Transportation Systems Engineering, Department of Civil Engineering, Indian Institute of Technology Bombay (IITB), Powai, Mumbai, India.
Traffic Inj Prev. 2021;22(sup1):S21-S26. doi: 10.1080/15389588.2021.1965590. Epub 2021 Sep 7.
Aggressive driver behavior is one of the major contributing factors to road crashes. However, the relationship between aggressive driver behavior and crash risk is scarcely explored. The present study focused on quantifying the effect of aggressive driver behavior on crash probability.
A sample of 405 Indian drivers were analyzed to model the aggressive driver behavior using self-reported measures. Generalized linear models were developed to quantify the effects of independent variables such as age, gender, personality traits (e.g., driving anger, physical aggression, hostility), and individual predilections to commit violations (e.g., excessive speeding and frequent risky overtaking) on aggressive driver behavior and crash probabilities.
K-means clustering technique was applied to the Aggressive Driving Scale (ADS) scores to cluster the drivers into three groups (aggressive, normal, and cautious). Gender was significantly correlated with aggressive driver behavior. Compared to female drivers, male drivers were 2.57 times more likely to engage in aggressive driving. Driver's age was negatively correlated with aggressive driving. With one-year increment in driver's age, the tendency of a driver to engage in aggressive driving was reduced by 26%. In addition, the likelihood of being engaged in aggressive driving was increased by 2.98 times and 2.15 times for the drivers who engage in excessive speeding and frequent risky overtaking, respectively. Driver's personality traits were significantly correlated with aggressive drivers. The crash involvement model showed that aggressive drivers were 2.79 times more likely to be involved in road crashes than cautious drivers. Further, married drivers were 2.17 times less likely to be involved in crashes, whereas for professional drivers the crash involvement probability was increased by 75%.
The results revealed that in addition to age and gender personality traits were significant predictors of driving aggression. Further, the driver's marital status was negatively correlated with the crash involvement and professional drivers were more likely to be involved in crashes than nonprofessional drivers. The study findings can be used in identifying specific risk-prone drivers to provide safety measures via in-vehicle Advanced Driver Assistance Systems (ADAS).
攻击性驾驶行为是道路事故的主要原因之一。然而，攻击性驾驶行为与事故风险之间的关系尚未得到充分探讨。本研究旨在量化攻击性驾驶行为对事故概率的影响。
对 405 名印度驾驶员进行样本分析，使用自我报告的措施对攻击性驾驶行为进行建模。开发了广义线性模型，以量化年龄、性别、人格特质（如驾驶愤怒、身体攻击、敌意）、个体违规倾向（如超速行驶和频繁危险超车）等独立变量对攻击性驾驶行为和事故概率的影响。
应用 K-均值聚类技术对攻击性驾驶量表（ADS）得分进行聚类，将驾驶员分为三组（攻击性、正常和谨慎）。性别与攻击性驾驶行为显著相关。与女性驾驶员相比，男性驾驶员更有可能进行攻击性驾驶，可能性是女性的 2.57 倍。驾驶员年龄与攻击性驾驶呈负相关。驾驶员年龄每增加一年，驾驶员进行攻击性驾驶的倾向降低 26%。此外，超速行驶和频繁危险超车的驾驶员进行攻击性驾驶的可能性分别增加了 2.98 倍和 2.15 倍。驾驶员的人格特质与攻击性驾驶员显著相关。事故参与模型表明，攻击性驾驶员发生道路事故的可能性是谨慎驾驶员的 2.79 倍。此外，已婚驾驶员发生事故的可能性降低了 2.17 倍，而职业驾驶员发生事故的可能性增加了 75%。
结果表明，除年龄和性别外，人格特质也是驾驶攻击性的重要预测因素。此外，驾驶员的婚姻状况与事故参与呈负相关，职业驾驶员发生事故的可能性高于非职业驾驶员。研究结果可用于识别特定的高风险驾驶员，通过车载高级驾驶员辅助系统（ADAS）提供安全措施。
