Analysis of Autopilot Disengagements Occurring During Autonomous Vehicle Testing

Chen Lv; Dongpu Cao; Yifan Zhao; Daniel J. Auger; Mark Sullman; Huaji Wang; Laura Millen Dutka; Lee Skrypchuk; Alexandros Mouzakitis

doi:10.1109/JAS.2017.7510745

Volume 5 Issue 1

Jan. 2018

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2018 > 5(1): 58-68

Chen Lv, Dongpu Cao, Yifan Zhao, Daniel J. Auger, Mark Sullman, Huaji Wang, Laura Millen Dutka, Lee Skrypchuk and Alexandros Mouzakitis, "Analysis of Autopilot Disengagements Occurring During Autonomous Vehicle Testing," IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 58-68, Jan. 2018. doi: 10.1109/JAS.2017.7510745

Citation:

Chen Lv, Dongpu Cao, Yifan Zhao, Daniel J. Auger, Mark Sullman, Huaji Wang, Laura Millen Dutka, Lee Skrypchuk and Alexandros Mouzakitis, "Analysis of Autopilot Disengagements Occurring During Autonomous Vehicle Testing," IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 58-68, Jan. 2018. doi: 10.1109/JAS.2017.7510745

Citation:

Chen Lv, Dongpu Cao, Yifan Zhao, Daniel J. Auger, Mark Sullman, Huaji Wang, Laura Millen Dutka, Lee Skrypchuk and Alexandros Mouzakitis, "Analysis of Autopilot Disengagements Occurring During Autonomous Vehicle Testing," IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 58-68, Jan. 2018. doi: 10.1109/JAS.2017.7510745

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Analysis of Autopilot Disengagements Occurring During Autonomous Vehicle Testing

doi: 10.1109/JAS.2017.7510745

1.
School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield, Bedford, MK43 0AL, UK
2.
Skrypchuk, and A. Mouzakitis are with Jaguar Land Rover, Coventry, CV3 4LF, UK

Funds: This work was supported by Jaguar Land Rover and the UK-EPSRC grant EP/N012089/1 as part of the jointly funded Towards Autonomy:Smart and Connected Control (TASCC) Programme

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Author Bio:
Chen Lv is currently a Research Fellow at Advanced Vehicle Engineering Center, Cranfield University, UK. He received the Ph.D. degree at 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 holds 11 granted China patents. Dr. Lv serves as a Guest Editor for IEEE/ASME Transactions on Mechatronics and IEEE Transactions on Industrial Informatics, and an Associate Editor for International Journal of Electric and Hybrid Vehicles, International Journal of Vehicle Systems Modelling and Testing, and International Journal of Science and Engineering for Smart Vehicles. He received the Highly Commended Paper Award of IMechE UK in 2012, 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)

Dongpu Cao received the Ph.D. degree from Concordia University, Canada, in 2008. He is currently a Senior Lecturer at Advanced Vehicle Engineering Center, Cranfield University, UK. His research focuses on vehicle dynamics and control, automated driving and parallel driving, where he has contributed more than 100 publications and 1 US patent. He received the ASME AVTT'2010 Best Paper Award and 2012 SAE Arch T. Colwell Merit Award. Dr. Cao serves as an Associate Editor for IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Vehicular Technology, IEEE Transactions on Industrial Electronics, IEEE/ASME Transactions on Mechatronics 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 serves on the SAE International Vehicle Dynamics Standards Committee and a few ASME, SAE, IEEE technical committees. (e-mail: d.cao@cranfield.ac.uk)

Yifan Zhao received the Ph.D. degree in automatic control and system engineering from the University of Sheffield, Sheffield, U.K., in 2007. He is currently a Lecturer in image and signal processing and degradation assessment at Cranfield University, Cranfield, U.K. His research interests include computer-vision-based process monitoring, super resolution, active thermography, and nonlinear system identification. (e-mail: yifan.zhao@cranfield.ac.uk)

Daniel J. Auger received the M.Eng.and Ph.D. degrees in control engineering from Cambridge University, Cambridge, U.K., specializing in model validation for robust feedback control design. He is currently a Lecturer in Advanced Control and Optimization with Cranfield University, Cranfield, U.K. His recent publications have looked at techniques for addressing battery aging through optimal system design, the development of advanced battery state estimators, and techniques for the quantification of in-vehicle battery degradation. His current research interests include the application of advanced control methodologies to automotive design, development of software-embeddable battery models, optimal state-estimator design, and robust control architectures. (e-mail: d.j.auger@cranfield.ac.uk)

Mark Sullman is a Senior Lecturer based in the Driving Research Group, located in the Department of Advanced Systems. He received MSc and PhD from Massey University, New Zealand. He has more than 20 years of research and consultancy experience in the areas of occupational safety and driving behavior and has provided consultancy for a number of multinational companies. He is on the Editorial Advisor Board for Transportation Research Part F (Traffic Psychology and Behavior) and regularly reviews articles for several other international journals. In 2010 he was appointed the European representative for Division 13 of the International Association of Applied Psychology (IAAP) and has been on the Scientific Advisory board for many international conferences. He has authored over 65 journal articles, 24 book chapters, and more than 150 conference papers and industry reports. (e-mail: m.sullman@cranfield.ac.uk)

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@cranfield.ac.uk)

Laura Millen Dutka is a Human Machine Interface Technical Specialist at Jaguar Land Rover. (e-mail: lmillen@jaguarlandrover.com)

Lee Skrypchuk is a Human Machine Interface Technical Specialist at Jaguar Land Rover. (e-mail: lskrypch@jaguarlandrover.com)

Alexandros Mouzakitis is the Head of Electrical, Electronics & Software Engineering Research Department at Jaguar Land Rover. (e-mail: amouzak1@jaguarlandrover.com)
Corresponding author: Dongpu Cao, e-mail:d.cao@cranfield.ac.uk
Received Date: 2017-02-28
Accepted Date: 2017-09-29

Abstract

Abstract

In present-day highly-automated vehicles, there are occasions when the driving system disengages and the human driver is required to take-over. This is of great importance to a vehicle's safety and ride comfort. In the U.S state of California, the Autonomous Vehicle Testing Regulations require every manufacturer testing autonomous vehicles on public roads to submit an annual report summarizing the disengagements of the technology experienced during testing. On 1 January 2016, seven manufacturers submitted their first disengagement reports:Bosch, Delphi, Google, Nissan, Mercedes-Benz, Volkswagen, and Tesla Motors. This work analyses the data from these disengagement reports with the aim of gaining abetter understanding of the situations in which a driver is required to takeover, as this is potentially useful in improving the Society of Automotive Engineers (SAE) Level 2 and Level 3 automation technologies. Disengagement events from testing are classified into different groups based on attributes and the causes of disengagement are investigated and compared in detail. The mechanisms and time taken for take-over transition occurred in disengagements are studied. Finally, recommendations for OEMs, manufacturers, and government organizations are also discussed.
- Automated vehicle,
- Disengagement,
- humanvehicle interactions,
- take-over operation,
- vehicle testing

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References

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Analysis of Autopilot Disengagements Occurring During Autonomous Vehicle Testing

doi: 10.1109/JAS.2017.7510745

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