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- W2150668489 abstract "Dynamic collaborative driving involves the motion coordination of multiple vehicles using shared information from vehicles instrumented to perceive their surroundings in order to improve road usage and safety. A basic requirement of any vehicle participating in dynamic collaborative driving is longitudinal control. Without this capability, higher-level coordination is not possible. This paper focuses on the problem of longitudinal motion control. A detailed nonlinear longitudinal vehicle model which serves as the control system design platform is used to develop a longitudinal adaptive control system based on Monte Carlo reinforcement learning. The results of the reinforcement learning phase and the performance of the adaptive control system for a single automobile as well as the performance in a multi-vehicle platoon is presented." @default.
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- W2150668489 date "2008-06-01" @default.
- W2150668489 modified "2023-09-27" @default.
- W2150668489 title "Reinforcement learning of adaptive longitudinal vehicle control for dynamic collaborative driving" @default.
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- W2150668489 doi "https://doi.org/10.1109/ivs.2008.4621222" @default.
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