EEG, EOG, Likert Scale, and Interview Approaches for Assessing Stressful Hazard Perception Scenarios

Abstract

This study aimed to detect stressful hazard perception scenarios subjectively and objectively when using intelligent driving systems. We used electrooculography (EOG), electroencephalography (EEG), subjective ratings, and interviews to identify potential stressful hazard perceptions and record improvements in an intelligent navigation-guided pilot (NGP) system. Moreover, we analyzed electrophysiological data. Our study contributes to the use of engagement, concentration, and phase locking value connectivity based on EEG to support previous research methodologies using beta power, pupil size, fixation ratio, fixation duration, and subjective evaluations for investigating hazard perception. Our analyses showed that stressful hazard perception scenarios occurred mainly when encountering broken and solid lines, frequent lane changes, cars approaching suddenly, several cars driving in parallel, and the decision to change lanes but immediately pulling back upon using the NPG system. Our findings shed light on obtaining accurate results based on subjective and objective evaluations for developing intelligent driving systems.

Keywords:

• Electroencephalography
• electrooculography
• intelligent navigation system
• stress
• hazard perception
• subjective evaluation

Acknowledgments

Firstly, we would like to thank the psychology expert and teacher Meng Li, who explained the relationship between stress emotion and hazard perception in the driving context. Secondly, we would also like to thank Jakob Sajovic from ResearchGate, who answered the question about calculating the average power for all electrodes in a given band. Thirdly, we want to thank Shanghai Jiao Tong University for offering the experiments set up to execute and fund the experiment. Fourthly, this work was also funded by the Research Funds of China Disabled Persons’ Federation and SAIC Motor Corporation. Fifthly, we would like to thank Xpeng for creating the NGP intelligent system and helping drivers to have better UX in their daily driving life, which supports us in the experimental design, research findings, and results. Finally, we thank all my friends and colleagues at the university and industry who contributed to the research experiments.

Disclosure statement

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

Data availability statement

Rui, Zhepeng; Li, Yahong; Dong, Zhanxun; Hao, Lingyu; Chen, Bingliang; Chang, Fangyuan; Gu, Zhenyu (2024), “Data for: EEG, EOG, Likert-Scales and Interview Approaches for Assessing Stressful Hazard-Perception Scenarios”, Mendeley Data, V3, doi: 10.17632/dmkvdh2pc7.3. URL: https://data.mendeley.com/datasets/dmkvdh2pc7/3

Additional information

Funding

This research was funded by the Design School Innovation Grant [grant number WH102243005/201/004].

Notes on contributors

Zhepeng Rui

Zhepeng Rui earned Bachelor’s and Master’s degrees in Design Computing, Interaction Design, and Electronic Art from the University of Sydney. He finished his PhD at Shanghai Jiao Tong University. In his four years of industry experience, he has managed intelligent vehicle systems. His research covers HCI, user-centric marketing, and neuroscience.

Yahong Li

Yahong Li, a PhD candidate at Shanghai Jiao Tong University’s School of Design, holds a Bachelor’s in Industrial Design from Jiangnan University. Her focus is Emotion Recognition and Interaction Design for advancing next-generation intelligent living and human-machine collaboration.

Zhanxun Dong

Zhanxun Dong, an associate professor at Shanghai Jiao Tong University’s School of Design, holds a PhD in digital art and design from Zhejiang University. He serves as the head of the Design Department and is a doctoral supervisor. His research interests include Applied Ergonomics, Interaction design for XR.

Lingyu Hao

Lingyu Hao is currently a master’s student in International Industrial Design Engineering at Shanghai Jiao Tong University. Her research interests include product styling aesthetics, human-product interaction design, multi-sensory interaction design, and human and nature integration product design.

Bingliang Chen

Bingliang Chen is currently a master’s student in Design Engineering at Shanghai Jiaotong University. He received his bachelor’s degree from the East China University of Science and Technology in 2021. His research interests include User Experience Design, human-computer interaction, user-centered design, and multisensory design.

Fangyuan Chang

Fangyuan Chang is a postdoc fellow at the Department of Design at Shanghai Jiao Tong University. She received her PhD in Technology in Health Care from KTH Royal Institute of Technology. Her research interests include human-computer interaction, user research, ergonomics, and gerontechnology design.

Zhenyu Gu

Zhenyu Gu, a design professor at Shanghai Jiao Tong University’s School of Design, holds a PhD from Hong Kong Polytechnic University. He serves as the director of the industrial and interactive design committee. His research spans industrial and interactive design, design computing, and cognitive intelligent product design.