Multi-Vehicle Automated Driving as a Generalized Mixed-Integer Potential Game

Journal article (2020)

Authors

F. Fabiani University of Pisa, Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
S. Grammatico Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
Research Group
Team Bart De Schutter (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2020 F. Fabiani, S. Grammatico
DOI: https://doi.org/10.1109/TITS.2019.2901505
Autonomous vehicles Networked control systems Optimization methods
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Published Date

2020

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Bart De Schutter

Abstract

This paper considers the multi-vehicle automated driving coordination problem. We develop a distributed, hybrid decision-making framework for safe and efficient autonomous driving of selfish vehicles on multi-lane highways, where each dynamics is modeled as a mixed-logical–dynamical system. We formalize the coordination problem as a generalized mixed-integer potential game, seeking an equilibrium solution that generates almost individually optimal mixed-integer decisions, given the safety constraints. Finally, we embed the proposed best-response-based algorithms within the distributed open- and closed-loop control policies.