An automatic driving decision-making method for road conditions of cross-sea bridges
A cross-sea bridge and automatic driving technology, applied in the direction of neural learning methods, external condition input parameters, biological neural network models, etc., can solve the difficulty of taking into account the complex and changeable environmental state transfer, and cannot satisfy the real-time performance of automatic driving vehicles in complex environments and accuracy to ensure applicability and stability
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[0040] The present invention will be further described below in conjunction with specific embodiments. The following examples are only used to illustrate the technical solutions of the present invention more clearly, and cannot be used to limit the protection scope of the present invention.
[0041] As mentioned above, the existing autonomous driving decision-making technology is difficult to take into account the state transition of complex and changeable environments, and cannot meet the real-time and accuracy of autonomous vehicles for complex environments.
[0042] In order to solve the above technical problems, the present invention provides an automatic driving decision-making method oriented to the road conditions of a cross-sea bridge. Implement a meta-reinforcement learning-based decision-making method for autonomous driving. Meta-reinforcement learning combines meta-learning and reinforcement learning to enable agents to quickly learn new tasks, especially for compl...
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