Exploring the Current State of Road Lane Detection: A Comprehensive Survey
Keywords:
Road Monitoring, Lane Detection, Survey, Road transportation, Advanced Driver Assistance Systems (ADAS)Abstract
Road lane identification plays a very role in providing directions to the self-driving car and also gives the accurate positions of the vehicle. Therefore, road lane line detection is one of the critical tasks for self-driving cars. The features contribute significantly improves the efficiency and safety of self-driving cars. In this paper, we identify some methods to avoid the risk of getting into another lane. Comparisons are made based on the available dataset and the robustness of these methods.References
Feng, Z., Guo, S., Tan, X., Xu, K., Wang, M., & Ma, L. (2022). Rethinking Efficient Lane Detection via Curve Modeling. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 17062-17070).
Kortli, Y., Gabsi, S., Voon, L. F. L. Y., Jridi, M., Merzougui, M., & Atri, M. (2022). Deep-embedded hybrid CNN–LSTM network for lane detection on NVIDIA Jetson Xavier NX. Knowledge-based systems, 240, 107941.
Yang, S., Yunpeng, L., & Yu, L. (2022). Lane Detection Based on Instance Segmentation of BiSeNet V2 Backbone Network. Applied Artificial Intelligence, 36(1), 2085321.
Philion, J. (2019). Fast draw: Addressing the long tail of lane detection by adapting a sequential prediction network. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 11582-11591).
Gupta, A., Anpalagan, A., Guan, L., & Khwaja, A. S. (2021). Deep learning for object detection and scene perception in self-driving cars: Survey, challenges, and open issues. Array, 10, 100057.
Ahmed, S. T., & Sankar, S. (2020). Investigative protocol design of layer optimized image compression in telemedicine environment. Procedia Computer Science, 167, 2617-2622.
Fayyad, J., Jaradat, M. A., Gruyer, D., & Najjaran, H. (2020). Deep learning sensor fusion for autonomous vehicle perception and localization: A review. Sensors, 20(15), 4220.
Xu, Z., Sun, Y., & Liu, M. (2021). icurb: Imitation learning-based detection of road curbs using aerial images for autonomous driving. IEEE Robotics and Automation Letters, 6(2), 1097-1104.
Tabelini, L., Berriel, R., Paixao, T. M., Badue, C., De Souza, A. F., & Oliveira-Santos, T. (2021, January). Polylanenet: Lane estimation via deep polynomial regression. In 2020 25th International Conference on Pattern Recognition (ICPR) (pp. 6150-6156). IEEE.
Liu, R., Yuan, Z., Liu, T., & Xiong, Z. (2021). End-to-end lane shape prediction with transformers. In Proceedings of the IEEE/CVF winter conference on applications of computer vision (pp. 3694-3702).
Basha, S. M., Poluru, R. K., & Ahmed, S. T. (2022, April). A Comprehensive Study on Learning Strategies of Optimization Algorithms and its Applications. In 2022 8th International Conference on Smart Structures and Systems (ICSSS) (pp. 1-4). IEEE.
Tang, J., Li, S., & Liu, P. (2021). A review of lane detection methods based on deep learning. Pattern Recognition, 111, 107623.
Ghanem, S., Kanungo, P., Panda, G., Satapathy, S. C., & Sharma, R. (2021). Lane detection under artificial colored light in tunnels and on highways: an IoT-based framework for smart city infrastructure. Complex & Intelligent Systems, 1-12.
Basha, S. M., Ahmed, S. T., Iyengar, N. C. S. N., & Caytiles, R. D. (2021, December). Inter-locking dependency evaluation schema based on block-chain enabled federated transfer learning for autonomous vehicular systems. In 2021 Second International Conference on Innovative Technology Convergence (CITC) (pp. 46-51). IEEE.
Fathima, A. S., & Manjunath, S. (2022). Biomedical Image Recurrence Identification Using Image Registration Technique. International Journal of Computational Learning & Intelligence, 1(1), 37-41.
Caltagirone, L., Bellone, M., Svensson, L., & Wahde, M. (2019). LIDAR–camera fusion for road detection using fully convolutional neural networks. Robotics and Autonomous Systems, 111, 125-131.
Lee, C., & Moon, J. H. (2018). Robust lane detection and tracking for real-time applications. IEEE Transactions on Intelligent Transportation Systems, 19(12), 4043-4048.
Wang, Z., Ren, W., & Qiu, Q. (2018). Lanenet: Real-time lane detection networks for autonomous driving. arXiv preprint arXiv:1807.01726.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Bhavana N, Mallikarjun M Kodabagi
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
