基于高精地图的超高速公路虚拟轨道系统

doi:10.13229/j.cnki.jdxbgxb.20210974

Abstract

Abstract:

To improve the safety of vehicles driving on the superhighway， a virtual track system model of the superhighway based on high precision map is established and analyzed. The virtual track system is composed of high precision map subsystem， positioning subsystem， cloud server subsystem and track keeping subsystem. When the autonomous vehicle is driving on the virtual track， the frequency of the vehicle positioning information will affect the response speed of the vehicle. The minimum positioning return frequency is calculated based on the constraint that the vehicle does not deviate from the virtual track and the lane change safety.When the autonomous vehicle is running on the virtual track， the frequency of vehicle positioning information return affects the response speed of the vehicle. The minimum positioning return frequency is calculated based on the constraint that the vehicle does not deviate from the virtual track and the safety of lane change. If the angle between the center line of the body and the tangent line of the track and the sum of the deflection angle of the front wheel or the lateral deviation distance exceeds the threshold value， the vehicle may deviate from the track， which will trigger the track deviation warning system， and the vehicle will take the maximum safe deflection angle of the front wheel as the reference to the corrected driving trajectory. The research results show that when the vehicle speed is 100， 120， 140， 160， 180 km/h， the system positioning and return frequency is kept above 49， 58， 68， 78， 87 Hz can ensure the vehicle running in the virtual track.

Key words: engineering of communications and transportation system, high precision map, superhighway, virtual track, automatic driving

CLC Number:

U491

Yong-ming HE,Shi-sheng CHEN,Jia FENG,Ya-nan WAN. Superhighway virtual track system based on high precision map[J].Journal of Jilin University(Engineering and Technology Edition), 2023, 53(7): 2016-2028.

Figures/Tables 18

Table 1

Table 2

Table 3

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

Fig.10

Table 4

Table 5

Table 6

Maximum steering wheel angle at differentspeeds βmax"

$φ h$	超一级高速公路/（km·h^-1）			超二级高速公路/（km·h^-1）			超三级高速公路/（km·h^-1）
$φ h$	140	120	100	160	140	120	180	160	140
$0.3$	2.02	2.75	3.96	1.55	2.02	2.75	1.22	1.55	2.02
$0.5$	3.37	4.59	6.62	2.58	3.37	4.59	2.04	2.58	3.37

Table 6

Fig.11

Table 7

Track departure warning strategy"

$θ$	$λ 、 β$	$d$	是否修正
$θ = 0$	—	$d 1 > 0, d 2 < 0$	否
		$d 1 > 0, d 2 > 0$	向左修正
		$d 1 < 0, d 2 < 0$	向右修正
$θ > 0$	1. $λ > 0$ ， $β < 0$ 2. $λ < 0$ ， $β > 0$	$d 1 > 0, d 2 < 0$	1?向右修正；2?向左修正
		$d 1 > 0, d 2 > 0$	1?向右修正；2?向右修正
		$d 1 < 0, d 2 < 0$	1?向左修正；2?向左修正
$θ < 0$	1. $λ > 0$ ， $β < 0$ 2. $λ < 0$ ， $β > 0$	$d 1 > 0, d 2 < 0$	1?向左修正；2?向右修正
		$d 1 > 0, d 2 > 0$	1?向右修正；2?向右修正
		$d 1 < 0, d 2 < 0$	1?向左修正；2?向左修正

Table 7

References 23

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超高速公路等级	设计速度/（km·h^-1）
超一级	100、120、140
超二级	120、140、160
超三级	140、160、180

特征	解释
高精度	高精地图精度比传统地图高，高精地图的相对精度可以达到10 cm左右，能够满足无人驾驶的需求；高精地图会提供精准的道路环境信息和车道预测信息，不易受环境、天气、温度等影响。
实时性	高精地图采用实时通信技术，地图信息更新速度很快，能够及时更新道路信息，以保证车辆实时感知交通动态环境信息。按照更新频率可将所有高精地图数据划分为四类^［10］，如表3所示。
属性信息、语义信息	高精地图完整记录了道路的3D属性信息、拓扑关系和路况信息。包括车道的具体属性信息（车道等级、车道宽度、车道功能等），交通基础设施信息（信号灯位置、标志标线、护栏等），周边环境信息（包括路侧建筑物、绿化带等）等静态信息，还有信号配时、机动车、行人和非机动车位置等动态信息^［11］。

数据类型	更新频率	内容属性
持续静态数据	1个月	主要是道路网络、定位数据（路边环境等）等
瞬时静态数据	1 h	主要是路侧的基础设施的信息，如交通标识和路标
瞬时动态数据	1 min	主要是红绿灯的相位、交通拥堵等实时路况信息
高度动态数据	1 s	主要是车辆、行人等交通参与者的实时状态数据

项目	超一级高速公路速度/（km·h^-1）			超二级高速公路速度/（km·h^-1）			超三级高速公路速度/（km·h^-1）
项目	140	120	100	160	140	120	180	160	140
最小半径一般值/m	1450	1000	700	1850	1450	1000	2350	1850	1450
最长更新时间/s	0.4379	0.4243	0.4260	0.4328	0.4379	0.4243	0.4336	0.4328	0.4379
最小更新频率/Hz	2.28	2.36	2.35	2.31	2.28	2.36	2.32	2.31	2.29

项目	超一级高速公路速度/（km·h^-1）			超二级高速公路速度/（km·h^-1）			超三级高速公路速度/（km·h^-1）
项目	140	120	100	160	140	120	180	160	140
最长更新时间/s	0.015	0.017	0.021	0.013	0.015	0.017	0.011	0.013	0.015
最小更新频率/Hz	67.53	57.88	48.24	77.18	67.53	57.88	86.82	77.18	67.53

Superhighway virtual track system based on high precision map

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