School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan 410075, PR China.
Department of Civil Engineering, College of Engineering, Qassim University, 51452, Saudi Arabia.
Accid Anal Prev. 2024 Sep;204:107651. doi: 10.1016/j.aap.2024.107651. Epub 2024 Jun 3.
Traffic crashes involving three-wheeler motorized rickshaw (3-WMR) are alarming public health and socioeconomic concerns in developing countries. While most of the earlier studies have dealt with safety analysis of four- and two-wheelers, there is a noticeable gap in understanding the safety dynamics, especially the risk factors affecting the crashes involving 3-WMR. The present study aims to address this gap by exploring potential risk factors influencing 3-WMR crashes, utilizing a correlated random parameters multinomial logit model with heterogeneity in means (CRPMNLMHM). This modeling framework advances the classic random parameters model by capturing associations among random parameters, providing a more comprehensive understanding of crash risks associated with 3-WMR. The empirical analysis draws on three years of traffic crash records (2017-2019) maintained by RESCUE 1122 in Rawalpindi city, Pakistan. A comparative assessment between the modeling frameworks demonstrated that CRPMNLMHM outperformed its counterparts. Model assessment for heterogeneity in the means identifies two significant variables, i.e., young age and nighttime, which yield statistically significant random parameters. In addition, the model's results suggest that fatal and severe injury outcomes in 3-WMR crashes are affected by several attributes related to temporal characteristics (weekend, nighttime, and off-peak indicators), driver profiles (young, older aged, and speeding), posted speed limits (>70 kmph), weather conditions (raining), and crash characteristics (collision with pedestrians, trucks, or 3-WMR overturning). The present study's findings offer invaluable insights, emphasizing the significance of considering for unobserved heterogeneity in variables contributing to the injury severity of 3-WMR crashes. Moreover, in light of the findings, a set of policy implications are suggested, which will guide safety practitioners to develop more effective countermeasures to address safety issues associated with 3-WMRs.
涉及三轮机动人力车（3-WMR）的交通事故是发展中国家令人震惊的公共卫生和社会经济问题。虽然大多数早期的研究都涉及四轮和两轮车的安全分析，但对于理解 3-WMR 事故的安全动态，特别是影响 3-WMR 事故的风险因素，存在明显的差距。本研究旨在通过利用均值异质性相关随机参数多项逻辑回归模型（CRPMNLMHM）来探索影响 3-WMR 事故的潜在风险因素，从而填补这一空白。该建模框架通过捕捉随机参数之间的关联，改进了经典的随机参数模型，提供了对与 3-WMR 相关的碰撞风险的更全面理解。实证分析利用巴基斯坦拉瓦尔品第市 RESCUE 1122 维护的三年交通事故记录（2017-2019 年）。对建模框架的比较评估表明，CRPMNLMHM 优于其对应物。均值异质性的模型评估确定了两个重要变量，即年轻年龄和夜间，它们产生了统计学上显著的随机参数。此外，模型结果表明，3-WMR 事故中的致命和严重伤害结果受到与时间特征（周末、夜间和非高峰指标）、驾驶员特征（年轻、年龄较大和超速）、规定的限速（>70 公里/小时）、天气条件（下雨）和碰撞特征（与行人、卡车或 3-WMR 翻车碰撞）相关的几个属性的影响。本研究的结果提供了宝贵的见解，强调了考虑导致 3-WMR 碰撞伤害严重程度的变量中未观察到的异质性的重要性。此外，根据研究结果，提出了一系列政策建议，这将指导安全从业者制定更有效的对策，以解决与 3-WMR 相关的安全问题。
