Transportation Engineering Department, Faculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran.
Transportation Engineering Department, Faculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran.
Accid Anal Prev. 2023 Apr;183:106974. doi: 10.1016/j.aap.2023.106974. Epub 2023 Jan 31.
Recent driving behaviour theories with motivational approaches have paid considerable attention to the cognitive characteristics of the driver, especially emotions. The role of drivers' emotions in driving behaviour has been the subject of extensive research, but an important question remains: how do drivers feel in actual driving situations? In this study, we developeda questionnaire comprised of 20 different emotions, conducted an online survey, and collected the responses from 232 participants. Exploratory factor analysis (EFA) indicated a 4-factor structure. In addition, a path diagram and a confirmatory factor analysis (CFA) were constructed, and the factors were semantically named "Unease," "Fear," "Pride," and "Joy," representing two positive and two negative emotions, respectively. Four multiple linear regression (MLR) analyses revealed a statistically significant but low-magnitudeeffect of sociodemographic variables on emotions. The correlations between the emotional factors indicate that two negative emotions and one positive emotion (pride) are highly positively correlated, whereas "joy" is the only emotion negatively associated with negative emotions and has a low correlation with pride. These results imply that sociodemographic variables may only serve as a foundation for forming a driver's contingent emotions, which are later specified by other factors, such as the driving context. Moreover, "joy" may be the only emotional factor that promotes regulation-congruent and favourable driving behaviour; the other three factors may result in various unfavourable driving styles. These findings may be used to determine the needs and specific characteristics of every driver based on their feelings and help design various mitigation measures addressing unfavourable behaviours tailored for different groups of drivers.
近期的动机导向驾驶行为理论非常关注驾驶员的认知特征，尤其是情绪。驾驶员情绪在驾驶行为中的作用已成为广泛研究的课题，但仍有一个重要问题悬而未决：驾驶员在实际驾驶情境中会有何感受？在本研究中，我们开发了一个包含 20 种不同情绪的问卷，进行了一项在线调查，并收集了 232 名参与者的回复。探索性因素分析（EFA）表明存在 4 种因素结构。此外，我们构建了路径图和验证性因素分析（CFA），并将这些因素语义命名为“不适”、“恐惧”、“自豪”和“喜悦”，分别代表两种积极情绪和两种消极情绪。四项多元线性回归（MLR）分析表明，社会人口统计学变量对情绪的影响具有统计学意义，但程度较低。情绪因素之间的相关性表明，两种消极情绪和一种积极情绪（自豪）之间高度正相关，而“喜悦”是唯一与消极情绪呈负相关且与自豪相关性较低的情绪。这些结果表明，社会人口统计学变量可能仅作为形成驾驶员条件情绪的基础，而其他因素，如驾驶情境，会进一步具体说明这些情绪。此外，“喜悦”可能是唯一能够促进与调节一致和有利的驾驶行为的情绪因素；其他三个因素可能会导致各种不利的驾驶风格。这些发现可用于根据驾驶员的感受确定每个驾驶员的需求和特定特征，并帮助设计针对不同驾驶员群体的各种有针对性的缓解措施。
