A framework for self-enforced optimal interaction between connected vehicles

Date

2020-05-06

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

IEEE

Department

Type

Article

ISSN

1524-9050

Format

Free to read from

2020-11-12

Citation

Stryszowski 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. 6152-6161

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.

Description

Software Description

Software Language

Github

Keywords

Connected cars, game theory platooning, negotiation, overtake, V2V

DOI

Rights

Attribution-NonCommercial 4.0 International

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Relationships

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