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A Survey on Knowledge Graph-Based Methods for Automated Driving

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Knowledge Graphs and Semantic Web (KGSWC 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1686))

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Abstract

Deep learning methods have made remarkable breakthroughs in machine learning in general and in automated driving (AD) in particular. However, there are still unsolved problems to guarantee reliability and safety of automated systems, especially to effectively incorporate all available information and knowledge in the driving task. Knowledge graphs (KG) have recently gained significant attention from both industry and academia for applications that benefit by exploiting structured, dynamic, and relational data. The complexity of graph-structured data with complex relationships and inter-dependencies between objects has posed significant challenges to existing machine learning algorithms. However, recent progress in knowledge graph embeddings and graph neural networks allows to applying machine learning to graph-structured data. Therefore, we motivate and discuss the benefit of KGs applied to AD. Then, we survey, analyze and categorize ontologies and KG-based approaches for AD. We discuss current research challenges and propose promising future research directions for KG-based solutions for AD.

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Authors and Affiliations

  1. Bosch Center for AI, Renningen, Germany

    Juergen Luettin, Sebastian Monka & Lavdim Halilaj

  2. Bosch Center for AI, Pittsburgh, PA, USA

    Cory Henson

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  1. Juergen Luettin
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  2. Sebastian Monka
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  3. Cory Henson
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  4. Lavdim Halilaj
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Correspondence to Juergen Luettin .

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  1. EY wavespace/UNIR, Madrid, Spain

    Boris Villazón-Terrazas

  2. Autonomous University of Tamaulipas, Ciudad Victoria, Mexico

    Fernando Ortiz-Rodriguez

  3. Autonomous University of Tamaulipas, Ciudad Victoria, Mexico

    Sanju Tiwari

  4. University of Alcalá, Alcalá de Henares, Spain

    Miguel-Angel Sicilia

  5. Universidad Camilo José Cela, Madrid, Spain

    David Martín-Moncunill

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Luettin, J., Monka, S., Henson, C., Halilaj, L. (2022). A Survey on Knowledge Graph-Based Methods for Automated Driving. In: Villazón-Terrazas, B., Ortiz-Rodriguez, F., Tiwari, S., Sicilia, MA., Martín-Moncunill, D. (eds) Knowledge Graphs and Semantic Web . KGSWC 2022. Communications in Computer and Information Science, vol 1686. Springer, Cham. https://doi.org/10.1007/978-3-031-21422-6_2

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