Can we Use Smart Phone on a Moving Vehicle Without Worrying About Carsickness? Developing an Effective Motion Cue APP with Driving Simulator and Real Vehicle Experiments

Abstract

The prevalence of motion sickness among passengers using personal electronic devices, such as smartphones, during vehicle journeys has become a growing concern. This issue is expected to intensify with the increasing adoption of assistant or automated driving functions, which may lead to non-driving tasks (NDT) being performed by all on-board passengers, including the user in the “driver” seat during conditionally or fully automated driving modes. This trend presents challenges related to motion sickness, particularly in terms of specific performance requirements for non-driving tasks. In response to the need to alleviate passenger motion sickness, we have developed an easy-to-understand animation cue app that can be conveniently implemented on smartphones. The motion cue conveys information about vehicle accelerations, including their directions and magnitudes, using the metaphors of traffic signal colors and backward-moving lane lines, either in straight or curved lane driving. Following several rounds of improvements based on moving-base simulator and real car experiments, finally a successful cue design was found, which could significantly alleviate motion sickness of passengers while engaging in NDT, with minimal impact on their NDT performances. However, the study also revealed limitations to the sickness-alleviating capability of our motion cue design, including potential lack of universal acceptance among different users and reduced effectiveness in severely uncomfortable driving conditions. This work may provide valuable insights for further visual cue improvements that can contribute in future carsickness-proof vehicles.

Keywords:

• Motion sickness
• non-driving tasks
• sickness mitigation
• visual cue
• driving simulator
• real car experiment

Ethical approval

This work involved human subjects in its research. Approval of all ethical and experimental procedures and protocols was granted by ZJU College of Biomedical Engineering & Instrument Science Ethical Committee (2022-35).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 52372421; in part by the Department of Science and Technology of Zhejiang under Grant 2022C01241 and Grant 2023C01238. The experimental works were supported by the Engineering Innovation and Training Center in Polytechnic Institute of Zhejiang University.

Notes on contributors

Daofei Li

Daofei Li is an Associate Professor at Zhejiang University and directs the Research Group of Human-Mobility-Automation. His research interests include vehicle dynamics and control, driver model, autonomous driving and motion sickness mitigation. He holds a Bachelor degree from Jilin University (2003) and PhD from Shanghai Jiao Tong University (2008).

Binbin Tang

Binbin Tang is pursuing his master’s degree in Power Engineering at Zhejiang University. His research interests include autonomous driving and ride comfort. He holds a Bachelor degree from Zhejiang University (2022).

Tingzhe Yu

Tingzhe Yu is pursuing his master’s degree in Power Engineering at Zhejiang University. His research interests include autonomous driving and carsickness mitigation. He holds a Bachelor degree from Huazhong University of Science and Technology (2022).

Linhui Chen

Linhui Chen is pursuing his master’s degree in Power Engineering at Zhejiang University. His research interests include autonomous driving and driver model. He holds a Bachelor degree from Zhejiang University (2021).

Keyuan Zhou

Keyuan Zhou is a senior human factors engineer at OPPO Research Institute. His research area is mainly in the usability evaluation of consumer electronics products. He holds a Bachelor‘s degree from Tsinghua University and a Master’s degree from Purdue University.

Nan Qie

Nan Qie is a senior human factors engineer at OPPO, PhD in human factors engineering, membership of HFES. She has 10+ years of experience in human factors research and has published 20+ papers. Her research interests include smart terminal HCI, multimodal interaction, human-centered AI, physiological measures of emotion, etc.

Yilei Shi

Yilei Shi previously worked at OPPO Research Institute, holding the position of Senior HCI Engineer. He is currently an Associate Professor at Northwestern Polytechnical University, China, where he is engaged in research focusing on Computer 3D Vision and AIGC. He obtained his PhD from the University of Auckland in 2021.

Cheng Lu

Cheng Lu previously worked as a Human Factors Engineer at OPPO Research Institute. He is currently with RayNeo, an AR startup backed by TCL. He holds a Master’s degree in Computer Science from University of Toronto. His research interests focus on ergonomics, visual comfort, and the wearability of AR glasses.

Haimo Zhang

Haimo Zhang is director of the HCI & Human Factors Lab in OPPO Research Institute, where they apply advanced interaction technologies and knowledge about human to improve user experiences in existing and emerging usage scenarios. He received his PhD (2015) and Bachelor’s (2009) degrees at the National University of Singapore.