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Localization Method for Autonomous Vehicles with Sensor Fusion Using Extended and Unscented Kalman Filters
Technical Paper
2021-01-5089
ISSN: 0148-7191, e-ISSN: 2688-3627
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Automotive Technical Papers
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English
Abstract
This paper presents the design and experimental validation of a localization method for autonomous driving. The investigated method proposes and compares the application of the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) to the sensor fusion of onboard data streaming from a Global Positioning System (GPS) sensor and an Inertial Navigation System (INS). In the paper, the design of the hardware layout and the proposed software architecture is presented. The method is experimentally validated in real time by using a properly instrumented all-wheel-drive electric racing vehicle and a compact Sport Utility Vehicle (SUV). The proposed algorithm is deployed on a high-performance computing platform with an embedded Graphical Processing Unit that is mounted on board the considered vehicles. The reported experimental results include the outcomes of the localization algorithm at submeter accuracy and the estimated vehicle’s states for the retained single-track vehicle model that is exploited for further control strategies. The experimental results show a substantial equivalence of the application of the two filters. Nevertheless, the UKF-based method is characterized by a significantly lower estimation variance in the localization task, thus providing more robust results.
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Feraco, S., Favelli, S., Tonoli, A., Bonfitto, A. et al., "Localization Method for Autonomous Vehicles with Sensor Fusion Using Extended and Unscented Kalman Filters," SAE Technical Paper 2021-01-5089, 2021, https://doi.org/10.4271/2021-01-5089.Data Sets - Support Documents
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References
- Luettel , T. , Himmelsbach , M. , and Wuensche , H.J. Autonomous Ground Vehicles—Concepts and a Path to the Future Proceedings of the IEEE 100 Special Centennial Issue 2012 1831 1839
- Fraedrich , E. and Lenz , B. Automated Driving: Individual and Societal Aspects Transportation Research Record 2416 1 2014 64 72
- Ziebinski , A. , Cupek , R. , Grzechca , D. , and Chruszczyk , L. Review of Advanced Driver Assistance Systems (ADAS) AIP Conference Proceedings 1906 1 2017 120002
- Bonfitto , A. , Feraco , S. , Tonoli , A. , and Amati , N. Combined Regression and Classification Artificial Neural Networks for Sideslip Angle Estimation and Road Condition Identification Vehicle System Dynamics 58 11 2020 1766 1787
- Luciani , S. , Bonfitto , A. , Amati , N. , and Tonoli , A. Comfort-Oriented Design of Model Predictive Control in Assisted and Autonomous Driving International Design Engineering Technical Conferences and Computers and Information in Engineering Conference St. Louis, MO 2020 83938 V004T04A008
- Hörl , S. , Ciari , F. , and Axhausen , K.W. Recent Perspectives on the Impact of Autonomous Vehicles Arbeitsberichte Verkehrs-und Raumplanung 1216 2016 5 18
- Kaur , K. and Rampersad , G. Trust in Driverless Cars: Investigating Key Factors Influencing the Adoption of Driverless Cars Journal of Engineering and Technology Management 48 2018 87 96
- Kuutti , S. , Fallah , S. , Katsaros , K. , Dianati , M. et al. A Survey of the State-of-the-Art Localization Techniques and Their Potentials for Autonomous Vehicle Applications IEEE Internet of Things Journal 5 2 2018 829 846
- Woo , A. , Fidan , B. , and Melek , W.W. Localization for Autonomous Driving Handbook of Position Location: Theory, Practice, and Advances 2nd ed. Hoboken, NJ Wiley 2018 1051 1087
- Leonard , J.J. and Durrant-Whyte , H.F. Mobile Robot Localization by Tracking Geometric Beacons IEEE Transactions on Robotics and Automation 7 3 1991 376 382
- Feraco , S. , Bonfitto , A. , Khan , I. , Amati , N. et al. Optimal Trajectory Generation Using an Improved Probabilistic Road Map Algorithm for Autonomous Driving International Design Engineering Technical Conferences and Computers and Information in Engineering Conference Anaheim, CA (USA) 2020 83938 V004T04A006
- Feraco , S. , Luciani , S. , Bonfitto , A. , Amati , N. et al. A Local Trajectory Planning and Control Method for Autonomous Vehicles Based on the RRT Algorithm 2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE) Torino, Italy 2020 1 6
- Formula Student Germany 2019 https://www.formulastudent.de/fileadmin/user_upload/all/2019/rules/FSG19_Competition_Handbook_v1.0.pdf
- Marin-Plaza , P. , Hussein , A. , Martin , D. , and Escalera , A.D.L. Global and Local Path Planning Study in a ROS-Based Research Platform for Autonomous Vehicles Journal of Advanced Transportation 2018
- Kabzan , J. , Valls , M.I. , Reijgwart , V.J. , Hendrikx , H.F. et al. Amz Driverless: The Full Autonomous Racing System Journal of Field Robotics 37 7 2020 1267 1294
- Nekkah , S. , Janus , J. , Boxheimer , M. , Ohnemus , L. et al. 2020
- Zeilinger , M. , Hauk , R. , Bader , M. , and Hofmann , A. Design of an Autonomous Race Car for the Formula Student Driverless (FSD) Oagm & Arw Joint Workshop Wien, Austria 2017
- Chen , T. , Li , Z. , He , Y. , Xu , Z. 2019
- Cadena , C. , Carlone , L. , Carrillo , H. , Latif , Y. et al. Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age IEEE Transactions on Robotics 32 6 2016 1309 1332
- Ferreira , J.V. Sensor Fusion Tests for an Autonomous Vehicle, Using Extended Kalman Filter Journal of Engineering Science and Technology Review 11 3 2018 1 8
- Meng , X. , Wang , H. , and Liu , B. A Robust Vehicle Localization Approach Based on gnss/imu/dmi/Lidar Sensor Fusion for Autonomous Vehicles Sensors 17 9 2017 2140
- Lin , M. , Yoon , J. , and Kim , B. Self-Driving Car Location Estimation Based on a Particle-Aided Unscented Kalman Filter Sensors 20 9 2020 2544
- D’Alfonso , L. , Lucia , W. , Muraca , P. , and Pugliese , P. Mobile Robot Localization via EKF and UKF: A Comparison Based on Real Data Robotics and Autonomous Systems 74 2015 122 127
- Konatowski , S. , Kaniewski , P. , and Matuszewski , J. Comparison of Estimation Accuracy of EKF, UKF and PF Filters Annual of Navigation 23 2016 69 87
- Xue , Z. and Schwartz , H. A Comparison of Several Nonlinear Filters for Mobile Robot Pose Estimation 2013 IEEE International Conference on Mechatronics and Automation Takamatsu, Japan 2013 1087 1094
- Allotta , B. , Chisci , L. , Costanzi , R. , Fanelli , F. et al. A Comparison between EKF-Based and UKF-Based Navigation Algorithms for AUVs Localization OCEANS 2015 Genova 2015 1 5
- Khan , I. , Feraco , S. , Bonfitto , A. , and Amati , N. A Model Predictive Control Strategy for Lateral and Longitudinal Dynamics in Autonomous Driving ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference Virtual Conference 2020
- Amer , N. , Zamzuri , H. , Hudha , K. , and Kadir , Z. Modelling and Control Strategies in Path Tracking Control for Autonomous Ground Vehicles: A Review of State of the Art and Challenges Journal of Intelligent & Robotic Systems 86 2017 225 254
- Feraco , S. , Bonfitto , A. , Amati , N. , and Tonoli , A. Combined Lane Keeping and Longitudinal Speed Control for Autonomous Driving International Design Engineering Technical Conferences and Computers and Information in Engineering Conference Anaheim, CA (USA) 2019 59216 V003T01A018
- Kiencke , U. and Nielsen , L. Automotive Control Systems: For Engine, Driveline, and Vehicle Berlin Springer 2000
- Rajamani , R. Vehicle Dynamics and Control New York Springer Science & Business Media 2011
- Barshan , B. and Durrant-Whyte , H.F. Inertial Navigation Systems for Mobile Robots IEEE Transactions on Robotics and Automation 11 3 1995 328 342
- Lazarou , T. and Danezis , C. Assessment of Modern Smartphone Sensors Performance on Vehicle Localization in Urban Environments Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017) Paphos, Cyprus 2017 10444 104441S
- Moore , T. and Stouch , D. A Generalized Extended Kalman Filter Implementation for the Robot Operating System Intelligent Autonomous Systems 13 Cham Springer 2016 335 348
- Thrun , S. , Burgard , W. , and Fox , D. Probabilistic Robotics Intelligent Robotics and Autonomous Agents Series Cambridge, MA The MIT Press 2006
- Särkkä , S. Bayesian Filtering and Smoothing 3 Cambridge Cambridge University Press 2013
- Bishop , G. and Welch , G. An Introduction to the Kalman Filter Proceedings of SIGGRAPH Los Angeles, CA (USA) 2001
- Zhang , B. , Chu , H. , Sun , T. , Jia , H. et al. Error Prediction for SINS/GPS after GPS Outage Based on Hybrid KF-UKF Mathematical Problems in Engineering 2015 2015 1 9
- Ali , H.F. , Mansour , N.A. , and Kim , Y. Comparative Study of Extended and Unscented Kalman Filters for Estimating Motion States of an Autonomous Vehicle-Trailer System Recent Advances in Mechanical Engineering Singapore Springer 2021 165 173
- Julier , S.J. and Uhlmann , J.K. Unscented Filtering and Nonlinear Estimation Proceedings of the IEEE 92 3 2004 401 422 https://doi.org/10.1109/JPROC.2003.823141
- Wan , E.A. and Van Der Merwe , R. The Unscented Kalman Filter for Nonlinear Estimation Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373) Lake Louise, Alberta, Canada 2000 153 158 https://doi.org/10.1109/ASSPCC.2000.882463
- Higham , N.J. Accuracy and Stability of Numerical Algorithms Society for Industrial and Applied Mathematics Philadelphia, PA (USA) 2002