کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4978595 1452897 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An empirical analysis of run-off-road injury severity crashes involving large trucks
ترجمه فارسی عنوان
تجزیه و تحلیل تجربی از سوانح آسیب دفاعی در راه است که شامل کامیون های بزرگ می شود
کلمات کلیدی
ایمنی کامیون، سقوط رانندگی جاده، مدل پروبیت پارامتری تصادفی مرتب شده، شدت آسیب ناهمگونی ناشناخته،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی بهداشت و امنیت شیمی
چکیده انگلیسی
In recent years, there has been an increasing interest in understanding the contributory factors to run-off-road (ROR) crashes in the US, especially those where large trucks are involved. Although there have been several efforts to understand large-truck crashes, the relationship between crash factors, crash severity, and ROR crashes is not clearly understood. The intent of this research is to develop statistical models that provide additional insight into the effects that various contributory factors related to the person (driver), vehicle, crash, roadway, and environment have on ROR injury severity. An ordered random parameter probit was estimated to predict the likelihood of three injury severity categories using Oregon crash data: severe, minor, and no injury. The modeling approach accounts for unobserved heterogeneity (i.e., unobserved factors). The results showed that five parameter estimates were found to be random and normally distributed, and varied across ROR crash observations. These were factors related to crashes that occurred between January and April, raised median type, loss of control of a vehicle, the indicator variable of speed not involved, and the indicator variable of two vehicles or more involved in the crashes. In contrast, eight variables were found to be fixed across ROR observations. Looking more closely at the fixed parameter results, large-truck drivers who are not licensed in Oregon have a higher probability of experiencing no injury ROR crash outcomes, and human related factor, fatigue, increases the probability of minor injury. The modeling framework presented in this work offers a flexible methodology to analyze ROR crashes involving large trucks while accounting for unobserved heterogeneity. This information can aid safety planners and the trucking industry in identifying appropriate countermeasures to help mitigate the number and severity of large-truck ROR crashes.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Accident Analysis & Prevention - Volume 102, May 2017, Pages 93-100
نویسندگان
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