[1] [1] KIM Z. Robust lane detection and tracking in challenging scenarios[J]. IEEE Transactions on Intelligent Transportation Systems, 2008, 9(1): 16-26.

[2] [2] CHEN L, LI Q Q, MAO Q Z, et al. Block-constraint line scanning method for lane detection[C]//2010 IEEE Intelligent Vehicles Symposium, La Jolla: IEEE, 2010.

[3] [3] BAR HILLEL A, LERNER R, LEVI D, et al. Recent progress in road and lane detection: a survey[J]. Machine Vision and Applications, 2014, 25(3): 727-745.

[4] [4] YENIKAYA S, YENIKAYA G, DVEN E. Keeping the vehicle on the road[J]. ACM Computing Surveys, 2013, 46(1): 1-43.

[5] [5] LI Q Q, CHEN L, LI M, et al. A sensor-fusion drivable-region and lane-detection system for autonomous vehicle navigation in challenging road scenarios[J]. IEEE Transactions on Vehicular Technology, 2014, 63(2): 540-555.

[6] [6] BORKAR A, HAYES M, SMITH M T. A novel lane detection system with efficient ground truth generation[J]. IEEE Transactions on Intelligent Transportation Systems, 13(1): 365-374.

[7] [7] HUR J, KANG S N, SEO S W. Multi-lane detection in urban driving environments using conditional random fields[C]//2013 IEEE Intelligent Vehicles Symposium (IV), Gold Coast City: IEEE, 2013.

[8] [8] TAN H C, ZHOU Y, ZHU Y, et al. A novel curve lane detection based on Improved River Flow and RANSA[C]//17th International IEEE Conference on Intelligent Transportation Systems (ITSC), Qingdao: IEEE, 2014.

[14] [14] VAN GANSBEKE W, DE BRABANDERE B, NEVEN D, et al. End-to-end lane detection through differentiable least-squares fitting[C]//2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), Seoul: IEEE, 2019.

[15] [15] WU D, LIAO M-W, ZHANG W-T, et al. YOLOP: you only look once for panoptic driving perception[J]. IEEE Machine Intelligence Research, 2022, 19(6): 550-562.

[16] [16] QIN Z Q, WANG H Y, LI X. Ultra fast structure-aware deep lane detection[M]. Computer Vision-ECCV 2020. Cham: Springer International Publishing, 2020: 276-291.

[18] [18] SANDLER M, HOWARD A, ZHU M L, et al. MobileNetV2: inverted residuals and linear bottlenecks[C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City: IEEE, 2018: 4510-4520.

[19] [19] HOWARD D, ANDREW G. Mobile nets: efficient convolutional neural networks for mobile vision applications[C]//Computer Vision and Pattern Recognition, Hawaii, the United States, 2017: 1-9.

[20] [20] WAGSTAFF K, CARDIE C, ROGERS S, et al. Constrained K-means clustering with background knowledge[C]//Proceedings of the Eighteenth International Conference on Machine Learning. 2001: 577-584.

[21] [21] LINARTH A, ANGELOPOULOU E. On feature templates for particle filter based lane detection[C]//2011 14 th International IEEE Conference on Intelligent Transportation Systems (ITSC), Washington: IEEE, 2011: 1721-1726.

[22] [22] KO Y, LEE Y, AZAM S, et al. Key points estimation and point instance segmentation approach for lane detection[J]. IEEE Transactions on Intelligent Transportation Systems, 23(7): 8949-8958.

[23] [23] TABELINI L, BERRIEL R, PAIXAO T M, et al. Keep your eyes on the lane: real-time attention-guided lane detection[C]//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville: IEEE, 2021: 294-302.

[24] [24] ABUALSAUD H, LIU S A, LU D B, et al. LaneAF: robust multi-lane detection with affinity fields[J]. IEEE Robotics and Automation Letters, 2021, 6(4): 7477-7484.