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Simulation Studies of the Hybrid Human-Fuzzy Controller for Path Tracking of an Autonomous Vehicle

机译:混合动力模糊控​​制器在自动驾驶汽车路径跟踪中的仿真研究

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Human intelligence and experience help them in making a decision and recognize a pattern. This ability enables the driver to take action even in an unexpected situation. The hybrid integration between human intelligence/experience and machine controller able to improve the autonomous vehicle path tracking capability. The path tracking capability is the main concern of the autonomous vehicle. The Fuzzy developed from the experiment's data. The experiments (human navigation experiments) used to gather the appropriate data from humans while controlling the buggy car. Data then use to develop the membership functions for inputs and output of the Fuzzy controller. The simulation uses to study the performance of the Fuzzy controller. The recorded path tracking error from the simulations for the right and left turn maneuver is 9 m and 7.5 m, respectively.
机译:人类的智力和经验可以帮助他们做出决定并识别模式。此功能使驾驶员即使在意外情况下也可以采取措施。人工智能/经验与机器控制器之间的混合集成能够提高自主车辆路径跟踪能力。路径跟踪能力是自动驾驶汽车的主要关注点。 Fuzzy是根据实验数据发展而来的。这些实验(人类导航实验)用于在控制越野车的同时从人类那里收集适当的数据。然后,数据用于开发模糊控制器输入和输出的隶属函数。该仿真用于研究模糊控制器的性能。从模拟得出的右转弯和左转弯的路径跟踪误差分别为9 m和7.5 m。

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