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Max-sum with quadtrees for continuous DCOPs with application to lane-free autonomous driving

Troullinos Dimitrios, Chalkiadakis Georgios, Samoladas Vasilis, Papageorgiou Markos

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URI: http://purl.tuc.gr/dl/dias/70F3D1B4-6025-4AB4-8647-4D09B99A33C1
Year 2022
Type of Item Conference Full Paper
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Bibliographic Citation D. Troullinos, G. Chalkiadakis, V. Samoladas, and M. Papageorgiou, “Max-sum with quadtrees for continuous DCOPs with application to lane-free autonomous driving,” in Proc. 21st Int. Conf. Autonomous Agents and Multiagent Systems (AAMAS 2022), pp. 1741–1743, May 2022.
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Summary

In this paper we put forward a novel extension of the classic Max-Sum algorithm to the framework of Continuous Distributed Constrained Optimization Problems (Continuous DCOPs), in which we model the exchanged messages by means of a popular geometric algorithm, Quadtrees. As such, the discretization process is dynamic and embedded in the internal Max-Sum operations (addition and marginal maximization). We apply our Max-Sum with Quadtrees approach to Lane-Free Autonomous Driving in a highway populated with vehicles. Our experimental evaluation verifies the efficiency of our approach in this challenging dynamic coordination domain, demonstrating its superior performance with respect to the standard Max-Sum algorithm.

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