Autonomous Car for Indian Terrain

DOI: https://doi.org/10.58190/imiens.2022.3

Keywords

Autonomous Vehicle (AV), Convolutional neural network, Deep learning, Neural Network

Abstract

In recent years, autonomous vehicle (AV) technology has improved dramatically. Self-driving cars have the potential to transform urban mobility in India by offering sustainable, convenient, and congestion-free transportation. However, India confronts challenges such as potholes and the need for enhanced lane detection to make autonomous vehicles a reality. The project's central goal is to create a Convolution Neural Network (CNN) model that can scan and identify its surroundings and move. This paper proposes a project which is accomplished by training CNN with a dataset of images and videos to perform advanced lane identification, pothole recognition, and sophisticated object detection.

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References

  • N. Sanil, P. A. N. venkat, V. Rakesh, R. Mallapur and M. R. Ahmed, "Deep Learning Techniques for Obstacle Detection and Avoidance in Driverless Cars," 2020 International Conference on Artificial Intelligence and Signal Processing (AISP), 2020, pp. 1-4, doi: 10.1109/AISP48273.2020.9073155.
  • Chirag Sharma , S. Bharathiraja , G. Anusooya, “Self Driving Car using Deep Learning Technique”, International Journal of Engineering Research & Technology (IJERT) Volume 09, Issue 06 (June 2020).
  • P. Cai, H. Wang, H. Huang, Y. Liu and M. Liu, "Vision-Based Autonomous Car Racing Using Deep Imitative Reinforcement Learning," in IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 7262-7269, Oct. 2021, doi: 10.1109/LRA.2021.3097345.
  • I. Sonata, Y. Heryadi, L. Lukas, και A. Wibowo, ‘Autonomous car using CNN deep learning algorithm’, Journal of Physics: Conference Series, τ. 1869, τχ. 1, σ. 012071, Απριλίου 2021.
  • Y. Valeja, S. Pathare, D. Patel and M. Pawar, "Traffic Sign Detection using Clara and Yolo in Python," 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), 2021, pp. 367-371, doi: 10.1109/ICACCS51430.2021.9442065.
  • N. Banupriya, S. Saranya, R. Swaminathan, S. Harikumar, και S. Palanisamy, ‘Animal detection using deep learning algorithm’, J. Crit. Rev, τ. 7, τχ. 1, σσ. 434–439, 2020.
  • C. Koch and I. Brilakis, “Pothole detection in asphalt pavement images,” Advanced Engineering Informatics, 01-Feb-2011. [Online].
  • B. -H. Lin and S. -F. Tseng, "A predictive analysis of citizen hotlines 1999 and traffic accidents: A case study of Taoyuan city," 2017 IEEE International Conference on Big Data and Smart Computing (BigComp), 2017, pp. 374-376, doi: 10.1109/BIGCOMP.2017.7881696.
  • D. O'Carroll, “For the love of pizza, Domino's is now fixing potholes in roads,” Stuff, 12-Jun-2018. [Online]. Available: https://www.stuff.co.nz/motoring/104643123/for-the-love-of-pizza-dominos-is-now-fixing-potholes-in-roads. [Accessed: 30-Oct-2022].
  • S. Uchida, S. Ide, B. K. Iwana and A. Zhu, "A Further Step to Perfect Accuracy by Training CNN with Larger Data," 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2016, pp. 405-410, doi: 10.1109/ICFHR.2016.0082.
  • M. Egmont-Petersen, D. de Ridder, and H. Handels, “Image processing with neural networks-A Review,” Pattern Recognition, 19-Jun-2002. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0031320301001789. [Accessed: 30-Oct-2022].
  • Y. Li, “Reinforcement learning in practice: Opportunities and challenges,” arXiv.org, 22-Apr-2022. [Online]. Available: https://arxiv.org/abs/2202.11296v2. [Accessed: 30-Oct-2022].

    • Published: 2022-11-03

    Issue: Vol. 1 No. 1 (2022) (view)

    Section: Research Articles

    How to cite:
    [1]
    S. T. Patil, A. Aher, Aarushi Bhate, Adnan Shaikh, and Sandhya Vinukonda, “Autonomous Car for Indian Terrain”, Intell Methods Eng Sci, vol. 1, no. 1, pp. 13–17, Nov. 2022.

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