arXiv · 2410.07209
Behavior Cloning for Mini Autonomous Car Path Following
Abstract
This article presents the implementation and evaluation of a behavior cloning approach for route following with autonomous cars. Behavior cloning is a machine-learning technique in which a neural network is trained to mimic the driving behavior of a human operator. Using camera data that captures the environment and the vehicle's movement, the neural network learns to predict the control actions necessary to follow a predetermined route. Mini-autonomous cars, which provide a good benchmark for use, are employed as a testing platform. This approach simplifies the control system by directly mapping the driver's movements to the control outputs, avoiding the need for complex algorithms. We performed an evaluation in a 13-meter sizer route, where our vehicle was evaluated. The results show that behavior cloning allows for a smooth and precise route, allowing it to be a full-sized vehicle and enabling an effective transition from small-scale experiments to real-world implementations.
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Pablo Moraes, Christopher Peters, Hiago Sodre, William Moraes, Sebastian Barcelona, Juan Deniz, Victor Castelli, Bruna Guterres, Ricardo Grando. 2024-09-25. Behavior Cloning for Mini Autonomous Car Path Following. https://arxiv.org/abs/2410.07209
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