This paper presents the development of a steering sensor system for use in motorcycle riding simulation based on the forces acting on the handlebar. An overview of motorcycle dynamics models for riding simulation is also given. In the section Related Work, different approaches to steering a motorcycle simulator are evaluated and divided into force-based and angle-based. Based on this, a recommendation is given on how to measure and evaluate steering interaction separately on the left/right handlebar stubs. The development is described with the following subsections steps: technical development, software development and determination of the steering forces/torques based on a calibration test bench. This is followed by a validation method of the sensors and an evaluation of the ridability using this handlebar. Finally, the steering angle, the steering torque and the roll angle are compared with the previously described motorcycle riding dynamics. The evaluation of the interaction (rider control behavior) during a lane change is presented based on the applied forces on the handlebar.
In this paper, we used an isometric steering system on a motorcycle riding simulator. The investigation was done for a static and dynamic platform with an already known Motion Cueing Algorithm (MCA) from the literature. The aim was to determine whether the Standard Deviation of Lateral Position (SDLP) is suitable for evaluating ride quality. For this purpose, we implemented the already investigated MCA and compare whether the algorithm has a positive effect on the SDLP. When the MCA was used, the SDLP were reduced, but the mental workload and rider state remained the same. In addition, we used exploratory adjective pairs as a semantic differential. These also showed a positive tendency when using a dynamic platform with this MCA. This study thus showed that the SDLP is suitable as an objective criterion of riding quality in motorcycle riding simulation.
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