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.

The mass adoption of automated vehicles in the near future will benefit safety (of occupants and pedestrians), the environment (low emissions), and society (accessibility, on-demand travel). There are, however, still challenges that need to be addressed, with one of the most crucial being motion sickness. In automated vehicles, the interior could be transformed into a living room or a working space, allowing occupants to spend their time with non-driving activities. These changes are likely to provoke, and increase, motion sickness incidence. To that end, this workshop will explore the current state of motion sickness detection and mitigation methods from different angles (e.g., closed-loop detection, multimodal motion cues,etc.) through expert talks and reflections, followed by discussions. The workshop will develop an agenda for motion sickness research in automated vehicles, facilitate new research ideas and fruitful collaborations.