A Study on AI-based Approaches for High-Level Decision Making in Highway Autonomous Driving

Résumé : Autonomous driving relies on a wide range of domains of research. It faces rapid technological and theoretical advances, with various methods and process developments. For the interest of the high-level decision making subpart of autonomous vehicle architecture, the previous states of the art report a vast literature, from traditional mobile robotics to human-modelling approaches. The objective of this paper is to survey the current and major algorithms in the specific field of artificial intelligence for autonomous vehicles. Such systems are particularly suited for high-level decision making since they must, by definition, be able to perceive and react to their environment in order to reach given objectives. The scope is reduced to highway driving applications, considering individual, collective, and cooperative decisions. Strengths and limitations of the reviewed methods are compared, with respect to the structure and constraints of the studied driving situations. Open questions are proposed as a reflection towards the next generation of decisionmakers for autonomous vehicles.
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Communication dans un congrès
2017 IEEE International Conference on Systems, Man, and Cybernetics, Oct 2014, Bannf, Canada. Institute of Electrical and Electronics Engineers - IEEE, 2017 IEEE International Conference on Systems, Man, and Cybernetics, pp. 3671 - 3676, 2017, 〈10.1109/SMC.2017.8123203〉
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Soumis le : vendredi 22 décembre 2017 - 10:31:58
Dernière modification le : samedi 23 décembre 2017 - 01:11:37

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Laurène Claussmann, Marc Revilloud, Sébastien Glaser, Dominique Gruyer. A Study on AI-based Approaches for High-Level Decision Making in Highway Autonomous Driving. 2017 IEEE International Conference on Systems, Man, and Cybernetics, Oct 2014, Bannf, Canada. Institute of Electrical and Electronics Engineers - IEEE, 2017 IEEE International Conference on Systems, Man, and Cybernetics, pp. 3671 - 3676, 2017, 〈10.1109/SMC.2017.8123203〉. 〈hal-01671298〉

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