DMP-2019.

This study explores the demographic and behavioral determinants of road traffic accident (RTA) severity in the context of the Dhaka metropolitan area, Bangladesh. Road crash data recorded by the Dhaka Metropolitan Police (DMP) were analyzed through ordered logistic regression and generalized ordered logistic regression. The results were interpreted using log odds ratios, odds ratios, predicted probabilities, and marginal effects. The findings reveal that young and middle-aged drivers exhibit significantly higher odds of severe crashes compared to underage drivers. Young-aged drivers are 14 percentage points more likely to cause fatal crashes when compared to old aged drivers in our ordered logit model. In addition, male drivers show higher odds of severe crashes than females. Factors such as overloading of vehicles, alcohol consumption while driving, and over-speeding were identified as the major contributors to increasing crash severity. Alcohol consumption had an odds ratio of 1.223 in the ordered logit model, and it had odds ratios of 2.418, 1.722, and 1.086 for the thresholds of motor collision, simple injury, and grievous injury, respectively, in the generalized ordered logit model. In contrast, the use of seatbelts, vehicle fitness maintenance, and drivers’ licensing shows mitigating effects on crash severity, with significant odds ratios本研究以孟加拉国达卡都会区为研究场景，探讨了道路交通事故（road traffic accident, RTA）严重程度的人口统计学与行为学影响因素。研究采用达卡大都会警察局（Dhaka Metropolitan Police, DMP）记录的道路碰撞数据，通过有序logistic回归与广义有序logistic回归开展分析。研究结果通过对数优势比、优势比、预测概率与边际效应进行解读。研究发现，与未成年驾驶员相比，青年与中年驾驶员发生严重碰撞事故的概率显著更高。在有序logit模型中，青年驾驶员引发致命碰撞事故的概率较老年驾驶员高出14个百分点。此外，男性驾驶员发生严重碰撞事故的概率高于女性驾驶员。车辆超载、驾驶时饮酒与超速行驶等因素被确定为加剧事故严重程度的主要诱因。在有序logit模型中，饮酒驾驶的优势比为1.223；而在广义有序logit模型中，其针对机动车碰撞、轻微受伤与重伤三类事故严重程度阈值的优势比分别为2.418、1.722与1.086。与之相对，安全带使用、车辆状况维护与驾驶员持证上岗对事故严重程度具有缓解作用，其优势比均具有统计学显著性。