Traffic accidents, by their nature, are random events; therefore, it is difficult to estimate the exact places and times of their occurrences and the true nature of their impacts. Although they are hard to precisely predict, preventative actions can be taken and their numbers (in a certain period) can be approximately predicted. In this study, we investigated the relationship between accident frequency and factors that affect accident frequency; we used accident data for events that occurred on a flat rural state road in Serbia. The analysis was conducted using five statistical models, i.e., Poisson, negative binomial, random effect negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models. The results indicated that the random effect negative binomial model outperformed the other models in terms of goodness-of-fit measures; it was chosen as the accident prediction model for flat rural roads. Four explanatory variables—annual average daily traffic, segment length, number of horizontal curves, and access road density—were found to significantly affect accident frequency. The results of this research can help road authorities make decisions about interventions and investments in road networks, designing new roads, and reconstructing existing roads.
The Republic of Srpska is susceptible to natural disasters, with particular regard to floods. Floods had caused human losses and property damage to both civilian and commercial facilities, road infrastructure and other infrastructure, on several occasions, including the 2014 floods. It is not always possible to predict natural disasters but human and material losses may be reduced if institutions undertake planned prevention activities and educate the population in terms of flood protection and risk reduction. The paper addresses floods as the natural disaster to which the Republic of Srpska is susceptible due to a long network of non-regulated water streams and frequent heavy rains. A special attention is paid to the floods which heavily affected the city of Doboj in 2014 as we analyze the activities on hazard elimination and consequence mitigation. The analysis is based on the study, assessment and plans designed in order to protect the city from floods in near future. Along with that we analyzed the impact of floods on the changes in the size of traffic flow requirements on the part of the M-17 road damaged in floods.
In the process of compensation for the damage suffered by the aggrieved party as a result of a traffic accident, it is often necessary to provide expertise to determine the cause of the accident, the aggrieved party’s contribution to the accident, or increase in the amount of damage. Formally and legally, it is necessary to observe the institute rule of shared responsibility. Shared responsibility is an institute rule that marks the contribution of the aggrieved party to cause damage or to be greater than it would otherwise be. Within the framework of this paper, the model of traffic accident expertise in civil procedure is investigated, primarily from the aspect of the contribution of the inadmissible action of the aggrieved party in the occurrence of the accident or increase of the damage.
The number of registered commercial freight vehicles in Bosnia and Herzegovina has been increasing over the years, which affects the traffic load and the condition of roads, especially in Bosnia and Herzegovina. Vehicle overloading is considered to be one of the biggest causes of damage to part of the road surface, especially with regard to the load-bearing road substructure. The focus of the research is the vehicle overloading on the roads of Bosnia and Herzegovina, with special emphasis on determining the type and degree of overloaded vehicles and determining the equivalence factor (EF). In the research phase, data from weighing control stations were used, taking into account the total weight of vehicles, the distribution of total weight on vehicle axles and the equivalent standard axle load for a particular vehicle type over a period of two years. A high degree of overloading was found, especially 5-axle vehicles (58.7%). The level of overloading in the range of 10-20% in relation to the maximum allowed weight is especially apparent. The calculated EF is 3.64 and is higher than the standard EF.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.