Abstract
The aim of this work was to develop and empirically test different algorithms of a lane-keeping assistance system that supports drivers by means of a tone when the car is about to deviate from its lane. These auditory assistance systems were tested in a driving simulator with its screens shut down, so that the participants used auditory feedback only. Five participants drove with a previously published algorithm that predicted the future position of the car based on the current velocity vector, and three new algorithms that predicted the future position based on the momentary speed and steering angle. Results of a total of 5 h of driving across participants showed that, with extensive practice and knowledge of the system, it is possible to drive on a track with sharp curves for 5 min without leaving the road. Future research should aim to improve the intuitiveness of the auditory feedback.
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Acknowledgements
Pavlo Bazilinskyy and Joost de Winter are involved in the Marie Curie ITN: HFAuto (PITN-GA-2013-605817).
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Bazilinskyy, P., Beaumont, C., van der Geest, X., de Jonge, R., van der Kroft, K., de Winter, J. (2018). Blind Driving by Means of a Steering-Based Predictor Algorithm. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2017. Advances in Intelligent Systems and Computing, vol 597. Springer, Cham. https://doi.org/10.1007/978-3-319-60441-1_45
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DOI: https://doi.org/10.1007/978-3-319-60441-1_45
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