This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
A Stability-Guaranteed Time-Delay Range for Feedback Control of Autonomous Vehicles
Technical Paper
2020-01-0090
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
The vehicles with level-5 autonomy (L5AVs) that have no human driver in the loop are also known as self-driving cars. L5AVs are assumed the next generation of ground transportation, which have growing attention from both industry and academia in most recent years. Most of the work related to feedback strategies of L5AVs are on developing mapping systems through a variety of sensors. These systems can be considered as an analogue to the perception and central nervous system of human drivers. For instance, innovative visualization systems are more powerful when compared to the visual perception system of a person, yet, mapping demands high computation loads. This burden causes delay in the feedback loop and thus, it might have an unfavorable influence on proper and safe control action. This study investigates the effect of time delay occurring in mapping systems on the stability of the controlled vehicle. An algorithm entitled as “Cluster Treatment of Characteristic Roots - CTCR” is used to calculate a safe delay range as a remedy for the time delay caused by mapping systems. The CTCR analysis is applied to a linearized two degree-of-freedom bicycle model for different velocities. The critical time delay values, which determines the boundary between the stability and instability of the controlled vehicle, are calculated based on the vehicle dynamics. Finally, results are drawn for a regular weave test by computer simulations, in which a non-linear vehicle model is used. The proposed approach is validated by exhibiting that a delay value outside the safe range leads the vehicle instability.
Recommended Content
Authors
Topic
Citation
Kirli, A. and Arslan, M., "A Stability-Guaranteed Time-Delay Range for Feedback Control of Autonomous Vehicles," SAE Technical Paper 2020-01-0090, 2020, https://doi.org/10.4271/2020-01-0090.Data Sets - Support Documents
Title | Description | Download |
---|---|---|
Unnamed Dataset 1 | ||
Unnamed Dataset 2 | ||
Unnamed Dataset 3 | ||
Unnamed Dataset 4 |
Also In
References
- Fagnant , D.J. and Kockelman , K. Preparing a Nation for Autonomous Vehicles: Opportunities, Barriers and Policy Recommendations Transp. Res. Part A Policy Pract. 77 167 181 2015
- Alex , D. https://www.wired.com/2017/04/detroit-stomping-silicon-valley-self-driving-car-race/ July 3, 2017
- Susan , C. http://ns.umich.edu/new/multimedia/videos/24923-driverless-shuttle-service-coming-to-u-m-s-north-campus July 3, 2017
- Bengler , K. , Dietmayer , K. , Farber , B. , Maurer , M. et al. Three Decades of Driver Assistance Systems: Review and Future Perspectives IEEE Intell. Transp. Syst. Mag. 6 4 6 22 2014
- Ulsoy , A.G. , Peng , H. , and Çakmakci , M. Automotive Control Systems 6 2012
- Shladover , S.E. Review of the State of Development of Advanced Vehicle Control Systems (AVCS) 24 6 1995
- Abraham , H. et al. May, 2016
- Schellekens , M. Self-Driving Cars and the Chilling Effect of Liability Law Comput. Law Secur. Rev. 31 4 506 517 2015
- Kalra , N. and Paddock , S.M. Driving to Safety: How Many Miles of Driving Would it Take to Demonstrate Autonomous Vehicle Reliability? Transp. Res. Part A 94 15 2016
- Lekkas , A.M. and Guidance 2014
- Ilas , C. Electronic Sensing Technologies for Autonomous Ground Vehicles: A Review 8th Int. Symp. Adv. Top. Electr. Eng. ATEE 2013 2013 0 5
- Bernini , N. , Bertozzi , M. , Castangia , L. , Patander , M. , and Sabbatelli , M. Real-Time Obstacle Detection Using Stereo Vision for Autonomous Ground Vehicles: A Survey 17th International IEEE Conference on Intelligent Transportation Systems (ITSC) 2014 1 873 878
- Kim , S. , Kim , H. , Yoo , W. , and Huh , K. Sensor Fusion Algorithm Design in Detecting Vehicles Using Laser Scanner and Stereo Vision IEEE Transactions on Intelligent Transportation Systems 17 4 1072 1084 April 2016
- Francis , S.L.X. , Anavatti , S.G. , Garratt , M. , and Shim , H. A ToF-Camera as a 3D Vision Sensor for Autonomous Mobile Robotics Int. J. Adv. Robot. Syst. 12 11 2015
- Rajamani , R. Vehicle Dynamics and Control Boston, MA Springer US 2012
- Zhang , D. , Lin , B. , Kirli , A. , and Okwudire , C. Reduction of Steering Effort in the Event of EPAS Failure Using Differential Braking Assisted Steering SAE Int. J. Trans. Saf. 5 2 2017
- Kirli , A. and Arslan , M.S. Online Optimized Hysteresis-Based Steering Feel Model for Steer-by-Wire Systems Adv. Mech. Eng. 8 7 168781401665658 Jun. 2016
- Gao , Q. , Cepeda-Gomez , R. , and Olgac , N. The Homicidal Chauffeur Problem with Multiple Time Delayed Feedback 45 14 2012
- Olgac , N. and Sipahi , R. An Exact Method for the Stability Analysis of Time-Delayed Linear Time-Invariant (LTI) Systems IEEE Trans. Automat. Contr. 47 5 793 797 2002
- Olgac , N. and Sipahi , R. The Cluster Treatment of Characterıstıc Roots and the Neutral Type Time-Delayed Systems ASME 2004 Int. Mech. Eng. Congr. Expo. 1 10 2004
- Gao , Q. 2015
- Rekasius , Z.V. A Stability Test for Systems with Delays Jt. Autom. Control Conf. 17 39 1980
- Nguyen , A.-T. , Sentouh , C. , and Popieul , J.-C. Fuzzy Steering Control for Autonomous Vehicles under Actuator Saturation: Design and Experiments Journal of the Franklin Institute 355 18 2018