This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Hardware-in-the-Loop (HIL) Implementation and Validation of SAE Level 2 Autonomous Vehicle with Subsystem Fault Tolerant Fallback Performance for Takeover Scenarios
Technical Paper
2017-01-1994
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
The advancement towards development of autonomy follows either the bottom-up approach of gradually improving and expanding existing Advanced Driver Assist Systems (ADAS) technology where the driver is present in the control loop or the top-down approach of directly developing Autonomous Vehicles (AV) hardware and software using alternative approaches without the driver present in the control loop. Most ADAS systems today fall under the classification of SAE Level 1 which is also referred to as the driver assistance level. The progression from SAE Level 1 to SAE Level 2 or partial automation involves the critical task of merging autonomous lateral control and autonomous longitudinal control such that the tasks of steering and acceleration/deceleration are not required to be handled by the driver under certain conditions [1]. However, the driver is still required to monitor the driving environment and handle scenarios where control is handed over to the driver due to subsystem faults of the autonomous system. Due to the disadvantages of vehicle testing being expensive, time-consuming and hazardous for testing such scenarios, an alternative method of development and validation is required. Therefore, the objectives of this research are two-fold. The first objective focuses on a real-time powertrain-based Hardware-in-the-Loop (HIL) implementation and validation of an SAE Level 2 autonomous vehicle. The second objective focuses on studying the performance of SAE Level 2 autonomous vehicles during takeover scenarios due to subsystem faults. To accomplish these objectives, an acceleration-based Adaptive Cruise Control (ACC) was combined with a path-following lateral control along with supervisory control for system mode transitions due to system deactivations and faults. This research presents system modes in which longitudinal control only and lateral control only are engaged as fallback states to the full autonomous system being faulted for lateral control and longitudinal control failures respectively. Simulations were conducted to evaluate the performance of the autonomous controls when subjected to these faults. A powertrain subsystem representative of the 2017 Ford Fusion Hybrid was used as the hardware simulation platform using a dSPACE HIL simulator and CarSim RT.
Recommended Content
Authors
Citation
Joshi, A., "Hardware-in-the-Loop (HIL) Implementation and Validation of SAE Level 2 Autonomous Vehicle with Subsystem Fault Tolerant Fallback Performance for Takeover Scenarios," SAE Technical Paper 2017-01-1994, 2017, https://doi.org/10.4271/2017-01-1994.Data Sets - Support Documents
| Title | Description | Download |
|---|---|---|
| [Unnamed Dataset 1] | ||
| [Unnamed Dataset 2] | ||
| [Unnamed Dataset 3] | ||
| [Unnamed Dataset 4] | ||
| [Unnamed Dataset 5] | ||
| [Unnamed Dataset 6] | ||
| [Unnamed Dataset 7] | ||
| [Unnamed Dataset 8] | ||
| [Unnamed Dataset 9] |
Also In
References
- SAE International Recommended Practice, “Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles,” SAE Standard J3016, Rev. Sept. 2016.
- Singh, S., “Critical reasons for Crashes Investigated in the National Motor Vehicle Crash Causation Survey,” Traffic Safety Facts Crash Stats, National Highway Traffic Safety Administration, Report No. DOT HS 812 115, Feb. 2015.
- National Center for Statistics and Analysis, “2015 Motor Vehicle Crashes: Overview,” Traffic Safety Facts Research Note, National Highway Traffic Safety Administration, Report No. DOT HS 812 318, Aug. 2016.
- Fagnant, D., and Kockelman K., “Preparing a Nation for Autonomous Vehicles: Opportunities, Barriers and Policy Recommendations,” Transportation Research Part A: Policy and Practice 77 (2015): 167-181, 2015, doi:10.1016/j.tra.2015.04.003.
- Blincoe, L., Seay, A., Zaloshnja, E., Miller, T., Romano, E., Luchter, S., and Spicer, R., “The Economic Impact of Motor Vehicle Crashes, 2000,” National Highway Traffic Safety Administration, Report No. DOT HS 809 446, May 2016.
- Fertuck, D., Feldmaier, R., and Hurtado, M., “The Technology of Automated and Connected Vehicles,” http://www.matecnetworks.org/webinars/pdf/CAAT%20Webinar%20August%202015%20with%20Valeo%20Final_8-26-15.pdf, accessed on Aug. 2015.
- Litman, T., “Autonomous Vehicle Implementation Predictions: Implications for Transport Planning,” Presentation at 2015 Transportation Research Board Annual Meeting, Jan. 2015.
- Casner, S., Hutchins, E., and Norman D., “The Challenges of Partially Automated Driving,” Communications of the ACM Magazine 59 (5): 70-77, 2016, doi:10.1145/2830565.
- Foundation for Traffic Safety, “Aggressive Driving: Research Update,” https://www.aaafoundation.org/sites/default/files/AggressiveDrivingResearchUpdate2009.pdf, accessed Apr. 2009.
- Tasca, L., “A review of the literature on aggressive driving research,” Aggressive Driving Issues Conference, 2000.
- Nillson, J., “Safe Transitions to Manual Driving from Faulty Automated Driving System,” Ph.D. thesis, Department of Signals and Systems, Mechatronics, Chalmers University of Technology, Göteborg, 2014.
- International Organization for Standardization, “Transport Information and Control systems - Adaptive Cruise Control systems - Performance requirements and test procedures,” ISO Standard 15622, Apr. 2010.
- Avizienis, A., Laprie, J., Randell, B., and Landwehr, C., “Basic concepts and taxonomy of dependable and secure computing” IEEE Transactions on Dependable and Secure Computing 1 (1): 11-33, 2004, doi:10.1109/TDSC.2004.2.
- Spooner, J., and Passino, K., “Fault-Tolerant Control for Automated Highway Systems” IEEE Transactions on Vehicular Technology 46 (3): 770-785, 1997, doi:10.1109/25.618202.
- Kalra, N., and Paddock, S., “Driving to Safety: How Many Miles of Driving Would It Take to Demonstrate Autonomous Vehicle Reliability?,” RAND Corporation, 2016, doi:10.7249/rr1478.
- Waeltermann, P., “Hardware-in-the-Loop: The Technology for Testing Electronic Controls in Automotive Engineering,” 6th Paderborn Workshop on Designing Mechatronic Systems, 2009.
- Joshi, A., "Real-Time Implementation and Validation for Automated Path Following Lateral Control Using Hardware-in-the-Loop (HIL) Simulation," SAE Technical Paper 2017-01-1683, 2017, doi:10.4271/2017-01-1683.
- Khan, J., "A Standardized Process Flow for Creating and Maintaining Component Level Hardware in the Loop Simulation Test Bench," SAE Technical Paper 2016-01-0052, 2016, doi:10.4271/2016-01-0052.
- Lamberg, K., and Waeltermann P., “Using HIL Simulation to Test Mechatronic Components in Automotive Engineering,” 2nd Congress on Mechatronics in Automobiles, Nov. 2000
- Chan, B., “Framework for Developing Active Safety System for Commercial Vehicles,” Presentation at 2016 dSPACE Technology Conference, Sept. 2016.
- Kohl, S., Lamberg, K., Otterbach, R., and Stroop, J., “Simulation, implementation and testing of distributed, time-controlled vehicle systems,” IAV Symposium, 2003.
- Otterbach, R., and Kohl, S., “Efficient Function and Software Development,” 2nd Paderborn Workshop on Intelligent Mechatronic Systems, 2004.
- Freund, E., and Mayr R., “Nonlinear Path Control in Automated Vehicle Guidance,” IEEE Transactions on Robotics and Automation 13 (1): 49-60, 1997, doi:10.1109/70.554346.
- Sha, L., “Using simplicity to control complexity,” IEEE Software 18 (4): 20-28, 2001, doi:10.1109/MS.2001.936213.
- Boran, C. “Bringing Autonomous Vehicles into Production: An Automotive OEM Perspective,” 3rd Automated Vehicles Symposium, 2016.
- Shen, S., “Quantifying Drivers' Responses to Failures of Semi-Autonomous Vehicle Systems,” Ph.D. thesis, Department of Industrial Engineering, Clemson University, Clemson, 2016.
- Clark, H., and Feng, J., “Semi-Autonomous Vehicles: A Closer Look at the Take-Over,” 2015 International Annual Meeting of the Human Factors and Ergonomics Society, 2015.
- Trimble, T., Bishop, R., Morgan, J., and Blanco, M., “Human factors evaluation of level 2 and level 3 automated driving concepts: Past research, state of automation technology, and emerging system concepts,” National Highway Traffic Safety Administration, Report No. DOT HS 812 043, Jul. 2014.
- National Highway Traffic Safety Administration, “Preliminary statement of policy concerning automated vehicles,” http://www.nhtsa.gov/staticfiles/rulemaking/pdf/Automated_Vehicles_Policy.pdf, accessed on May 2013.
- Norman, D., “The ‘Problem’ with Automation: Inappropriate Feedback and Interaction, not ‘Over-Automation’,” Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences 327 (1241): 585-593, 1990.
- Sarter, N., and Woods, D., “How in the World Did We Ever Get into That Mode? Mode Error and Awareness in Supervisory Control,” Human Factors: The Journal of the Human Factors and Ergonomics Society 37(1): 5-19,1995
- Ziegler, W., Franke, U., Renner, G., and Kühnle, A., "Computer Vision on the Road: A Lane Departure and Drowsy Driver Warning System," SAE Technical Paper 952256, 1995, doi:10.4271/952256.
- Motoyama, S., Ohta, T., Watanabe, T., and Ito, Y., “Development of lane departure warning system,” 7th ITS World Congress, 2000
- Suzuki, K., and Jansson, H. (2003). “An analysis of driver’s steering behavior during auditory or haptic warnings for the designing of lane departure warning system,” JSAE review 24(1), 65-70, 2003, doi: 10.1016/S0389-4304(02)00247-3.
- Information Resources Management, “Software Design and Development: Concepts, Methodologies, Tools, and Applications,” (IGI Global, 2013), 310-334, ISBN:1466643013
- Mechanical Simulation Corporation “CarSim/TruckSim/BikeSim Real-Time Hardware in the Loop,” http://www.ishinho.com/product/data/CarSimRT_Presentation.pdf