Predicting Motion Incongruence Ratings in Closed-and Open-Loop Urban Driving Simulation
This paper presents a three-step validation approach for subjective rating predictions of driving simulator motion incongruences based on objective mismatches between reference vehicle and simulator motion. This approach relies on using high-resolution rating predictions of open-loop driving (participants being driven) for ratings of motion in closed-loop driving (participants driving themselves). A driving simulator experiment in an urban scenario is described, in which 42 participants participated. In the experiment’s first phase, participants actively drove themselves (i.e., closed-loop). By recording the drives of the participants and playing these back to themselves (open-loop) in the second phase, participants experienced the same motion in both phases. Participants rated the motion after each maneuver and at the end of each drive. In the third phase they again drove open-loop, but rated the motion continuously, only possible in open-loop driving. Results show that a rating model from literature can predict 70% of the measured continuous rating variance. Second, the maximum of the measured continuous ratings correlates to both the maneuver-based (P = 0.88) and overall (P = 0.70) ratings, allowing for predictions of both rating types based on the continuous rating model. Third, using Bayes’ analysis it is then shown that both the maneuver-based and overall ratings between the closed-loop and open-loop drives are equivalent. Combined, this shows that the high-resolution, open-loop continuous ratings are valid for analyzing motion in closed-loop driving simulation. Furthermore, the predictions of maneuver-based and overall ratings can be used as an accurate trade-off method of motion cueing settings.
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Submitting Author's InstitutionDelft University of Technology
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