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A Framework and Automotive Application of Collision Avoidance Decision Making
The Swedish National Road and Transport Research Institute, Sweden.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2008 (English)In: Automatica, ISSN 0005-1098, Vol. 44, no 9, 2347-2351 p.Article in journal (Refereed) Published
Abstract [en]

Collision avoidance (CA) systems are applicable for most transportation systems ranging from autonomous robots and vehicles to aircraft, cars and ships. A probabilistic framework is presented for designing and analyzing existing CA algorithms proposed in literature, enabling on-line computation of the risk for faulty intervention and consequence of different actions. The approach is based on Monte Carlo techniques, where sampling-resampling methods are used to convert sensor readings with stochastic errors to a Bayesian risk. The concepts are evaluated using a real-time implementation of an automotive collision mitigation system, and results from one demonstrator vehicle are presented.

Place, publisher, year, edition, pages
Elsevier, 2008. Vol. 44, no 9, 2347-2351 p.
Keyword [en]
Automotive control, Decision support, Decision theory, Collision avoidance, Non-linear filtering, Kalman filter
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-45856DOI: 10.1016/j.automatica.2008.01.016OAI: diva2:266752

© 2008 Elsevier Ltd. All rights reserved.

Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2013-07-22

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Gustafsson, Fredrik
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Automatic ControlThe Institute of Technology
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