IMU based method estimates vehicle sideways motion accurately and robustly
IMU-Centric Moving Horizon Estimation for Lateral Dynamics Estimation Across Vehicles and Grip Conditions
Robotics
Summary
Measuring how fast a car moves sideways is tricky because special sensors are expensive and hard to use. The authors introduce a new way to estimate this sideways speed using only inertial sensors already on most cars, plus existing signals. They show this works well for both human-driven sports cars and autonomous race cars, even when road grip changes. Their method doesn't need extra expensive sensors or detailed knowledge about tires to give accurate estimates.
What this means in practice
- •For automotive stability engineers: Estimate precise sideways vehicle motion without costly sensors to improve vehicle stability control systems.
- •For autonomous vehicle developers: Use onboard inertial sensors to accurately track lateral dynamics across different vehicles and grip conditions for better driving control.
Authors
Seuffo Akouan ha Ngoune, Alessandro Toschi, Paolo Burgio, Marko Bertogna
Abstract
Accurate estimation of lateral vehicle dynamics near the adhesion limit is important for stability control and high-performance driving, but lateral velocity is rarely measured directly because sensors such as optical sensors are costly. This paper presents an inertial measurement unit (IMU)-centric Moving Horizon Estimation framework that reconstructs lateral velocity using standard onboard signals, without relying on exteroceptive odometry or detailed tire-parameter tuning. Experimental validation on human-driven sports cars and an autonomous open-wheel race car across tracks, maneuvers, and conditions demonstrates accurate and robust lateral velocity and lateral acceleration estimates. The proposed framework is available at https://github.com/Aseuffo/IMU-Centric-MHE