Self-driving vehicles are one of the trending technologies with a significant operational progress over the last decade. Self-driving cars have the capacity to save people and to promote peaceful lives. Autonomous cars use software to limit or remove human interaction by making decisions regarding the actions a vehicle must take in a given situation and then manipulate physical machinery to adjust the steering angle, the throttle, and the braking mechanisms. The goal of this work is to explore the necessary software components and techniques required to create an autonomous vehicle. The open-source Udacity Car Simulator environment is used to collect data, train, and evaluate the performance of the self drive car modeled in this work. External software using image processing combined with machine learning techniques such as neural networks and behavioral cloning is developed to mimic human driving on the training mode on the Udacity track.
Dam, Anh Tran Quynh, "Self-driving Car with Udacity Simulator" (2021). Senior Independent Study Theses. Paper 9361.
Navigation, Guidance, Control, and Dynamics | Robotics
self-driving car, machine learning, neural networks
Bachelor of Arts
Senior Independent Study Thesis
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