Deep Learning for Line Road Detection in Smart Cars
الموضوعات : Majlesi Journal of Telecommunication Devices
Zohreh Dorrani
1
(Payame Noor University, Tehran, Iran)
الکلمات المفتاحية: Artificial Intelligence, Deep Learning, Smart Cars, YOLOV8,
ملخص المقالة :
In recent years, smart cars have advanced rapidly and use artificial intelligence technology to predict behavior, make decisions, and control goals. This technology significantly determines the knowledge level of vehicles. In the complex and dynamic environment of road traffic, negligence, and inattention can lead to irreparable damage. Real-time identification and positioning of road lines are key to improving the safety of driving cars. To improve the performance of safe driving assistance, this paper shows how to detect road lines using the YOLOV8 algorithm and then make decisions to continue driving straight, turn right, and turn left. Simulation results and accuracy comparison show that this approach can be used as a reliable source for creating driving assistance scenarios in natural road traffic environments. The use of artificial intelligence and the precise architecture of YOLOV8 promise high speed and accuracy in smart cars.
[1] D.-H. Lee and J.-L. Liu, "End-to-end deep learning of lane detection and path prediction for real-time autonomous driving," Signal, Image and Video Processing, vol. 17, no. 1, pp. 199-205, 2023.
[2] A. Arshaghi and M. Norouzi, "A Survey on Face Recognition Based on Deep Neural Networks," Majlesi Journal of Telecommunication Devices, 2023.
[3] A. A. Abed and M. Emadi, "Detection and Segmentation of Breast Cancer Using Auto Encoder Deep Neural Networks," Majlesi Journal of Telecommunication Devices, vol. 12, no. 4, pp. 209-217, 2023.
[4] N. Habibi and S. Mousavi, "A Survey on Applications of Machine Learning in Bioinformatics and Neuroscience," Majlesi Journal of Telecommunication Devices, vol. 11, no. 2, pp. 95-111, 2022.
[5] Z. Dorrani, "Traffic scene analysis and classification using deep learning," International Journal of Engineering, 2023.
[6] M. Ghasemzade, "Extracting Image Features Through Deep Learning," Majlesi Journal of Telecommunication Devices, vol. 9, no. 3, pp. 109-114, 2020.
[7] Z. Dorrani, H. Farsi, and S. Mohamadzadeh, "Deep Learning in Vehicle Detection Using ResUNet-a Architecture," Jordan Journal of Electrical Engineering. All rights reserved-Volume, vol. 8, no. 2, p. 166, 2022.
[8] Z. Dorrani, H. Farsi, and S. Mohammadzadeh, "Edge Detection and Identification using Deep Learning to Identify Vehicles," Journal of Information Systems and Telecommunication (JIST), vol. 3, no. 39, p. 201, 2022.
[9] Z. Dorrani, "Road Detection with Deep Learning in Satellite Images," Majlesi Journal of Telecommunication Devices, vol. 12, no. 1, pp. 43-47, 2023.
[10] S.-W. Baek, M.-J. Kim, U. Suddamalla, A. Wong, B.-H. Lee, and J.-H. Kim, "Real-time lane detection based on deep learning," Journal of Electrical Engineering & Technology, vol. 17, no. 1, pp. 655-664, 2022.
[11] H. Nadeem et al., "Road feature detection for advance driver assistance system using deep learning," Sensors, vol. 23, no. 9, p. 4466, 2023.
[12] E. Oğuz, A. Küçükmanisa, R. Duvar, and O. Urhan, "A deep learning based fast lane detection approach," Chaos, Solitons & Fractals, vol. 155, p. 111722, 2022.
[13] Z. Zhao, Q. Wang, and X. Li, "Deep reinforcement learning based lane detection and localization," Neurocomputing, vol. 413, pp. 328-338, 2020.
[14] N. J. Zakaria, M. I. Shapiai, R. Abd Ghani, M. N. M. Yassin, M. Z. Ibrahim, and N. Wahid, "Lane detection in autonomous vehicles: A systematic review," IEEE access, vol. 11, pp. 3729-3765, 2023.
[15] L. Zhang, G. Ding, C. Li, and D. Li, "DCF-Yolov8: An Improved Algorithm for Aggregating Low-Level Features to Detect Agricultural Pests and Diseases," Agronomy, vol. 13, no. 8, p. 2012, 2023.
[16] Z. Dorrani and M. Mahmoodi, "Noisy images edge detection: Ant colony optimization algorithm," Journal of AI and Data Mining, vol. 4, no. 1, pp. 77-83, 2016.
[17] Detection of lanes on a road and prediction of turns based on vanishing point. https://github.com/ysshah95/Lane-Detection-using-MATLAB
