Development and evaluation of a motorcycle riding simulator for low speed maneuvering

Research output: ThesisDissertation (TU Delft)

17 Downloads (Pure)

Abstract

Driving simulators have been extensively used over the last decades and technological advancements have propelled their development for cars, trucks and other vehicles with four (or more) wheels. This dissertation focuses on the use of driving simulators for two wheeled vehicles and in particular on the development and evaluation of a motorcycle riding simulator for low speed maneuvering. The reason to focus on low speed maneuvers is related to the unstable nature of motorcycles at low speeds. A dedicated riding simulator could be used to train riders to cope with vehicle instabilities and develop active safety systems that can help them to maintain the vehicle balanced and avoid falling. Existing riding simulators adopt simplified vehicle models to simulate motorcycle dynamics. In some cases, advanced non-linear models are adopted, but their validation is not always sufficiently described for the simulator application. Once the model has been integrated in the complete simulator, the results of its real-time simulation are used to provide feedback to the simulator rider through the cueing systems. Motion cueing is particularly interesting due to the peculiar vehicle dynamics of two wheelers. Different approaches are found in literature, however the applied motion cueing methods are not based on understanding of human motion perception. Finally, the riding simulator should also be validated for its usage in the specific application domain and its fidelity and behavioral validity are often neglected. In this thesis, specific aspects of development and validation of a riding simulator for low speed maneuvering are investigated.
Original languageEnglish
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • Happee, R., Supervisor
  • Mulder, M., Supervisor
Award date19 Apr 2021
Print ISBNs978-94-6421-323-2
DOIs
Publication statusPublished - 2021

Keywords

  • Motorcycle Dynamics
  • Riding Simulator
  • Motion Cueing
  • Motion perception

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