Similarities in steering control between cars and motorcycles: application to a low-complexity riding simulator (original) (raw)

inertia was tuned to obtain a motorcycle-like steering response. Finally, the calibrated car model was implemented into a low-complexity motorcycle simulator for objective validation. It was verified that an understeering single-track model with high yaw inertia has amplitude and phase responses analogous to a motorcycle. The experimental results of the simulator test confirmed these findings for a diverse set of manoeuvres, validating the method. This straightforward approach allows the development of low-complexity simulators with good steering fidelity, using an objective procedure to reproduce the behaviour of a chosen motorcycle class. In addition, the low computational cost of the model makes it a potential candidate for use in assistance systems. Keywords Motorcycle simulator • Car and motorcycle manoeuvrability • Car and motorcycle dynamics • Simulation • Frequency response and transfer functions • Objective and quantitative validation 1 Introduction Riding simulators are a fundamental tool for driver training and the development of assistance systems. However, the complexity of realistically simulating two-wheeled vehicles has meant that the development and adoption of motorcycle simulators have Abstract Motorcycle simulators are employed for rider training, studying human-machine interaction, and developing assistance systems. However, existing simulators are either too simple and, therefore, unsuitable or significantly complex, with higher hardware costs and familiarisation times. This study aimed to use a tuned single-track car model as the basis of a motorcycle simulator, leading to considerable software simplification while preserving its fidelity. In particular, the approach defined a conversion between motorcycle steering torque and car steering angle. It modified the parameters of the latter to reproduce the response of various motorcycle models in quasistatic and transient conditions for different speeds and radii of curvature. A robust manoeuvrability index was chosen. For the car, it was possible to calculate it from its parameters analytically. Next, the car yaw

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