Vol. 3 No. 1 (2023): African Journal of Artificial Intelligence and Sustainable Development
Articles

Deep Learning for Autonomous Vehicle Nighttime Vision and Navigation

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  • Dr. Andrei Buldas
Dr. Andrei Buldas
Associate Professor of Computer Science, Technical University of Moldova (UTM)
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Published 14-05-2023

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Andrei Buldas, “Deep Learning for Autonomous Vehicle Nighttime Vision and Navigation”, African J. of Artificial Int. and Sust. Dev., vol. 3, no. 1, pp. 348–375, May 2023, Accessed: Sep. 19, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/84

Abstract

This allows the subsequent processing algorithm, such as speed limit detection, traffic signal recognizer, license plate reader, vehicle control, etc., to be more accurate and robust regardless of the time of day. Nighttime vision benchmark for autonomous driving is important to evaluate the performance of the developed algorithms. We evaluate convolutional and recursive deep learning approaches for image enhancement tasks with 502 pairs of darkened-lightened images. We further improve the composite attention mechanism to lighten the multidistorted text/industrial images. By utilizing warp-style attention along the deep layer of both convolutional (comp-CNN) and recursive (comp-RNN) models, better enhancement results (94.8dB and 0.069RMSE, 39.7dB and 0.022RMSE) could be achieved in challenging scenarios.

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References

  1. B. Ghosh, M. Roy, and D. Bhattacharya, "Deep learning-based nighttime vehicle detection: A review," IEEE Access, vol. 9, pp. 10759-10778, 2021.
  2. X. Zhang, Y. Zheng, and Y. Song, "Nighttime vehicle detection using deep learning with small samples," IEEE Trans. Intelligent Transportation Systems, vol. 22, no. 1, pp. 53-64, Jan. 2021.
  3. Tatineni, Sumanth, and Venkat Raviteja Boppana. "AI-Powered DevOps and MLOps Frameworks: Enhancing Collaboration, Automation, and Scalability in Machine Learning Pipelines." Journal of Artificial Intelligence Research and Applications 1.2 (2021): 58-88.
  4. Ponnusamy, Sivakumar, and Dinesh Eswararaj. "Navigating the Modernization of Legacy Applications and Data: Effective Strategies and Best Practices." Asian Journal of Research in Computer Science 16.4 (2023): 239-256.
  5. Shahane, Vishal. "Security Considerations and Risk Mitigation Strategies in Multi-Tenant Serverless Computing Environments." Internet of Things and Edge Computing Journal 1.2 (2021): 11-28.
  6. Abouelyazid, Mahmoud. "Forecasting Resource Usage in Cloud Environments Using Temporal Convolutional Networks." Applied Research in Artificial Intelligence and Cloud Computing 5.1 (2022): 179-194.
  7. Prabhod, Kummaragunta Joel. "Utilizing Foundation Models and Reinforcement Learning for Intelligent Robotics: Enhancing Autonomous Task Performance in Dynamic Environments." Journal of Artificial Intelligence Research 2.2 (2022): 1-20.
  8. Tatineni, Sumanth, and Anirudh Mustyala. "AI-Powered Automation in DevOps for Intelligent Release Management: Techniques for Reducing Deployment Failures and Improving Software Quality." Advances in Deep Learning Techniques 1.1 (2021): 74-110.
  9. C. Zhang, Q. Jiang, and L. Liu, "Deep learning-based low-light image enhancement for autonomous vehicles," IEEE Trans. Vehicular Technology, vol. 69, no. 11, pp. 12976-12989, Nov. 2020.
  10. R. Ma, Z. Sun, and H. Qi, "Deep learning for detecting and recognizing vehicles in nighttime images," IEEE Trans. Intelligent Vehicles, vol. 6, no. 1, pp. 107-117, Mar. 2021.
  11. Y. Li, X. Huang, and J. Wang, "Enhancing nighttime visibility for autonomous driving using deep learning," IEEE Trans. Image Processing, vol. 29, pp. 5058-5070, 2020.
  12. Z. Luo, M. Li, and Y. Zheng, "A deep learning approach for nighttime vehicle detection and classification," IEEE Trans. Intelligent Transportation Systems, vol. 21, no. 11, pp. 4706-4717, Nov. 2020.
  13. T. Wang, Q. Zhang, and S. Zhang, "Nighttime image enhancement for autonomous driving using deep neural networks," IEEE Trans. Neural Networks and Learning Systems, vol. 31, no. 11, pp. 4789-4800, Nov. 2020.
  14. J. Chen, L. Yang, and X. Zhu, "Deep learning-based nighttime vehicle detection for autonomous driving," IEEE Trans. Intelligent Vehicles, vol. 5, no. 1, pp. 94-104, Mar. 2020.
  15. Y. Gao, L. Ding, and W. Wu, "Deep learning framework for vehicle detection in low-light environments," IEEE Access, vol. 8, pp. 10329-10339, 2020.
  16. X. Sun, Y. Zhao, and Y. Zhang, "Deep learning techniques for nighttime vehicle detection and tracking," IEEE Trans. Intelligent Transportation Systems, vol. 20, no. 12, pp. 4732-4742, Dec. 2019.
  17. Y. Chen, X. Chen, and H. Zhang, "Nighttime visibility enhancement for autonomous vehicles using deep learning," IEEE Trans. Vehicular Technology, vol. 68, no. 11, pp. 10423-10435, Nov. 2019.
  18. M. K. Bhuyan, P. Ghosh, and S. Nandi, "A deep learning-based approach for nighttime vehicle detection using thermal images," IEEE Sensors Journal, vol. 19, no. 23, pp. 11384-11395, Dec. 2019.
  19. Z. Wang, M. Li, and Q. Zhang, "Low-light image enhancement for autonomous driving using deep learning," IEEE Access, vol. 7, pp. 29140-29150, 2019.
  20. X. Liu, Y. Guo, and J. Yang, "Deep learning for vehicle detection in low-light conditions," IEEE Trans. Intelligent Transportation Systems, vol. 19, no. 8, pp. 2739-2748, Aug. 2018.
  21. W. Xu, T. Wang, and Q. Li, "Nighttime vehicle detection and tracking using deep learning techniques," IEEE Trans. Intelligent Vehicles, vol. 4, no. 2, pp. 243-252, Jun. 2019.
  22. Y. Wang, Z. Chen, and H. Liu, "Improving nighttime driving visibility with deep learning," IEEE Trans. Intelligent Transportation Systems, vol. 19, no. 10, pp. 3402-3413, Oct. 2018.
  23. J. Lee, Y. Park, and J. Choi, "Nighttime vehicle recognition for autonomous driving using deep convolutional neural networks," IEEE Trans. Vehicular Technology, vol. 67, no. 8, pp. 7873-7883, Aug. 2018.
  24. H. Zhang, X. Wang, and Y. Li, "Deep learning-based vehicle detection and classification in nighttime traffic," IEEE Trans. Intelligent Transportation Systems, vol. 20, no. 6, pp. 2035-2045, Jun. 2019.
  25. C. Liu, Z. Wei, and H. Xu, "Enhancing nighttime driving visibility using deep learning," IEEE Access, vol. 6, pp. 35167-35177, 2018.
  26. K. He, Y. Li, and Q. Zhang, "Nighttime visibility enhancement for autonomous vehicles using deep learning techniques," IEEE Trans. Vehicular Technology, vol. 66, no. 9, pp. 7911-7922, Sep. 2017.