TY - JOUR
T1 - Efficient Motion Sickness Assessment
T2 - Recreation of On-Road Driving on a Compact Test Track
AU - Harmankaya, Huseyin
AU - Brietzke, Adrian
AU - Pham Xuan, Rebecca
AU - Shyrokau, Barys
AU - Happee, Riender
AU - Papaioannou, Georgios
PY - 2025/9/19
Y1 - 2025/9/19
N2 - The ability to engage in other activities during the ride is considered by consumers as one of the key reasons for the adoption of automated vehicles. However, engagement in non-driving activities will provoke occupants’ motion sickness, deteriorating their overall comfort and thereby risking acceptance of automated driving. Therefore, it is critical to extend our understanding of motion sickness and unravel the modulating factors that affect it through experiments with participants. Currently, most experiments are conducted on public roads (realistic but not reproducible) or test tracks (feasible with prototype automated vehicles). This research study develops a method to design an optimal path and speed reference to accurately replicate on-road motion sickness exposure on a small test track. The method uses model predictive control to replicate the longitudinal and lateral accelerations collected from on-road drives on a test track of 70 m by 175 m. A within-subject experiment (47 participants) was conducted comparing the occupants’ motion sickness occurrence in test-track and on-road conditions, with the conditions being cross-randomized. The results illustrate that the subjective (reported) motion sickness is well reproduced with an insignificant reduction on the track. Meanwhile, there is an overall correspondence of individual sickness levels between on-road and test-track. This paves the path for the employment of our method for a simpler, safer and more replicable assessment of motion sickness.
AB - The ability to engage in other activities during the ride is considered by consumers as one of the key reasons for the adoption of automated vehicles. However, engagement in non-driving activities will provoke occupants’ motion sickness, deteriorating their overall comfort and thereby risking acceptance of automated driving. Therefore, it is critical to extend our understanding of motion sickness and unravel the modulating factors that affect it through experiments with participants. Currently, most experiments are conducted on public roads (realistic but not reproducible) or test tracks (feasible with prototype automated vehicles). This research study develops a method to design an optimal path and speed reference to accurately replicate on-road motion sickness exposure on a small test track. The method uses model predictive control to replicate the longitudinal and lateral accelerations collected from on-road drives on a test track of 70 m by 175 m. A within-subject experiment (47 participants) was conducted comparing the occupants’ motion sickness occurrence in test-track and on-road conditions, with the conditions being cross-randomized. The results illustrate that the subjective (reported) motion sickness is well reproduced with an insignificant reduction on the track. Meanwhile, there is an overall correspondence of individual sickness levels between on-road and test-track. This paves the path for the employment of our method for a simpler, safer and more replicable assessment of motion sickness.
KW - automated vehicles
KW - efficient assessment
KW - human experiments
KW - model predictive control
KW - Motion sickness
UR - http://www.scopus.com/inward/record.url?scp=105017176007&partnerID=8YFLogxK
U2 - 10.1109/TITS.2025.3608238
DO - 10.1109/TITS.2025.3608238
M3 - Article
AN - SCOPUS:105017176007
SN - 1524-9050
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
ER -