Key Technologies and Application Prospects for High-definition Map in Off-road Environments

doi:10.12382/bgxb.2023.0854

Abstract

Abstract:

With the development of technologies such as artificial intelligence, the unmanned driving technology has emerged as the times require, and more and more unmanned equipment has also been put into combat applications. In the complex off-road environments, a high-definition map can provide rich prior information for unmanned ground vehicles, assist the unmanned ground vehicles in environmental perception, path planning and decision-making, and improve the off-road mobility of unmanned ground vehicles. This paper analyzes the research status of the standardization, construction and application of high-precision map, puts forward the research objectives and technical systems of high-precision map in off-road environments for the autonomous maneuvering tasks of unmanned vehicles in off-road environments, summarizes the basic theories and key technologies of high-precision map in off-road environments, and looks forward to the application and development of high-precision map in off-road environments, which provides a reference for the convenient application of high-precision map in unmanned driving.

Key words: off-road environments, high-definition map, unmanned ground vehicle, autonomous navigation

CLC Number:

TJ301

LI Zhaodong, ZHAO Xijun, YANG Tingting, QI Xiaolong, ZHOU Changyi, ZHANG Liming. Key Technologies and Application Prospects for High-definition Map in Off-road Environments[J]. Acta Armamentarii, 2023, 44(S2): 1-11.

Figures/Tables 11

Fig.1 Layered architecture of autonomous navigation system

Table 1 The difference between high-definition map and traditional electronic map

地图种类	服务对象	精度	要素和属性
高精地图	无人车辆	亚米级	详细的车道模型(曲率、坡度、航向、限高、限重、限宽)、道路部件、定位地物等
传统电子地图	人	米级	道路、兴趣点

Fig.2 Road structure and intersection representation of OpenDRIVE

Table 2 Advantages and disadvantages of data collection methods

数据来源	优势	劣势
众包采集	高效率、高实时性、高适应性	成本高、数据后处理代价较大
开源数据集	数据质量高、无需后处理	数据实时性差、针对性较差
MMS	数据可定制、成本较低、可针对特殊场景	地图覆盖范围小、数据实时性较差、数据采集耗时较多

Fig.3 Schematic diagram of 3D point cloud map

Fig.4 Generating road networks based on iterative growth(Green represents the road network structure)[37]

Fig.5 Data fusion of space-air-ground

Fig.6 Effect of map feature extraction and classification

Fig.7 Framework for real-time point clouds

Fig.8 Effect of UAV 3D true color point cloud

Fig.9 Autonomous navigation system for unmanned vehicles

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