Acta Geodaetica et Cartographica Sinica ›› 2021, Vol. 50 ›› Issue (11): 1447-1456.doi: 10.11947/j.AGCS.2021.20210259

• Environment Perception for Intelligent Driving • Previous Articles     Next Articles

Key technologies of multi-agent collaborative high definition map construc-tion

CHEN Long1, LIU Kunhua1, ZHOU Baoding2,3, LI Qingquan4,5   

  1. 1. School of Computer Science and Engineering, Sun Yat-sen Univercity, Guangzhou 510006, China;
    2. College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China;
    3. Institute of Urban Smart Transportation & Safety Maintenance, Shenzhen University, Shenzhen 518060, China;
    4. Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China;
    5. MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen 518060, China
  • Received:2021-05-13 Revised:2021-10-31 Published:2021-12-07
  • Supported by:
    The National Key Research and Development Program of China (No. 2018YFB1305002);The Guangdong Natural Science Funds for Distinguished Young Scholar (No. 2021B1515020020);The National Natural Science Foundation of China (Nos. 62006256;42171427);The Key Research and Development Program of Guangzhou (No. 202007050002)

Abstract: The higher the automatic driving degree, the higher requirements of a high definition map. Intelligent high definition maps can provide information for L5 level autonomous vehicles, which is an important direction for the development of high definition maps in the future. According to the current high definition map construction methods, the definition of multi-agent collaborative intelligent high definition map construction is proposed. Its construction framework and key technologies: multi-agent routing for data collection, multi-source heterogeneous integration data fusion and expression, road scene cognition, intelligent high definition map fusion, intelligent high-definition update are studied, and their corresponding appropriate technical schemes are proposed. Besides, the challenges in the further construction process are analyzed.

Key words: high definition map, path planning, road scene understanding, multi-source heterogeneous data processing

CLC Number: