Autonomous vehicle-target assignment: A game-theoretical formulation

Gürdal Arslan*, Jason R. Marden, Jeff S. Shamma

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

250 Scopus citations

Abstract

We consider an autonomous vehicle-target assignment problem where a group of vehicles are expected to optimally assign themselves to a set of targets. We introduce a gametheoretical formulation of the problem in which the vehicles are viewed as self-interested decision makers. Thus, we seek the optimization of a global utility function through autonomous vehicles that are capable of making individually rational decisions to optimize their own utility functions. The first important aspect of the problem is to choose the utility functions of the vehicles in such a way that the objectives of the vehicles are localized to each vehicle yet aligned with a global utility function. The second important aspect of the problem is to equip the vehicles with an appropriate negotiation mechanism by which each vehicle pursues the optimization of its own utility function. We present several design procedures and accompanying caveats for vehicle utility design. We present two new negotiation mechanisms, namely, "generalized regret monitoring with fading memory and inertia" and "selective spatial adaptive play," and provide accompanying proofs of their convergence. Finally, we present simulations that illustrate howvehicle negotiations can consistently lead to near-optimal assignments provided that the utilities of the vehicles are designed appropriately.

Original languageEnglish (US)
Pages (from-to)584-596
Number of pages13
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume129
Issue number5
DOIs
StatePublished - Sep 1 2007

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications

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