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A newer version of the DeepPicar can be found at the following repository:


DeepPicar is a low-cost autonomous RC car platform using a deep convolutional neural network (CNN). DeepPicar is a small scale replication of NVIDIA's real self-driving car called Dave-2, which drove on public roads using a CNN. DeepPicar uses the same CNN architecture of NVIDIA's Dave-2 and can drive itself in real-time locally on a Raspberry Pi 3.


DeepPicar Driving

Some other examples of the DeepPicar driving can be found at:

If you wish to recreate the paper's findings, you can train one or more models using our dataset which can be found at:

Please refer to Embedded Platform Comparison for the steps needed to run the experiments conducted in the paper.

Hardware Configuration

DeepPicar is comprised of the following components:

  • Raspberry Pi 3 Model B: $35
  • New Bright 1:24 scale RC car: $10
  • Playstation Eye camera: $7
  • Pololu DRV8835 motor hat: $8
  • External battery pack & misc.: $10

Please refer to Parts and Assembly for assembly steps, and Setup and Operation for in-depth installation and usage instructions.


The DeepPicar code utilizes MIT's DeepTesla (, which provides a TensorFlow version of NVIDIA Dave-2's CNN.

NVIDIA Dave-2 (and its CNN) is described in the following paper.


The paper for DeepPicar can be found at It can be cited using the following BibTeX entry:

	title = {DeepPicar: A Low-cost Deep Neural Network-based Autonomous Car},    
	author = {Michael Garrett Bechtel and Elise McEllhiney and Minje Kim and Heechul Yun},
	booktitle = {IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)},
	year = {2018}


End-to-end deep learning based autonomous RC car using Raspberry Pi 3.







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