Understanding and mitigating drivers' negative emotions, stress levels, and anxiety is of high importance for decreasing accident rates, enhancing road safety, and providing a healthy lifestyle to the community of drivers. While detecting drivers' stress and negative emotions can significantly help with this goal, understanding what might be associated with increases in drivers' negative emotions and high stress level, might better help with planning interventions. While studies have provided significant insight into detecting drivers' emotions and stress levels; not many studies focused on the reasons behind changes in stress levels and negative emotions. In this study, by using a naturalistic driving study database, we analyze the changes in the driving scene, including road objects and the dynamical relationship between the ego vehicle and the lead vehicle with respect to changes in drivers' psychophysiological metrics (i.e., heart rate (HR) and facial expressions). We find that different road objects might be associated with varying levels of increase in drivers' HR as well as different proportions of negative facial emotions detected through computer vision. Our results indicate that larger vehicles on the road, such as trucks and buses, are associated with the highest amount of increase in drivers' HR as well as negative emotions. Additionally, we provide evidence that shorter distances to the lead vehicle in naturalistic driving, as well as the higher standard deviation in the distance, might be associated with a higher number of abrupt increases in drivers' HR, depicting a possible increase in stress level. Lastly, our results indicate more positive emotions, lower facial engagement, and a lower abrupt increase in HR at a higher speed of driving, which often happens in highway driving.
翻译:了解和减轻司机的负面情绪、压力和焦虑程度,对于降低事故发生率、加强道路安全和为司机提供健康的生活方式非常重要。虽然发现司机的压力和消极情绪可以极大地帮助实现这一目标,但了解司机的负面情绪和高度压力水平的增加可能与司机负面情绪和高度压力水平的增加相关联,这可能有助于规划干预措施。虽然研究为发现司机的情绪和压力水平提供了重要的洞察力;没有许多研究侧重于压力水平和消极情绪变化背后的原因。在这项研究中,我们利用自然驾驶研究数据库,分析驾驶场的变化,包括道路物体的变化,以及自我驾驶车辆和领头车辆之间的动态关系,可以极大地有助于实现这一目标。虽然发现司机的负面情绪和高度压力水平可能与司机的情绪增长有关,但我们利用自然驾驶研究数据库分析了驾驶场的变化,包括道路物体的变化以及自我驾驶车辆和领头车辆之间的动态关系。此外,我们发现,不同的道路目标可能与司机的性增长程度不同,而车辆的急剧性变化程度可能更高,而车辆的急剧性变化程度可能增加,而车辆的直径偏差程度可能增加。