Advances in Vision-Based Lane Detection: Algorithms, Integration, Assessment, and Perspectives on ACP-Based Parallel Vision

Yang Xing; Chen Lv; Long Chen; Huaji Wang; Hong Wang; Dongpu Cao; Efstathios Velenis; Fei-Yue Wang

doi:10.1109/JAS.2018.7511063

Volume 5 Issue 3

May 2018

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2018 > 5(3): 645-661

Yang Xing, Chen Lv, Long Chen, Huaji Wang, Hong Wang, Dongpu Cao, Efstathios Velenis and Fei-Yue Wang, "Advances in Vision-Based Lane Detection: Algorithms, Integration, Assessment, and Perspectives on ACP-Based Parallel Vision," IEEE/CAA J. Autom. Sinica, vol. 5, no. 3, pp. 645-661, Mar. 2018. doi: 10.1109/JAS.2018.7511063

Citation:

Yang Xing, Chen Lv, Long Chen, Huaji Wang, Hong Wang, Dongpu Cao, Efstathios Velenis and Fei-Yue Wang, "Advances in Vision-Based Lane Detection: Algorithms, Integration, Assessment, and Perspectives on ACP-Based Parallel Vision," IEEE/CAA J. Autom. Sinica, vol. 5, no. 3, pp. 645-661, Mar. 2018. doi: 10.1109/JAS.2018.7511063

Citation:

Yang Xing, Chen Lv, Long Chen, Huaji Wang, Hong Wang, Dongpu Cao, Efstathios Velenis and Fei-Yue Wang, "Advances in Vision-Based Lane Detection: Algorithms, Integration, Assessment, and Perspectives on ACP-Based Parallel Vision," IEEE/CAA J. Autom. Sinica, vol. 5, no. 3, pp. 645-661, Mar. 2018. doi: 10.1109/JAS.2018.7511063

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Advances in Vision-Based Lane Detection: Algorithms, Integration, Assessment, and Perspectives on ACP-Based Parallel Vision

doi: 10.1109/JAS.2018.7511063

Yang Xing^1
,,
Chen Lv^2
,,
Long Chen^3
,,
Huaji Wang^2
,,
Hong Wang^4
,,
Dongpu Cao^{4
,
,},
Efstathios Velenis^2
,,
Fei-Yue Wang^5
,

1.
Advanced Vehicle Engineering Centre, Cranfield University, Bedford MK43 0AL, U. K., and also with Vehicle Intelligence Pioneers Ltd, Qingdao, 266000, China
2.
Advanced Vehicle Engineering Centre, Cranfield University, Bedford MK43 0AL, UK
3.
School of Data and Computer Science, Sun Yat-Sen University, Guangzhou 510275, China
4.
Mechanical and Mechatronics Engineering with the University of Waterloo, 200 University Avenue West Waterloo, ON, N2L 3G1, Canada
5.
State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

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Author Bio:
Yang Xing received the B.S. degree in automatic control from Qingdao University of Science and Technology, China, in 2012. He then received the MSc. degree in control systems from the Department of Automatic Control and System Engineering, The University of Sheffield, UK, in 2014. Now he is a Ph. D. candidate for transport systems, Cranfield University, UK. His research interests include driver behavior modelling, driver-vehicle interaction, and advanced driver assistance systems. His work focuses on the understanding of driver behaviors and identification of driver intentions using machine-learning methods for intelligent and automated vehicles.(e-mail: y.xing@cranfield.ac.uk)

Chen Lv (S'14-M'16) is currently a Research Fellow at Advanced Vehicle Engineering Center, Cranfield University, UK. He received the Ph.D. degree at the Department of Automotive Engineering, Tsinghua University, China in 2016. From 2014 to 2015, he was a joint Ph.D. researcher at EECS Dept., University of California, Berkeley. His research focuses on cyber-physical system, hybrid system, advanced vehicle control and intelligence, where he has contributed over 40 papers and obtained 11 patents in China. Dr. Lv serves as a Guest Editor for IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Industrial Informatics, and International Journal of Powertrains, and an Associate Editor for International Journal of Electric and Hybrid Vehicles, International Journal of Vehicle Systems Modelling and Testing, International Journal of Science and Engineering for Smart Vehicles, and Journal of Advances in Vehicle Engineering. He received the Highly Commended Paper Award of IMechE UK in 2012, the National Fellowship for Doctoral Student in 2013, the NSK Outstanding Mechanical Engineering Paper Award in 2014, the Tsinghua University Graduate Student Academic Rising Star Nomination Award in 2015, the China SAE Outstanding Paper Award in 2015, the 1st Class Award of China Automotive Industry Scientific and Technological Invention in 2015, and the Tsinghua University Outstanding Doctoral Thesis Award in 2016.(e-mail: c.lyu@cranfield.ac.uk)

Long Chen received the Ph.D. degree from Wuhan University, China, in 2013. He is also a co-trained Ph.D. at Social Robot Lab, the National University of Singapore. He is currently an Associate Professor at the School of Data and Computer Science, Sun Yat-Sen University. His researches focus on intelligent vehicle, including environment perception, scene understanding and 3D reconstruction, where he has contributed more than 40 publications and 10 Chinese patents. Dr. Chen serves as an Associate Editor for IEEE Technical Committee on CyberPhysical Systems Newsletter.(e-mail: chenl46@mail.sysu.edu.cn)

Huaji Wang received the B.S. degree in automotive engineering from Jilin University, China, in 2005, and the Ph.D. degree in Engineering from the University of Cambridge, Cambridge, U.K., in 2016, concentrating on the study of driver/vehicle systems and driver-automation collaboration. He presently works as a Research Fellow in automated driving at Cranfield University, UK.(e-mail: huaji.wang, d.cao@cranfield.ac.uk)

Hong Wang is currently a Postdoc Fellow of Mechanical and Mechatronics Engineering at University of Waterloo, Canada. She received the Ph.D. degree from Beijing Institute of Technology, China in 2015. Her research focuses on the component sizing, modeling of hybrid powertrains and power management control strategies design for hybrid electric vehicles, intelligent control theory and application, autonomous vehicles.(e-mail: hong.wang@uwaterloo.ca)

Dongpu Cao (M'08) received the Ph.D. degree from Concordia University, Canada, in 2008. He is currently an Associate Professor at University of Waterloo, Canada. His research focuses on vehicle control and intelligence, automated driving and parallel driving, where he has contributed more than 130 publications and 1 US patent. He received the ASME AVTT2010 Best Paper Award and 2012 SAE Arch T. Colwell Merit Award. Dr. Cao serves as an Associate Editor for IEEE Transactions on Vehicular Technology, IEEE Transactions on Intelligent Transportation Systems, IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Industrial Electronics, and ASME Journal of Dynamic Systems, Measurement and Control. He has been a Guest Editor for Vehicle System Dynamics, and IEEE Transactions on Human-machine Systems. He has been serving on the SAE International Vehicle Dynamics Standards Committee and a few ASME, SAE, IEEE technical committees.(e-mail: dongpu.cao@uwaterloo.ca)

Efstathios Velenis received the Ph.D. degree from the School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA, in 2006. He is currently a Senior Lecturer with the Advanced Vehicle Engineering Centre, Cranfield University, Cranfield, U.K. His current research interests include vehicle dynamics and control, optimal control for active chassis systems, traction, braking, and handling control for electric/hybrid vehicles, laptime optimization, and tire modeling. He obtained research funding from EPSRC, Innovate U.K., and the European Commission. Dr. Velenis received the Luther Long Award for best Ph.D. dissertation in the area of engineering mechanics at Georgia Tech.(e-mail: e.velenis@cranfield.ac.uk)

Fei-Yue Wang (S'87-M'89-SM'94-F'03) received his Ph.D. in Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy, New York in 1990. He joined the University of Arizona in 1990 and became a Professor and Director of the Robotics and Automation Lab (RAL) and Program in Advanced Research for Complex Systems (PARCS). In 1999, he founded the Intelligent Control and Systems Engineering Center at the Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China, under the support of the Outstanding Overseas Chinese Talents Program from the State Planning Council and "100Talent Program" from CAS, and in 2002, was appointed as the Director of the Key Lab of Complex Systems and Intelligence Science, CAS. From 2006 to 2010, he was Vice President for Research, Education, and Academic Exchanges at the Institute of Automation, CAS. In 2011, he became the State Specially Appointed Expert and the Director of the State Key Laboratory of Management and Control for Complex Systems. Dr. Wang's current research focuses on methods and applications for parallel systems, social computing, and knowledge automation. He was the Founding Editor-in-Chief of the International Journal of Intelligent Control and Systems (1995-2000), Founding EiC of IEEE ITS Magazine (2006-2007), EiC of IEEE Intelligent Systems (2009-2012), and EiC of IEEE Transactions on ITS (2009-2016). Currently he is EiC of IEEE Transactions on Computational Social Systems, Founding EiC of IEEE/CAA Journal of Automatica Sinica, and Chinese Journal of Command and Control. Since 1997, he has served as General or Program Chair of more than 20 IEEE, INFORMS, ACM, and ASME conferences. He was the President of IEEE ITS Society (2005-2007), Chinese Association for Science and Technology (CAST, USA) in 2005, the American Zhu Kezhen Education Foundation (2007-2008), and the Vice President of the ACM China Council (2010-2011). Since 2008, he has been the Vice President and Secretary General of Chinese Association of Automation. Dr. Wang has been elected as Fellow of IEEE, INCOSE, IFAC, ASME, and AAAS. In 2007, he received the National Prize in Natural Sciences of China and was awarded the Outstanding Scientist by ACM for his research contributions in intelligent control and social computing. He received IEEE ITS Outstanding Application and Research Awards in 2009, 2011 and 2015, and IEEE SMC Norbert Wiener Award in 2014.(e-mail: feiyue@ieee.org)
Corresponding author: Dongpu Cao, e-mail: dongpu.cao@uwaterloo.ca
Received Date: 2017-07-10
Accepted Date: 2017-12-06

Abstract

Abstract

Lane detection is a fundamental aspect of most current advanced driver assistance systems (ADASs). A large number of existing results focus on the study of vision-based lane detection methods due to the extensive knowledge background and the low-cost of camera devices. In this paper, previous visionbased lane detection studies are reviewed in terms of three aspects, which are lane detection algorithms, integration, and evaluation methods. Next, considering the inevitable limitations that exist in the camera-based lane detection system, the system integration methodologies for constructing more robust detection systems are reviewed and analyzed. The integration methods are further divided into three levels, namely, algorithm, system, and sensor. Algorithm level combines different lane detection algorithms while system level integrates other object detection systems to comprehensively detect lane positions. Sensor level uses multi-modal sensors to build a robust lane recognition system. In view of the complexity of evaluating the detection system, and the lack of common evaluation procedure and uniform metrics in past studies, the existing evaluation methods and metrics are analyzed and classified to propose a better evaluation of the lane detection system. Next, a comparison of representative studies is performed. Finally, a discussion on the limitations of current lane detection systems and the future developing trends toward an Artificial Society, Computational experiment-based parallel lane detection framework is proposed.
- Advanced driver assistance systems (ADASs),
- ACP theory,
- benchmark,
- lane detection,
- parallel vision,
- performance evaluation

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References(112)

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Advances in Vision-Based Lane Detection: Algorithms, Integration, Assessment, and Perspectives on ACP-Based Parallel Vision

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