Abstract
The increase in vehicular traffic have also increased the highway crash frequency with the passage of time. Improvements in highway safety is of vital importance as it could save vast life and monetary losses. The highway crash frequency analysis of major Pakistani highways is a subject less discovered and many important strategic and trade routes are not studied in this regard. This study is aimed to analyze the crash frequency and the prominent factors that cause these crashes on a 302 km section of Indus highway; one of the most important trade routes of the country. Eight years’ data from 2011 till 2018 was arranged into 19 variables where the crash frequency is set as dependent variable, while the eighteen prominent causation factors as independent variables. The tool used for analysis was negative binomial regression being run in the SPSS software. The results indicate that the driver’s behavior, understanding & risk recognition, negligence and law adherence have a significant effect on the crash frequency. Furthermore, highway crash frequency significantly increases with increase in highway segment lengths, number of lanes and lane widths. Similarly, the highway crash frequency significantly enhances when the light, pavement surface and climate condition gets deteriorated. The results of this study are of vital importance to government, transportation companies and general public in order to recognize the most important accident causing factors and devise the transport policies, rules and behaviors accordingly.
Highlights
The severity level of crashes are subject to the cumulative influences of various observed and unobserved factors [1]
In order to analyze the selected variables using negative binomial regression (NBR), first the mean, standard deviation, minimum and maximum values of the dependent and independent variables have been depicted in the table 1
Highway crashes have been a major concern in Pakistan for the authorities as it results in a significant annual life and monetary loss
Summary
The severity level of crashes are subject to the cumulative influences of various observed and unobserved factors [1]. These factors could either be engineering or non-engineering. The non-engineering factors stands for the behavioral patterns observed among drivers, various other human factors, effects of environment, seasonal and diurnal variations. The lack of data in this regard could be attributed to the reason that it is not the responsibility of federal or state highway agencies to take into record the behavioral patterns of the drivers involved in each accident. The data on the speed, lanes, distractions, disparities, and risky behaviors of drivers could be well found in the police reports of each accident [6]
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