Stryszowski, MarcinLongo, StefanoD'Alessandro, DarioVelenis, EfstathiosForostovsky, GregoryManfredi, Sabato2020-11-122020-11-122020-05-06Stryszowski S, Longo S, D'Alessandro D, et al., (2020) A framework for self-enforced optimal interaction between connected vehicles. IEEE Transactions on Intelligent Transportation Systems, Volume 22, Number 10, October 2021, pp. 6152-61611524-9050https://doi.org/10.1109/TITS.2020.2988150https://dspace.lib.cranfield.ac.uk/handle/1826/15995This paper proposes a decision-making framework for Connected Autonomous Vehicle interactions. It provides and justifies algorithms for strategic selection of control references for cruising, platooning and overtaking. The algorithm is based on the trade-off between energy consumption and time. The consequent cooperation opportunities originating from agent heterogeneity are captured by a game-theoretic cooperative-competitive solution concept to provide a computationally feasible, self-enforced, cooperative traffic management framework.enAttribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/Connected carsgame theory platooningnegotiationovertakeV2VArticle28788447