Li, WenboTan, RuichenXing, YangLi, GuofaLi, ShenZeng, GuanzhongWang, PeizhiZhang, BingbingSu, XinyuPi, DaweiGuo, GangCao, Dongpu2022-08-182022-08-182022-08-06Li W, Tan R, Xing Y, et al., (2022) A multimodal psychological, physiological and behavioural dataset for human emotions in driving tasks, Scientific Data, Volume 9, 2022, Article number 4812052-4463https://doi.org/10.1038/s41597-022-01557-2https://dspace.lib.cranfield.ac.uk/handle/1826/18332Human emotions are integral to daily tasks, and driving is now a typical daily task. Creating a multi-modal human emotion dataset in driving tasks is an essential step in human emotion studies. we conducted three experiments to collect multimodal psychological, physiological and behavioural dataset for human emotions (PPB-Emo). In Experiment I, 27 participants were recruited, the in-depth interview method was employed to explore the driver’s viewpoints on driving scenarios that induce different emotions. For Experiment II, 409 participants were recruited, a questionnaire survey was conducted to obtain driving scenarios information that induces human drivers to produce specific emotions, and the results were used as the basis for selecting video-audio stimulus materials. In Experiment III, 40 participants were recruited, and the psychological data and physiological data, as well as their behavioural data were collected of all participants in 280 times driving tasks. The PPB-Emo dataset will largely support the analysis of human emotion in driving tasks. Moreover, The PPB-Emo dataset will also benefit human emotion research in other daily tasks.enAttribution 4.0 Internationalelectroencephalogram measurementdriving behaviour measurementface expression, body gesture and road scenario measurementemotion and personalityelectroencephalography (EEG)driving simulatorvisual observation methodself-reported scaleArticle