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https://hdl.handle.net/123456789/742| Τύπος: | Άρθρο σε περιοδικό |
| Τίτλος: | Deep reinforcement-learning-based driving policy for autonomous road vehicles |
| Συγγραφέας: | [EL] Μακαντάσης, Κων/νος[EN] Makantasis, Konstantinos [EL] Κοντορινάκη, Μαρία[EN] Kontorinaki, Maria [EL] Νικολός, Ιωάννης[EN] Nikolos, Ioannis |
| Ημερομηνία: | 15/10/2019 |
| Περίληψη: | In this work, the problem of path planning for an autonomous vehicle that moves on a freeway is considered. The most common approaches that are used to address this problem are based on optimal control methods, which make assumptions about the model of the environment and the system dynamics. On the contrary, this work proposes the development of a driving policy based on reinforcement learning. In this way, the proposed driving policy makes minimal or no assumptions about the environment, since a priori knowledge about the system dynamics is not required. Driving scenarios where the road is occupied both by autonomous and manual driving vehicles are considered. To the best of the authors’ knowledge, this is one of the first approaches that propose a reinforcement learning driving policy for mixed driving environments. The derived reinforcement learning policy, firstly, is compared against an optimal policy derived via dynamic programming, and, secondly, its efficiency is evaluated under realistic scenarios generated by the established SUMO microscopic traffic flow simulator. Finally, some initial results regarding the effect of autonomous vehicles’ behaviour on the overall traffic flow are presented. |
| Γλώσσα: | Αγγλικά |
| Σελίδες: | 12 |
| DOI: | 10.1049/iet-its.2019.0249 |
| ISSN: | 1751-956X |
| Θεματική κατηγορία: | [EL] Άλλες Επιστήμες Μηχανικού και Τεχνολογίες[EN] Other Engineering and Technologies |
| Λέξεις-κλειδιά: | autonomous vehicles; Reinforcement learning; Driving policy |
| Κάτοχος πνευματικών δικαιωμάτων: | © The Institution of Engineering and Technology |
| Διατίθεται ανοιχτά στην τοποθεσία: | https://arxiv.org/pdf/1907.05246.pdf |
| Ηλεκτρονική διεύθυνση του τεκμηρίου στον εκδότη: | https://digital-library.theiet.org/content/journals/10.1049/iet-its.2019.0249 |
| Ηλεκτρονική διεύθυνση περιοδικού: | https://digital-library.theiet.org/content/journals/iet-its |
| Τίτλος πηγής δημοσίευσης: | IET Intelligent Transport Systems |
| Τεύχος: | 1 |
| Τόμος: | 14 |
| Σελίδες τεκμηρίου (στην πηγή): | 13-24 |
| Σημειώσεις: | This research is implemented through and has been financed by the Operational Program ”Human Resources Development, Education and Lifelong Learning” and is co-financed by the European Union (European Social Fund) and Greek national funds. |
| Εμφανίζεται στις συλλογές: | Ερευνητικές ομάδες |
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