Abstract
The steering wheel control is the method used for the navigation of an autonomous vehicle. In order to control the autonomous vehicle, the steering wheel controller must be able to adapt as the road condition and surrounding environment can change abruptly. The existed autonomous system currently in the testing phase. The system still needs to improve because there is some report regarding an accident caused by the test autonomous vehicles. The aim of this research is to implement the human driving capability into the Fuzzy controller. One of the human capabilities is the ability to make a decision based on the current situation. The fuzzy system is developed based on human driving data while controlling a buggy car. The experiments used to collect data such as position, speed, heading and steering wheel angle. Data then use to develop the membership function for the fuzzy inputs and output. The simulation is performed in order to study the performance of the Fuzzy controller. The performance of the Fuzzy controller is satisfactory and can be improved. The maximum path tracking error recorded is 9 m and 7.5 m for right and left turn simulations.
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Acknowledgment
Special gratitude to the members of the UniMAP Advanced Intelligent Computing and Sustainability Research Group (AICoS) and Intelligent Signal Processing (ISP). Thanks to Majlis Amanah Rakyat (MARA) and Universiti Malaysia Perlis (UniMAP) for their technical and financial support.
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Halin, H. et al. (2020). Path Tracking Simulation of the Buggy Car by Using Fuzzy Information of the Steering Wheel. In: Jamaludin, Z., Ali Mokhtar, M.N. (eds) Intelligent Manufacturing and Mechatronics. SympoSIMM 2019. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-9539-0_6
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DOI: https://doi.org/10.1007/978-981-13-9539-0_6
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