Game-Theoretic Lane-Changing Decision Making and Payoff Learning for Autonomous Vehicles
IEEE Transactions on Vehicular Technology(2022)
Abstract
In this paper, the problem of decision making for autonomous vehicles changing lanes is addressed by formulating multiple games in normal form for pairs of agents. This formulation generates the optimal action for the Ego vehicle at a given state and does not consider global optimality for all agents. The payoff matrices of the games are designed based on a user-defined set of rules. The constant ...
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Key words
Games,Autonomous vehicles,Roads,Neural networks,Q-learning,Vehicle dynamics,Space vehicles
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