Abstract
In this paper, we consider the problem of designing in-vehicle driver-assist systems that warn or override the driver to prevent collisions with a guaranteed probability. The probabilistic nature of the problem naturally arises from many sources of uncertainty, among which the behavior of the surrounding vehicles and the response of the driver to on-board warnings. We formulate this problem as a control problem for uncertain systems under probabilistic safety specifications and leverage the structure of the application domain to reach computationally efficient implementations. Simulations using a naturalistic data set show that the empirical probability of safety is always within 5% of the theoretical value in the case of direct driver override. In the case of on-board warnings, the empirical value is more conservative due primarily to drivers decelerating more strongly than requested. However, the empirical value is greater than or equal to the theoretical value, demonstrating a clear safety benefit.
Original document
The different versions of the original document can be found in:
- https://doi.org/10.1109/tase.2015.2499221 under the license publisher-specific, author manuscript: http://www.ieee.org/publications_standards/publications/rights/ieeecopyrightform.pdf
- https://orcid.org/0000-0001-8695-1891,
- https://orcid.org/0000-0003-1866-6970,
- https://orcid.org/0000-0001-6472-8576 under the license http://creativecommons.org/licenses/by-nc-sa/4.0/
Document information
Published on 01/01/2015
Volume 2015, 2015
DOI: 10.1109/tase.2015.2499221
Licence: Other
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