• Title/Summary/Keyword: cascade extended Kalman filter

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Vehicle Dynamics and Road Slope Estimation based on Cascade Extended Kalman Filter (Cascade Extended Kalman Filter 기반의 차량동특성 및 도로종단경사 추정)

  • Kim, Moon-Sik;Kim, Chang-Il;Lee, Kwang-Soo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.9
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    • pp.208-214
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    • 2014
  • Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

A Study on the Vehicle Dynamics and Road Slope Estimation (차량동특성 및 도로경사도 추정에 관한 연구)

  • Kim, Moon-Sik
    • Journal of the Korean Society of Industry Convergence
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    • v.22 no.5
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    • pp.575-582
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    • 2019
  • Advanced driving assist system can support safety of driver and passengers which may require vehicle dynamics states as well as road geometry. It is essential to have in real-time estimation of related variables and parameters. Among the road geometry parameters, road slope angle which can not be measured is essential parameter in pose estimation, adaptive cruise control and others on sag road. In this paper, Kalman filter based method for the estimation of the vehicle dynamics and road slope angle using a nonlinear vehicle model is proposed. It uses a combination of Kalman filter as Cascade Extended Kalman Filter. CEKF uses measured vehicle states such as yaw rate, longitudinal/lateral acceleration and velocity. Unknown vehicle parameters such as center of gravity and inertia are obtained by 2 D.O.F lateral model and experimentally. Simulation and Experimental tests conducted with commercialized vehicle dynamics model and real-car.