Simulator validation – a new methodological approach applied to motorcycle riding simulators

Will, Sebastian; Hammer, Thomas; Pleß, Raphael; Merkel, Nora Leona; Neukum, Alexandra · 2023 · Crossref

DOI: 10.59490/65c5fb14c9fa9023b6a2e622

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Summary

This paper addresses the challenge of validating motorcycle riding simulators, which are currently in an early stage of development compared to passenger car simulators. Traditional validation methods are complex, expensive, and specific to individual research questions, making them inefficient for assessing the broad applicability of new simulator concepts. The authors propose a new methodological approach that validates simulators using "minimal scenarios"—elementary, serial riding tasks such as starting from standstill or initiating a curve at constant velocity. The core assumption is that these minimal scenarios can be reorganized to represent complex riding tasks, allowing for a global assessment of a simulator’s capabilities with reduced effort. The study employed a within-subjects design comparing three test environments: a real measurement motorcycle (KTM 790 Duke), a high-fidelity dynamic simulator (DESMORI) with a 6-DOF motion platform, and a static simulator with simplified vehicle dynamics. Data were collected from two groups: six experts in motorcycle dynamics and fifteen non-professional riders. Participants performed specific maneuvers, including an avoidance task composed of minimal scenarios, while objective data (roll angle, velocity) and subjective data (workload ratings, qualitative feedback) were recorded. The minimal scenarios were derived from accident classification data to ensure practical relevance. Results indicated that the dynamic simulator provided a more realistic representation of vehicle dynamics than the static simulator. Objective data showed that roll angles in the dynamic simulator closely matched real riding patterns, whereas the static simulator produced significantly lower and less variable roll angles. However, subjective assessments revealed that the dynamic simulator induced higher perceived workload than both the static simulator and real riding. Conversely, the static simulator’s workload levels were comparable to real riding, though its physical dynamics were less accurate. Qualitative feedback confirmed that the dynamic simulator felt more natural in steering and stabilization, while the static simulator felt overly stable. The findings suggest that the minimal scenario approach effectively distinguishes between the physical and behavioral validity of different simulator setups. The method allows researchers to select appropriate simulators based on specific research needs: the static simulator is suitable for studies focusing on rider workload and distraction, while the dynamic simulator is better suited for research requiring accurate vehicle dynamics representation. The authors conclude that this approach complements existing validation methods by providing a holistic assessment of simulator characteristics, facilitating broader applicability evaluations for single-track vehicle simulators.

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Topics

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• simulator validity fidelity
• simulator training transfer

Information type

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• Methodological Resource: validation psychometrics, tool software
• Theoretical Contribution: computational model