Intelligent Hybrid Fusion Algorithm with Vision Patterns for Generation of Precise Digital Road Maps in Self-driving Vehicles |
Jung, Juho
(Department of Software, Korea National University of Transportation)
Park, Manbok (Department of Electronic Engineering, Korea National University of Transportation) Cho, Kuk (Land and Geospatial Informatix - Spatial Information Research Institue) Mun, Cheol (Department of Electronic Engineering, Korea National University of Transportation) Ahn, Junho (Department of Software, Korea National University of Transportation) |
1 | NHTSA, "Critical Reasons for Crashes Investigated in the National Motor Vehicle Crash Causation Survey," 2018. |
2 | National Sleep Foundation, "Drowsy Driving," 2019. |
3 | Tesla, "Autopilot". |
4 | Waymo, "Safety". |
5 | Uber, "Safety". |
6 | General Motors, "Mission". |
7 | ABIresearch, "High Accuracy and Real-time Maps for Autonomous Vehicles," 2016. |
8 | J. Canny, "A Computational Approach to Edge Detection," IEEE transactions on pattern analysis and machine intelligence, Vol. pami-8, no. 6. pp. 679-698, 1986. DOI |
9 | W. Farag and Z. Saleh, "Road Lane-Lines Detection in Real-Time for Advanced Driving Assistance Systems," in Proc. of International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT), pp. 1-8, 2018. |
10 | S. P. Narote, P. N. Bhujbal, A. S. Narote and D. M. Dhane, "A review of recent advances in lane detection and departure warning system," Pattern Recognition, vol. 73, pp. 216-234, 2018. DOI |
11 | Y. Huang, Y. Li, X. Hu and W. Ci, "Lane Detection Based on Inverse Perspective Transformation and Kalman Filter," KSII Transactions on Internet and Information Systems, vol. 12, no. 2, pp. 643-661, 2018. DOI |
12 | D. Neven, B. D. Brabandere, S. Georgoulis, M. Proesmans and L. V. Gool, "Towards End-to-End Lane Detection: an Instance Segmentation Approach," arXiv, pp. 1-7, 2018. |
13 | W. Song, Y. Yang, M. Fu, Y. Li and M. Wang, "Lane Detection and Classification for Forward Collision Warning System Based on Stereo Vision," IEEE Sensors Journal, vol. 18, no. 12, pp. 5151-5163, 2018. DOI |
14 | J. Shen, N. Liu, H. Sun, X. Tao and Q. Li, "Vehicle Detection in Aerial Images Based on Hyper Feature Map in Deep Convolutional Network," KSII Transactions on Internet and Information Systems, vol. 13, no. 4, pp. 1989-2011, 2019. DOI |
15 | S. Ren, K. He, R. Girshick and J. Sun, "Faster R-CNN: Towards real-time object detection with region proposal networks," in Proc. of the 28th International Conference on Neural Information Processing Systems, vol. 1, pp. 91-99, 2015. |
16 | J. Huang, V. Rathod, C. Sun, M. Zhu, A. Korattikara, A. Fathi, L. Fischer, Z. Wonja, Y. Song, S. Guadarrama and K. Murphy, "Speed/accuracy trade-offs for modern convolutional object detectors," in Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 3296-3297, 2017. |
17 | R. Girshick, "Fast R-CNN," in Proc. of IEEE International Conference on Computer Vision and Pattern Recognition, pp. 1440-1448, 2015. |
18 | Tensorflow, "Object detection model zoo". |
19 | C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens and Z. Wojna, "Rethinking the Inception Architecture for Computer Vision," in Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 2818-2826, 2016. |
20 | Y. Xing, C. Lv, L. Chen, H. Wang, H. Wang, D. Cao, E. Velenis and F. Wang, "Advances in Vision-Based Lane Detection: Algorithms, Integration, Assessment, and Perspectives on ACP-Based Parallel Vision," IEEE/CAA Journal of Automatica Sinica, vol. 5, no. 3, pp. 645-661, 2018. DOI |
21 | Z. Wang, W. Ren and Q. Qiu, "LaneNet: Real-Time Lane Detection Networks for Autonomous Driving," arXiv, pp. 1-9, 2018. |
22 | M. F. Delgado, E. Cernadas, S. Barro and D. Amorim, "Do we Need Hundreds of Classifiers to Solve Real World Classification Problems?," The Journal of Machine Learning Research, Vol. 15, no. 1, pp. 3133-3181, 2014. |
23 | C. Yuan, H. Chen, J. Liu, D. Zhu and Y. Xu, "Robust Lane Detection for Complicated Road Environment Based on Normal Map," IEEE Access, vol. 6, pp. 49679-49689, 2018. DOI |
24 | C. Tan, F. Sun, T. Kong,W. Zhang, C. Yang and C. Liu, "A Surbey on Deep Transfer Learning," in Proc. of International Conference on Artificial Neural Networks, Lecture Notes in Computer Science, vol. 11141, pp 270-279, 2018. |
25 | J. Ahn and R. Han, "myBlackBox: Blackbox Mobile Cloud Systems for Personalized Unusual Event Detection," Sensors (Basel), vol. 16, no. 5, pp. 753, 2016. DOI |
26 | N. Dogru and A. Subasi, "Traffic Accident Detection Using Random Forest Classifier," in Proc. of 15th Learning and Technology Conference (L&T), pp. 40-45, 2018. |
27 | J. Gwak, J. Jung, R. Oh, M. Park, M. A. K. Rakhimov and Junho ahn, "A Review of Intelligent Self-Driving Vehicle Software Research," KSII Transactions on Internet and Information Systems, vol. 13, no. 11, pp. 5299-5320, 2019. DOI |
28 | T. K. Ho, "Random Decision Forests," in Proc. of the 3rd International Conference on Document Analysis and Recognition, Montreal, QC, vol. 1, pp. 278-282, 1995. |
29 | National Geographic Information Institute, "Precision road map". |
30 | S. Li, Z. Hu and M. Zhao, "Moving Object Detection Using Sparse Approximation and Sparse Coding Migration," KSII Transactions on Internet and Information Systems, vol. 14, no. 5, pp. 2141-2155, 2020. DOI |