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Paper FR-EA-T40.1

De Las Heras Molins, Pau (Universitat Politècnica de Catalunya - BarcelonaTech (UPC)), Roy-Almonacid, Eric (Universitat Politècnica de Catalunya), Lee, Dong Ho (The University of Texas at Austin), Peters, Lasse (Delft University of Technology), Fridovich-Keil, David (The University of Texas at Austin), Bakirtzis, Georgios (Telecom Paris & Institut Polytechnique de Paris)

Approximate Solutions to Games of Ordered Preference

Scheduled for presentation during the Regular Session "S40b-Cooperative and Connected Autonomous Systems" (FR-EA-T40), Friday, November 21, 2025, 13:30−13:50, Cooleangata 4

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Keywords Multi-vehicle Coordination for Autonomous Fleets in Urban Environments, Cooperative Driving Systems and Vehicle Coordination in Multi-vehicle Scenarios

Abstract

Autonomous vehicles must balance ranked objectives, such as minimizing travel time, ensuring safety, and coordinating with traffic. Games of ordered preference effectively model these interactions but become computationally intractable as the time horizon, number of players, or number of preference levels increase. While receding horizon frameworks mitigate long-horizon intractability by solving sequential shorter games, often warm-started, they do not resolve the complexity growth inherent in existing methods for solving games of ordered preference. This paper introduces a solution strategy that avoids excessive complexity growth by approximating solutions using lexicographic iterated best response (IBR) in receding horizon, termed "lexicographic IBR over time." Lexicographic IBR over time uses past information to accelerate convergence. We demonstrate through simulated traffic scenarios that lexicographic IBR over time efficiently computes approximate-optimal solutions for receding horizon games of ordered preference, converging towards generalized Nash equilibria.

 

 

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