Abstract
Although technological developments in experimental autonomous vehicles are impressive, industry experts are realizing that if automation in driving is to gain acceptance by drivers and to become a reality in real world driving environment, new generation driving assistance system (NDAS) shaped by human factors is necessary since it will provide transition to self-driving vehicles. The paper consists of five parts. In part one, the balance of demand pull vs. technology push is introduced and part two reports developments in driving assistance technologies. In the third part, transitions between human control and automation are described as high level “design” challenges. In part four, a Bayesian Artificial Intelligence (AI) model is presented that enables the NDAS to perform its functions. An example application based on driving simulator data from distracted driving study is presented to illustrate advanced driving assistance capabilities. Finally, in part five, conclusions are presented on how human factors-guided NDAS design is likely to enhance driver acceptance.
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Acknowledgments
This paper is based on research that was sponsored by the Natural Sciences and Engineering Research Counsel of Canada (NSERC) and the Ministry of Transportation of Ontario (MTO). The views expressed are those of the author.
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Khan, A. (2017). Modelling Human Factors for Advanced Driving Assistance System Design. In: Stanton, N., Landry, S., Di Bucchianico, G., Vallicelli, A. (eds) Advances in Human Aspects of Transportation. Advances in Intelligent Systems and Computing, vol 484. Springer, Cham. https://doi.org/10.1007/978-3-319-41682-3_1
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DOI: https://doi.org/10.1007/978-3-319-41682-3_1
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