Face and Content Validity of an Automated Vehicle Road Course and a Corresponding Simulation Scenario

Classen, Sherrilene; Wersal, James; Mason, Justin; Rogers, Jason; Sisiopiku, Virginia · 2020 · Crossref

DOI: 10.3389/ffutr.2020.596620

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Summary

This study addresses the need to validate driving simulator scenarios as accurate substitutes for real-world automated vehicle (AV) experiences. As AV technology expands, simulators offer a safe environment for research, but their utility depends on environmental congruence with actual on-road routes. The authors aimed to assess the face and content validity of a high-fidelity simulator scenario designed to replicate a specific on-road automated shuttle route, ensuring the virtual environment adequately represents the physical reality for user perception studies. The methodology involved comparing a real-world route traveled by a Transdev EasyMile EZ10 automated shuttle in Gainesville, Florida, with a corresponding scenario in an RTI RDS-2000 driving simulator. Face validity was evaluated through facilitated discussions with seven members of the University of Florida’s Institute for Mobility, Activity, and Participation, who reviewed video clips and presentations of both routes. Content validity was assessed using a 17-item survey administered to seven national experts from diverse fields, including engineering, psychology, and rehabilitation science. Experts rated the congruence between the simulator and the on-road route on a 3-point Likert scale, focusing on traffic, environment, hazards, and fidelity. Face validity analysis identified five major themes: traffic conditions, environmental conditions, hazards, physical/emotional fidelity, and other recommendations. Based on this feedback, the researchers implemented six specific enhancements to the simulator scenario, including diversifying pedestrian demographics, adding jaywalking behaviors, adjusting building heights, and improving crosswalk signage. Content validity results yielded a scale content validity index (S-CVI) of 0.83, exceeding the acceptable threshold of 0.80. However, item-level analysis revealed lower ratings for traffic flow (I-CVI = 0.57) and seat direction (I-CVI = 0.67), prompting further refinements to address these discrepancies. The study concludes that while automated vehicle on-road routes can be effectively replicated in driving simulators, achieving reasonable accuracy requires a rigorous process of examining face and content validity and iteratively refining the scenario. The findings highlight that simulators are viable tools for AV research but must undergo careful validation to ensure environmental congruence, particularly regarding dynamic elements like traffic and pedestrian behavior. This work provides a framework for establishing the validity of simulator scenarios, supporting their use in studying user acceptance and adoption practices for automated mobility.

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Topics

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• simulator validity fidelity
• simulator training transfer
• simulator sickness
• situational awareness

Information type

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