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A Framework for Self-Enforced Optimal Interaction Between Connected Vehicles.
- Source :
- IEEE Transactions on Intelligent Transportation Systems; Oct2021, Vol. 22 Issue 10, p6152-6161, 10p
- Publication Year :
- 2021
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15249050
- Volume :
- 22
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Intelligent Transportation Systems
- Publication Type :
- Academic Journal
- Accession number :
- 153761792
- Full Text :
- https://doi.org/10.1109/TITS.2020.2988150