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Application and Prospect of Knowledge Graph in Unmanned Vehicle Field

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Bio-Inspired Computing: Theories and Applications (BIC-TA 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2062))

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Abstract

With the rapid development of unmanned vehicle technology, unmanned vehicle plays an increasingly important role in related fields, which is of great significance to the future development of intelligent transportation. In order to break through the bottleneck of the intelligent degree of existing unmanned vehicles, unmanned vehicle driving technology based on knowledge graph has become one of the development trends. Firstly, this paper gives a brief overview of the decision-making process of unmanned vehicles, and introduces the basic principles and related concepts of unmanned vehicle technology based on knowledge graph. Then the application of knowledge graph in intelligent decision-making of unmanned vehicle is introduced, including target recognition, semantic segmentation, target trajectory prediction and scene understanding. Then an automatic driving decision system based on knowledge graph is proposed. Finally, the future development of intelligent decision-making of unmanned vehicles based on knowledge graph is prospected, and various possibilities of its future development are discussed.

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Acknowledgements

This paper was funded by the National Natural Science Foundation of China (72101033 and 71831001), the Beijing Key Laboratory of Intelligent Logistics Systems (BZ0211), the Canal Plan-Youth Top-Notch Talent Project of Beijing Tongzhou District (YHQN2017014), the Scheduling Model and Method for Large-scale Logistics Robot E-commerce Picking System based on Deep Reinforcement Learning (KZ202210037046), the Fundamental Research Funds for the Central Universities No.2015JBM125 and the Beijing Intelligent Logistics System Collaborative Innovation Center (BILSCIC-2018KF-01).

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Authors and Affiliations

  1. School of Information, Beijing Wuzi University, Beijing, 101149, China

    Yi-ting Shen & Jun-tao Li

  2. Beijing Key Laboratory of Intelligent Logistics System, Beijing, 101149, China

    Yi-ting Shen & Jun-tao Li

Authors
  1. Yi-ting Shen
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  2. Jun-tao Li
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Correspondence to Jun-tao Li .

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Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  2. Central South University, Changsha, China

    Yong Wang

  3. Huazhong University of Science and Technology, Wuhan, China

    Jianqing Lin

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Shen, Yt., Li, Jt. (2024). Application and Prospect of Knowledge Graph in Unmanned Vehicle Field. In: Pan, L., Wang, Y., Lin, J. (eds) Bio-Inspired Computing: Theories and Applications. BIC-TA 2023. Communications in Computer and Information Science, vol 2062. Springer, Singapore. https://doi.org/10.1007/978-981-97-2275-4_18

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  • DOI: https://doi.org/10.1007/978-981-97-2275-4_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-2274-7

  • Online ISBN: 978-981-97-2275-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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