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

Filippo Fabiani, Sergio Grammatico

Research output: Contribution to journalArticleScientificpeer-review

42 Citations (Scopus)
193 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)1064-1073
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number3
Publication statusPublished - 2020

Bibliographical note

Accepted Author Manuscript


  • Autonomous vehicles
  • networked control systems
  • optimization methods


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