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- W2895923634 abstract "This paper studies the decision making problem of autonomous vehicles in traffic. We model the interaction between an autonomous vehicle and the environment as a stochastic Markov decision process (MDP) and consider the driving style of an experienced driver as the target to be learned. The road geometry is taken into consideration in the MDP model in order to incorporate more diverse driving styles. By designing the reward function of the MDP, the desired, driving behavior of the autonomous vehicle is obtained using reinforcement learning. Simulated results demonstrate the desired driving behaviors of an autonomous vehicle." @default.
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- W2895923634 date "2018-06-01" @default.
- W2895923634 modified "2023-10-14" @default.
- W2895923634 title "Highway Traffic Modeling and Decision Making for Autonomous Vehicle Using Reinforcement Learning" @default.
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- W2895923634 doi "https://doi.org/10.1109/ivs.2018.8500675" @default.
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