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Bayesian Artificial Intelligence-Based Driver for Fully Automated Vehicle with Cognitive Capabilities

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Advances in Human Factors of Transportation (AHFE 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 964))

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Abstract

At automation level 5 as defined by the Society of Automotive Engineers (SAE), a driver will not be in the loop even in a complex driving environment featuring among other challenges, the presence of vehicles with automation levels ranging from 1 (no automation) to 5 (fully automated). This paper defines the safety and ride quality requirements that a fully automated vehicle should meet when operating in a mixed traffic environment featuring vehicles of various automation levels and proposes a Bayesian AI-based driver algorithm as a solution. Design advances that can potentially overcome the safety and ride quality issues are described. Microscopic level data sourced from driving simulator studies are used in applications. Finally, conclusions are presented on the abilities of the Bayesian AI-based driver to meet safety and ride quality criteria while operating in driving environment characterized by uncertainties. The Bayesian AI-based driver is likely to enhance consumer and safety regulator acceptance.

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Acknowledgements

The Ministry of Transportation of Ontario (MTO) and the Natural Sciences and Engineering Research Council of Canada (NSERC) sponsored this research. The views ex-pressed are those of the author.

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Authors and Affiliations

  1. Civil and Environmental Engineering, Carleton University, 1125 Colonel by Drive, Ottawa, ON, K1S5B6, Canada

    Ata Khan

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  1. Ata Khan
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Correspondence to Ata Khan .

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  1. Boldrewood Innovation Campus, University of Southampton, TRG, Southampton, UK

    Neville Stanton

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Khan, A. (2020). Bayesian Artificial Intelligence-Based Driver for Fully Automated Vehicle with Cognitive Capabilities. In: Stanton, N. (eds) Advances in Human Factors of Transportation. AHFE 2019. Advances in Intelligent Systems and Computing, vol 964. Springer, Cham. https://doi.org/10.1007/978-3-030-20503-4_6

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  • DOI: https://doi.org/10.1007/978-3-030-20503-4_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20502-7

  • Online ISBN: 978-3-030-20503-4

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