Self Driving Car Using Deep Neural Networks

Authors

  • Sharmila S Department of Computer Science, East West Institute of Technology, Bengaluru, India
  • Shivaswaroop S Department of Computer Science, East West Institute of Technology, Bengaluru, India
  • Sudhakar M Department of Computer Science, East West Institute of Technology, Bengaluru, India
  • Tejashwini SV Department of Computer Science, East West Institute of Technology, Bengaluru, India
  • Rajshekhar SA Department of Computer Science, East West Institute of Technology, Bengaluru, India

Keywords:

Deep Neural Network, Canny Edge Detection Algorithm, Obstacle Detection

Abstract

Automation has a wide role in the current generation which can be deployed into cars making them drive on their own by considering the surrounding environment as input parameters. Detection of lanes using canny edge lane detection algorithm helps to detect lanes and ensure the drivable space and have clear information of lane in which the car is moving. Deep Neural Networks helps in deciding the action to be performed by the car (forward, reverse, right, left, stop, and park). This paper covers motion control, path detection and obstacle detection. The results have been achieved by the implementation of Canny Edge Detection Algorithm, Deep Neural Networks Techniques.

References

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Published

2025-11-26

How to Cite

[1]
S. S, S. S, S. M, T. SV, and R. SA, “Self Driving Car Using Deep Neural Networks”, Int. J. Comp. Sci. Eng., vol. 7, no. 15, pp. 171–176, Nov. 2025.

Issue

Vol. 7 No. 15 (2019): IJCSE Special Issue May Edition

Section

Research Article

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