nuScenes Knowledge Graph - A comprehensive semantic representation of traffic scenes for trajectory prediction

Mlodzian, Leon; Sun, Zhigang; Berkemeyer, Hendrik; Monka, Sebastian; Wang, Zixu; Dietze, Stefan; Halilaj, Lavdim; Luettin, Juergen

doi:10.1109/iccvw60793.2023.00011

2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 2023

DOI: 10.1109/iccvw60793.2023.00011

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nuScenes Knowledge Graph - A comprehensive semantic representation of traffic scenes for trajectory prediction

Leon Mlodzian,

Zhigang Sun,

Hendrik Berkemeyer

et al.

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2024

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Cited by 2 publications

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SemanticFormer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction Using Knowledge Graphs

Sun,

Wang,

Halilaj

et al. 2024

IEEE Robot. Autom. Lett.

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SemanticFormer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction Using Knowledge Graphs

Sun,

Wang,

Halilaj

et al. 2024

IEEE Robot. Autom. Lett.

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Integrating Knowledge Graphs into Autonomous Vehicle Technologies: A Survey of Current State and Future Directions

Htun,

Fukuda

2024

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Autonomous vehicles (AVs) represent a transformative innovation in transportation, promising enhanced safety, efficiency, and sustainability. Despite these promises, achieving robustness, reliability, and adherence to ethical standards in AV systems remains challenging due to the complexity of integrating diverse technologies. This survey reviews literature from 2017 to 2023, analyzing over 90 papers to explore the integration of knowledge graphs (KGs) into AV technologies. Our findings indicate that KGs significantly enhance AV systems by providing structured semantic understanding, improving real-time decision-making, and ensuring compliance with regulatory standards. The paper identifies that while KGs contribute to better environmental perception and contextual reasoning, challenges remain in their seamless integration with existing systems and in maintaining processing speed. We also address the ethical dimensions of AV decision-making, advocating for frameworks that prioritize safety and transparency. This review underscores the potential of KGs to address critical challenges in AV technologies, offering a hopeful and optimistic outlook for the development of robust, reliable, and socially responsible autonomous transportation solutions.

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nuScenes Knowledge Graph - A comprehensive semantic representation of traffic scenes for trajectory prediction

Cited by 2 publications

References 48 publications

SemanticFormer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction Using Knowledge Graphs

SemanticFormer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction Using Knowledge Graphs

Integrating Knowledge Graphs into Autonomous Vehicle Technologies: A Survey of Current State and Future Directions

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