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Simdriver ⭐ 11

A responsive driver model for traffic simulations to create exact and closed-loop microscopic traffic scenarios.

Traffic Simulator Q Learning ⭐ 7

We propose a driver modeling process and its evaluation results of an intelligent autonomous driving policy, which is obtained through reinforcement learning techniques. Assuming a MDP decision making model, Q-learning method is applied to simple but descriptive state and action spaces, so that a policy is developed within limited computational load. The driver could perform reasonable maneuvers, like acceleration, deceleration or lane-changes, under usual traffic conditions on a multi-lane high

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