NDLI: Vehicle position estimation using nonlinear tire model for autonomous vehicle

Content Provider	Springer Nature Link
Author	Yoon, Jae woo Kim, Byeong woo
Copyright Year	2016
Abstract	To achieve technical perfection of the Advanced driver assistant system (ADAS), accurate analysis of the vehicle’s position is essential. For this, conventionally, sensor fusion has been carried out using a general GPS and general Inertial measurement unit (IMU), but the position accuracy decreases because of inertial sensor accumulation. Furthermore, because a vehicle tire model is analyzed by linearization and using a bicycle model, the position error increases. To solve this, in this study, a fusion algorithm was proposed by using an extended Kalman filter based on the non-linear tire model for the vehicle state information and by using the general GPS position information provided by the electric stability program of the vehicle. The fusion algorithm proposed in this study allowed us to suggest a position error correction method corresponding to a high precision Differential global positioning system (DGPS) within 1 m.
Starting Page	3461
Ending Page	3468
Page Count	8
File Format	PDF
ISSN	1738494X
Journal	Journal of Mechanical Science and Technology
Volume Number	30
Issue Number	8
e-ISSN	19763824
Language	English
Publisher	Korean Society of Mechanical Engineers
Publisher Date	2016-08-19
Publisher Place	Seoul
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Autonomous vehicle Extended Kalman filter Nonlinear tire model Localization Mechanical Engineering Vibration, Dynamical Systems, Control Industrial and Production Engineering
Content Type	Text
Resource Type	Article
Subject	Mechanics of Materials Mechanical Engineering

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