基于C-V2X的车路协同自动驾驶关键技术与应用

doi:10.11959/j.issn.1000-0801.2023048

Abstract

Abstract:

With the evolution of vehicle-to-everything (V2X) technology, autonomous driving (AD) has entered a new stage of development, called vehicle-infrastructure cooperative autonomous driving (VICAD).Through the integrated complex cyber-physical system formed by the deep integration of “human-vehicle-road-cloud”, cooperative perception, cooperative decision-making and planning, and even cooperative control can be achieved with autonomous vehicles (AV), enhancing the safety of autonomous driving and helping to overcome various complex traffic environments.The concept and overall architecture of the complex cyber-physical system of VICAD was firstly introduced, and a series of typical application scenarios, technical principles, C-V2X performance requirements, and functional and performance requirements of the VICAD system were proposed.It can provide a reference and solution for the deep integration development of intelligent networked vehicles and intelligent transportation in the next stage.

Key words: autonomous driving, C-V2X, connected and automated vehicle, VICAD

Kun WANG, Zhenjiang DONG, Fan YANG, Guyue ZHOU. Key technologies and applications of C-V2X based vehicle-infrastructure cooperative autonomous driving[J]. Telecommunications Science, 2023, 39(3): 45-60.

Figures/Tables 20

References 36

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通信场景描述	有效负荷/byte	发送频率/Hz	最大端到端时延/ms	可靠性	数据速率/ (Mbit·s^-1)	最小通信范围/m
全量高精度协同感知	300～400	10～20	20	90%～99.99%	10	80～350
协同决策控制	300～12 000	10～100	3～20	99.999%	25～1 000	1 000

	道路功能或性能要求	具体指标
交通对象感知定位	类型识别	准确率≥95%
	（机动车、非机动车、行人、障碍物等）	召回率≥95%
	位置精度	3 m（99分位）
		0.5 m（均值要求）
	速度大小精度	4.5 m/s（99分位）
		1.5 m/s（均值）
	速度方向精度	10°（99分位）
	对象预测轨迹3 s最终偏差	<3.5 m
	对象预测轨迹3 s平均偏差	<1.5 m
	路侧对象感知端到端时延（含通信时延）	≤200 ms（99分位）
	数据发送频率	≥10 Hz
交通事件感知定位	事件类型识别	准确率≥95%；召回率≥95%
	定位精度	3 m（99分位）
	事件感知端到端时延（含通信时延）	≤200 ms（99分位）
	数据发送频率	≥10 Hz
红绿灯能力	路侧红绿灯颜色感知准确率	99.999 9%
	故障灯状态识别率	99.999 9%
	红绿灯数据端到端时延	≤200 ms（99分位）
	红绿灯数据发送频率	≥8 Hz
地图要素实时检测能力	交通设备物理位置和属性变更检测	准确率≥99%，召回率≥99%
	地面标识位置和属性变更检测	准确率≥99%，召回率≥99%

序号	可识别事件类型		服务对象
序号	可识别事件类型	I类	Ⅱ类	Ⅲ类
1	交通事故	●	●	●
2	道路施工	●	●	●
3	拥堵事件	●	●	●
4	停止事件	○	●	●
5	逆行事件	○	●	●
6	异常低速/超速事件	○	●	●
7	行人闯入事件	○	○	●
8	抛洒物事件	○	○	●
9	机动车驶离	○	○	●
10	非机动车闯入	○	○	●
11	机动车闯红灯	○	○	●
12	机动车不按导向行驶	○	○	●
13	实线变道	○	○	●
14	不礼让行人	○	○	●
15	机动车占用非机动车道行驶	○	○	●
16	非机动车占用机动车道行驶	○	○	●
17	其他自定义事件	○	○	○
注：“●”表示应具备功能，“○”表示宜具备功能。

类别	场景类别		场景子类别/名称	适用标准
1	自动驾驶地图更新		地图要素变更：交通红绿灯	标准制定中
			地图要素变更：车道线
2	协同感知		路端红绿灯融合感知	YD/T 3978-2021
			静态盲区/遮挡协同感知
			动态盲区/遮挡协同感知
			超视距协同感知
			低速车辆协同感知
			道路遗撒与低矮障碍物协同感知
3	协同决策规划	行为决策	排队决策	标准制定中
			“死车”决策	标准制定中
		行为决策+运动规划	交叉口协调通行	T/CSAE 157-2020
			阻塞绕行	标准制定中
			路口内施工绕行	T/CSAE 157-2020
		路径导航+行为决策+运	合作式代客泊车	T/CSAE 156-2020
		动规划	编队行驶	T/CSAE 157-2020
4	协同控制		控制车辆：5G云代驾	标准制定中
			控制基础设施：优先通行	标准制定中
			控制基础设施：绿波通行	标准制定中

地图更新方式	相对精度/m	实时性	观测连续性	覆盖范围	成本估算/(万元·km^-1)
测绘车地图更新	0.1	—	单点观测	区域全覆盖	千元级别
车端众包地图更新	0.4	天级别	断点重复观测	区域大部分覆盖	无须新增设备投入
路端局部地图更新	0.2	分钟级别	定点连续观测	区域路口覆盖	无须新增设备投入

Key technologies and applications of C-V2X based vehicle-infrastructure cooperative autonomous driving

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地图更新方式	地图更新间隔D	场景遭遇率M	场景成功率P
地图更新方式	地图更新间隔D	场景遭遇率M	条件1R_VICAD=99%	条件2 R_VICAD=99.9%
车端众包地图更新	≥24 h	6.38次/万千米	P_AD变更=90%	P_AD变更=99.8%
路端局部动态地图更新	≤5 min	0.058 7次/万千米（RVICAD=99%条件下）	P_VICAD变更≈99.86%	P_VICAD变更≈99.999%

比较项	车路协同决策规划链路时间D	场景遭遇率M	场景成功率P
比较项	车路协同决策规划链路时间D	场景遭遇率M	条件1	条件2
单车智能决策控制	—	4.5次/万千米	P_{未认知施工}=90%	P_{未认知施工}=99.8%
			R_VICAD=99%	R_VICAD=99.9%
车路协同决策控制	≤3 min	0.027 0次/万千米	P_VICAD施工≈99.87%	P_VICAD施工≈99.999 1%
		(R_VICAD=99.9%条件下)

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