A framework for self-enforced optimal interaction between connected vehicles - Stryszowski, Marcin; Longo, Stefano; D'Alessandro, Dario; Velenis, Efstathios; Forostovsky, Gregory; Manfredi, Sabato (IEEE, 2020)
This 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.
Keywords: Connected cars; game theory platooning; negotiation; overtake; V2V