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Collaborative decision making for lane-free autonomous driving in the presence of uncertainty

Geronymakis Pavlos, Troullinos Dimitrios, Chalkiadakis Georgios, Papageorgiou Markos

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Year 2022
Type of Item Conference Full Paper
Bibliographic Citation P. Geronymakis, D. Troullinos, G. Chalkiadakis, and M. Papageorgiou, “Collaborative decision making for lane-free autonomous driving in the presence of uncertainty,” in Multi-Agent Systems, EUMAS 2022, vol. 13442, Lecture Notes in Computer Science, Cham, Switzerland: Springer Nature, 2022, pp. 171–187, doi: 10.1007/978-3-031-20614-6_10.
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The recently introduced lane-free traffic paradigm removes the restrictions of the traffic lanes, so that autonomous vehicles can move anywhere laterally across the road’s width. Previous research in this domain has employed the celebrated max-plus message-passing algorithm in order to allow the coordination of all (connected and autonomous) vehicles in the environment. However, when allowing for the realistic perspective that there exist vehicles that are unable or unwilling to communicate with others, the uncertainty introduced renders the aforementioned coordination approach ineffective. To combat this, in this paper we adjust the Max-plus algorithm accordingly so that agents using max-plus for coordination can also observe and take into consideration independent agents via emulated messages. We put forward different methods to form these messages—namely the Maximax, Maximin, Hurwicz, Minimax Regret and Laplace decision-making criteria. Finally, we provide a thorough evaluation of our approach, including a detailed comparison of all criteria used for message-forming.

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