{"title":"你还是我?性格特征预测意外情况下的牺牲决定。","authors":"Ju Uijong, June Kang, Christian Wallraven","doi":"10.1109/TVCG.2019.2899227","DOIUrl":null,"url":null,"abstract":"<p><p>Emergency situations during car driving sometimes force the driver to make a sudden decision. Predicting these decisions will have important applications in updating risk analyses in insurance applications, but also can give insights for drafting autonomous vehicle guidelines. Studying such behavior in experimental settings, however, is limited by ethical issues as it would endanger peoples' lives. Here, we employed the potential of virtual reality (VR) to investigate decision-making in an extreme situation in which participants would have to sacrifice others in order to save themselves. In a VR driving simulation, participants first trained to complete a difficult course with multiple crossroads in which the wrong turn would lead the car to fall down a cliff. In the testing phase, obstacles suddenly appeared on the \"safe\" turn of a crossroad: for the control group, obstacles consisted of trees, whereas for the experimental group, they were pedestrians. In both groups, drivers had to decide between falling down the cliff or colliding with the obstacles. Results showed that differences in personality traits were able to predict this decision: in the experimental group, drivers who collided with the pedestrians had significantly higher psychopathy and impulsivity traits, whereas impulsivity alone was to some degree predictive in the control group. Other factors like heart rate differences, gender, video game expertise, and driving experience were not predictive of the emergency decision in either group. Our results show that self-interest related personality traits affect decision-making when choosing between preservation of self or others in extreme situations and showcase the potential of virtual reality in studying and modeling human decision-making.</p>","PeriodicalId":13376,"journal":{"name":"IEEE Transactions on Visualization and Computer Graphics","volume":"25 5","pages":"1898-1907"},"PeriodicalIF":4.7000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TVCG.2019.2899227","citationCount":"8","resultStr":"{\"title\":\"You or Me? Personality Traits Predict Sacrificial Decisions in an Accident Situation.\",\"authors\":\"Ju Uijong, June Kang, Christian Wallraven\",\"doi\":\"10.1109/TVCG.2019.2899227\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Emergency situations during car driving sometimes force the driver to make a sudden decision. Predicting these decisions will have important applications in updating risk analyses in insurance applications, but also can give insights for drafting autonomous vehicle guidelines. Studying such behavior in experimental settings, however, is limited by ethical issues as it would endanger peoples' lives. Here, we employed the potential of virtual reality (VR) to investigate decision-making in an extreme situation in which participants would have to sacrifice others in order to save themselves. In a VR driving simulation, participants first trained to complete a difficult course with multiple crossroads in which the wrong turn would lead the car to fall down a cliff. In the testing phase, obstacles suddenly appeared on the \\\"safe\\\" turn of a crossroad: for the control group, obstacles consisted of trees, whereas for the experimental group, they were pedestrians. In both groups, drivers had to decide between falling down the cliff or colliding with the obstacles. Results showed that differences in personality traits were able to predict this decision: in the experimental group, drivers who collided with the pedestrians had significantly higher psychopathy and impulsivity traits, whereas impulsivity alone was to some degree predictive in the control group. Other factors like heart rate differences, gender, video game expertise, and driving experience were not predictive of the emergency decision in either group. Our results show that self-interest related personality traits affect decision-making when choosing between preservation of self or others in extreme situations and showcase the potential of virtual reality in studying and modeling human decision-making.</p>\",\"PeriodicalId\":13376,\"journal\":{\"name\":\"IEEE Transactions on Visualization and Computer Graphics\",\"volume\":\"25 5\",\"pages\":\"1898-1907\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/TVCG.2019.2899227\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Visualization and Computer Graphics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1109/TVCG.2019.2899227\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2019/2/25 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Visualization and Computer Graphics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/TVCG.2019.2899227","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2019/2/25 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
You or Me? Personality Traits Predict Sacrificial Decisions in an Accident Situation.
Emergency situations during car driving sometimes force the driver to make a sudden decision. Predicting these decisions will have important applications in updating risk analyses in insurance applications, but also can give insights for drafting autonomous vehicle guidelines. Studying such behavior in experimental settings, however, is limited by ethical issues as it would endanger peoples' lives. Here, we employed the potential of virtual reality (VR) to investigate decision-making in an extreme situation in which participants would have to sacrifice others in order to save themselves. In a VR driving simulation, participants first trained to complete a difficult course with multiple crossroads in which the wrong turn would lead the car to fall down a cliff. In the testing phase, obstacles suddenly appeared on the "safe" turn of a crossroad: for the control group, obstacles consisted of trees, whereas for the experimental group, they were pedestrians. In both groups, drivers had to decide between falling down the cliff or colliding with the obstacles. Results showed that differences in personality traits were able to predict this decision: in the experimental group, drivers who collided with the pedestrians had significantly higher psychopathy and impulsivity traits, whereas impulsivity alone was to some degree predictive in the control group. Other factors like heart rate differences, gender, video game expertise, and driving experience were not predictive of the emergency decision in either group. Our results show that self-interest related personality traits affect decision-making when choosing between preservation of self or others in extreme situations and showcase the potential of virtual reality in studying and modeling human decision-making.
期刊介绍:
TVCG is a scholarly, archival journal published monthly. Its Editorial Board strives to publish papers that present important research results and state-of-the-art seminal papers in computer graphics, visualization, and virtual reality. Specific topics include, but are not limited to: rendering technologies; geometric modeling and processing; shape analysis; graphics hardware; animation and simulation; perception, interaction and user interfaces; haptics; computational photography; high-dynamic range imaging and display; user studies and evaluation; biomedical visualization; volume visualization and graphics; visual analytics for machine learning; topology-based visualization; visual programming and software visualization; visualization in data science; virtual reality, augmented reality and mixed reality; advanced display technology, (e.g., 3D, immersive and multi-modal displays); applications of computer graphics and visualization.