Abstract
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.
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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ahmadzadeh, H., Masehian, E.: Fuzzy coordination graphs and their application in multi-robot coordination under uncertainty. In: 2014 Second RSI/ISM International Conference on Robotics and Mechatronics (ICRoM), pp. 345–350. IEEE (2014)
Albrecht, S.V., Stone, P.: Autonomous agents modelling other agents: a comprehensive survey and open problems. Artif. Intell. 258, 66–95 (2018)
Aldea, C., Olariu, C.: Selecting the optimal software solution under conditions of uncertainty. Procedia Soc. Behav. Sci. 109, 333–337 (2014)
Guestrin, C., Koller, D., Parr, R.: Multiagent planning with factored MDPS. In: Advances in Neural Information Processing Systems, vol. 14. MIT Press (2001)
Hurwicz, L.: Some specification problems and applications to econometric models. Econometrica 19(3), 343–344 (1951)
Karafyllis, I., Theodosis, D., Papageorgiou, M.: Two-dimensional cruise control of autonomous vehicles on lane-free roads. In: 60th IEEE Conference on Decision and Control, pp. 2683–2689. CDC (2021)
Kok, J.R., Vlassis, N.: Collaborative multiagent reinforcement learning by payoff propagation. J. Mach. Learn. Res. 7, 1789–1828 (2006)
Larbani, M.: Non cooperative fuzzy games in normal form: a survey. Fuzzy Sets Syst. 160(22), 3184–3210 (2009)
Li, M., Yang, W., Cai, Z., Yang, S., Wang, J.: Integrating decision sharing with prediction in decentralized planning for multi-agent coordination under uncertainty. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence, pp. 450–456. IJCAI (2019)
Mulla, A.K., Joshi, A., Chavan, R., Chakraborty, D., Manjunath, D.: A microscopic model for lane-less traffic. IEEE Trans. Control Netw. Syst. 6(1), 415–428 (2019)
Papageorgiou, M., Mountakis, K.S., Karafyllis, I., Papamichail, I., Wang, Y.: Lane-free artificial-fluid concept for vehicular traffic. Proc. IEEE 109(2), 114–121 (2021)
Pérez-Galarce, F., Álvarez Miranda, E., Candia-Vejar, A., Toth, P.: On exact solutions for the minmax regret spanning tree problem. Comput. Oper. Res. 47, 114–122 (2014)
Troullinos, D., Chalkiadakis, G., Papamichail, I., Papageorgiou, M.: Collaborative multiagent decision making for lane-free autonomous driving. In: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS, pp. 1335–1343 (2021)
Troullinos, D., Chalkiadakis, G., Samoladas, V., Papageorgiou, M.: Max-sum with quadtrees for decentralized coordination in continuous domains. In: Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22, pp. 518–526. International Joint Conferences on Artificial Intelligence Organization (2022)
Wald, A.: Statistical decision functions which minimize the maximum risk. Ann. Math. 46(2), 265–280 (1945)
Yanumula, V.K., Typaldos, P., Troullinos, D., Malekzadeh, M., Papamichail, I., Papageorgiou, M.: Optimal path planning for connected and automated vehicles in lane-free traffic. In: 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), pp. 3545–3552 (2021)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Geronymakis, P., Troullinos, D., Chalkiadakis, G., Papageorgiou, M. (2022). Collaborative Decision Making for Lane-Free Autonomous Driving in the Presence of Uncertainty. In: Baumeister, D., Rothe, J. (eds) Multi-Agent Systems. EUMAS 2022. Lecture Notes in Computer Science(), vol 13442. Springer, Cham. https://doi.org/10.1007/978-3-031-20614-6_10
Download citation
DOI: https://doi.org/10.1007/978-3-031-20614-6_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-20613-9
Online ISBN: 978-3-031-20614-6
eBook Packages: Computer ScienceComputer Science (R0)