Abstract
We are presenting a model for self-driving car simulator provided by Udacity as an open-source simulator. We will then use the simulator to create our own training data for our model which will be driving a car through training mode on its track in the simulator. We are taking images at each instance of the drive. These images are used as a training dataset, and the labels are steering angle for each specific image at that instance. We will then input all those images to our Nvidia’s convolutional neural network model and allow it to learn how to drive autonomously by learning from our behavior as the manual driver. Our main variable is the steering angle which our model learns to adjust at any given instance. Now, as our model is perfectly trained, we use autonomous mode to find the performance of our model by driving the car autonomously.
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Tripathi, R., Vyas, S., Tewari, A. (2021). Behavioral Cloning for Self-driving Cars Using Deep Learning. In: Tiwari, S., Suryani, E., Ng, A.K., Mishra, K.K., Singh, N. (eds) Proceedings of International Conference on Big Data, Machine Learning and their Applications. Lecture Notes in Networks and Systems, vol 150. Springer, Singapore. https://doi.org/10.1007/978-981-15-8377-3_18
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DOI: https://doi.org/10.1007/978-981-15-8377-3_18
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