Yongfeng Ma , Yaqian Xing , Ying Wu , Shuyan Chen , Fengxiang Qiao , Xiaojian Hu , Jian Lu
{"title":"Analysis of emotions of online car-hailing drivers under different driving conditions and scenarios","authors":"Yongfeng Ma , Yaqian Xing , Ying Wu , Shuyan Chen , Fengxiang Qiao , Xiaojian Hu , Jian Lu","doi":"10.1016/j.tbs.2024.100937","DOIUrl":null,"url":null,"abstract":"<div><div>Emotion is an important factor that affects driving behavior, and thus, drivers’ emotions are closely related to overall traffic safety. We investigated the emotional expressions of online car-hailing drivers under two driving conditions: with passenger(s) and without passenger(s). We recruited 16 male car-hailing drivers and collected a total of 91.5 h of data using non-contact equipment. We employed FaceReader 8.0 software to analyze the collected video data and extract the drivers’ facial expression information, thereby identifying six emotions expressed by the drivers. We then compared the frequency of the occurrence of the six emotions between the two conditions. The frequency rates indicate that the drivers exhibited more emotions when no passengers were in the vehicle. The chi-square test results indicate significant differences in the drivers’ emotions under the two conditions. For example, happiness is related to chatting with passengers. Also, the drivers exhibited more aggressive driving behavior during trips without passengers, and such behavior often was accompanied by negative emotions, such as anger. We also investigated drivers’ emotions under three scenarios that often occur while online car-hailing drivers are working: driver distractions, passenger interaction, and the traffic environment. The understanding of drivers’ emotions and the relationships between those emotions and scenarios that take place under different driving conditions can facilitate the identification of drivers’ intentions and provide guidance for the development of safe driving assistance warning systems. Dangerous driving behavior can be reduced through intervention and the monitoring of drivers’ emotions for the enhanced overall safety of roadway travel.</div></div>","PeriodicalId":51534,"journal":{"name":"Travel Behaviour and Society","volume":"38 ","pages":"Article 100937"},"PeriodicalIF":5.1000,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Travel Behaviour and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214367X2400200X","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
Emotion is an important factor that affects driving behavior, and thus, drivers’ emotions are closely related to overall traffic safety. We investigated the emotional expressions of online car-hailing drivers under two driving conditions: with passenger(s) and without passenger(s). We recruited 16 male car-hailing drivers and collected a total of 91.5 h of data using non-contact equipment. We employed FaceReader 8.0 software to analyze the collected video data and extract the drivers’ facial expression information, thereby identifying six emotions expressed by the drivers. We then compared the frequency of the occurrence of the six emotions between the two conditions. The frequency rates indicate that the drivers exhibited more emotions when no passengers were in the vehicle. The chi-square test results indicate significant differences in the drivers’ emotions under the two conditions. For example, happiness is related to chatting with passengers. Also, the drivers exhibited more aggressive driving behavior during trips without passengers, and such behavior often was accompanied by negative emotions, such as anger. We also investigated drivers’ emotions under three scenarios that often occur while online car-hailing drivers are working: driver distractions, passenger interaction, and the traffic environment. The understanding of drivers’ emotions and the relationships between those emotions and scenarios that take place under different driving conditions can facilitate the identification of drivers’ intentions and provide guidance for the development of safe driving assistance warning systems. Dangerous driving behavior can be reduced through intervention and the monitoring of drivers’ emotions for the enhanced overall safety of roadway travel.
期刊介绍:
Travel Behaviour and Society is an interdisciplinary journal publishing high-quality original papers which report leading edge research in theories, methodologies and applications concerning transportation issues and challenges which involve the social and spatial dimensions. In particular, it provides a discussion forum for major research in travel behaviour, transportation infrastructure, transportation and environmental issues, mobility and social sustainability, transportation geographic information systems (TGIS), transportation and quality of life, transportation data collection and analysis, etc.