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Ιδρυματικό Αποθετήριο [SANDBOX]
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| URI | http://purl.tuc.gr/dl/dias/B59D20A6-1EC7-43AA-8DEA-5A5C65D13BE5 | - |
| Αναγνωριστικό | https://doi.org/10.48448/pxjq-9b34 | - |
| Γλώσσα | en | - |
| Μέγεθος | 9 pages | en |
| Τίτλος | Collaborative multiagent decision making for lane-free autonomous driving | en |
| Δημιουργός | Troullinos Dimitrios | en |
| Δημιουργός | Τρουλλινος Δημητριος | el |
| Δημιουργός | Chalkiadakis Georgios | en |
| Δημιουργός | Χαλκιαδακης Γεωργιος | el |
| Δημιουργός | Papamichail Ioannis | en |
| Δημιουργός | Παπαμιχαηλ Ιωαννης | el |
| Δημιουργός | Papageorgiou Markos | en |
| Δημιουργός | Παπαγεωργιου Μαρκος | el |
| Εκδότης | International Foundation for Autonomous Agents and Multiagent Systems | en |
| Περιγραφή | The research leading to these results has received funding from the European Research Council under the European Union’s Horizon 2020 Research and Innovation programme/ ERC Grant Agreement n. [833915], project TrafficFluid. | en |
| Περίληψη | This paper addresses the problem of collaborative multi-agent autonomous driving of connected and automated vehicles (CAVs) in lane-free highway scenarios. We eliminate the lane-changing task, i.e., CAVs may be located in any arbitrary lateral position within the road boundaries, hence allowing for better utilization of the available road capacity. As a consequence, vehicles operate in a much more complex environment, and the need for the individual CAVs to select actions that are efficient for the group as a whole is highly desired. We formulate this environment as a multiagent collaboration problem represented via a coordination graph, thus decomposing the problem with local utility functions, based on the interactions between vehicles. We produce a tractable and scalable solution by estimating the joint action of all vehicles via the anytime max-plus algorithm, with local utility functions provided by potential fields, designed to promote collision avoidance. Specifically, the fields have an ellipsoid form that is most suitable for lane-free highway environments. This novel use of max-plus with potential fields gives rise to a coordinated control policy that exploits only local information specific to each CAV. Our experimental evaluation confirms the effectiveness of our approach: lane-free movement allows for increased traffic flow rates, and vehicles are able to achieve speeds that are both high and close to their desired ones, even in demanding environments with high traffic flow. | en |
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Τύπος | Conference Full Paper | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
| Ημερομηνία | 2021-07-06 | - |
| Ημερομηνία Δημοσίευσης | 2021 | - |
| Θεματική Κατηγορία | Autonomous driving | en |
| Θεματική Κατηγορία | Lane-free traffic | en |
| Θεματική Κατηγορία | Max-plus algorithm | en |
| Βιβλιογραφική Αναφορά | D. Troullinos, G. Chalkiadakis, I. Papamichail, and M. Papageorgiou, "Collaborative multiagent decision making for lane-free autonomous driving," in 20th Int. Conf. Autonomous Agents and Multiagent Systems, 2021, pp. 1335-1343. doi: 10.48448/pxjq-9b34 | en |
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