International Journal of Automotive Technology

, Volume 19, Issue 6, pp 993–1000 | Cite as

Estimation of Road Bank Angle and Vehicle Side Slip Angle Using Bayesian Tracking and Kalman Filter Approach

  • Minje Hyun
  • Wanki ChoEmail author


A lateral acceleration is considered to be a significant sensor signal for an estimation of a side slip angle. Due to the fact that a characteristic of a lateral G sensor, the sensor has a technical issue when a road bank angle has presented. In order to resolve the issue, this paper describes a novel method for the real time estimation of a vehicle side slip angle and a road bank angle simultaneously. A Bayesian tracking approach is used to estimate the road bank angle by comparing a measured lateral acceleration with the calculated one in the case of various angle. A Kalman Filter has been implemented through bicycle model using vehicle roll angle, road bank angle and angular velocity of side slip angle. The performance of the proposed estimation method has been evaluated via vehicle tests on a real road.

Key Words

Vehicle side slip angle Road bank angle Bayesian tracking Kalman-filter 



measured lateral acceleration


longitudinal velocity


mass of vehicle


side-slip angle


side-slip angular velocity


yaw rate


front cornering stiffness


rear cornering stiffness


distance from center of mass to front axle


distance from center of mass to rear axle


roll inertia


yaw inertia


front steering angle


system matrix


input matrix


roll angle


bank angle


gravitational acceleration


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Copyright information

© The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Intelligent Vehicle Safety System Development TeamHyundai Kia Motors R&D CenterGyeonggiKorea

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