2.5	反应时间t_d/s	1.5
最大减速度d_max(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
交叉口	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/%
仿真时间/s	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
饱和度	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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