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      IMU-Based Automated Vehicle Slip Angle and Attitude Estimation Aided by Vehicle Dynamics †

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          Abstract

          The slip angle and attitude are vital for automated driving. In this paper, a systematic inertial measurement unit (IMU)-based vehicle slip angle and attitude estimation method aided by vehicle dynamics is proposed. This method can estimate the slip angle and attitude simultaneously and autonomously. With accurate attitude, the slip angle can be estimated precisely even though the vehicle dynamic model (VDM)-based velocity estimator diverges for a short time. First, the longitudinal velocity, pitch angle, lateral velocity, and roll angle were estimated by two estimators based on VDM considering the lever arm between the IMU and rotation center. When this information was in high fidelity, it was applied to aid the IMU-based slip angle and attitude estimators to eliminate the accumulated error correctly. Since there is a time delay in detecting the abnormal estimation results from VDM-based estimators during critical steering, a novel delay estimation and prediction structure was proposed to avoid the outlier feedback from vehicle dynamics estimators for the IMU-based slip angle and attitude estimators. Finally, the proposed estimation method was validated under large lateral excitation experimental tests including double lane change (DLC) and slalom maneuvers.

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          Most cited references31

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          Orientation Estimation Using a Quaternion-Based Indirect Kalman Filter With Adaptive Estimation of External Acceleration

          Young Suh (2010)
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            Integrating INS Sensors With GPS Measurements for Continuous Estimation of Vehicle Sideslip, Roll, and Tire Cornering Stiffness

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              An innovative information fusion method with adaptive Kalman filter for integrated INS/GPS navigation of autonomous vehicles

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                24 April 2019
                April 2019
                : 19
                : 8
                : 1930
                Affiliations
                School of Automotive Studies, Tongji University, Shanghai 201804, China; luyishi_ysu@ 123456163.com (Y.L.); liuwei_ev@ 123456163.com (W.L.); letiangao_515@ 123456126.com (L.G.); songshunhui@ 123456foxmail.com (S.S.); yanqun_han@ 123456163.com (Y.H.); yuzhuoping@ 123456tongji.edu.cn (Z.Y.)
                Author notes
                [†]

                This paper is an extended version of our paper: “Automated vehicle attitude and lateral velocity estimation using a 6-D IMU aided by vehicle dynamics” published in the Proceedings of the 2018 IEEE Intelligent Vehicles Symposium (IV), Changshu, China, 26–30 June 2018.

                Article
                sensors-19-01930
                10.3390/s19081930
                6515323
                31022929
                319d5e8f-62a8-4bf0-a201-eb99f1caa885
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 23 March 2019
                : 22 April 2019
                Categories
                Article

                Biomedical engineering
                sensor data fusion,slip angle estimation,attitude estimation,adaptive kalman filter

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