Road capacity utilization is causally connected with an appropriate level of efficiency and an optimal level of traffic safety. Therefore, in this paper, it is considered the issue of maximum utilization of road capacity through the maximization of the input parameter AADT (Annual Average Daily Traffic), and the minimization of output parameters related to the categories of traffic accidents. It was defined six main road sections, which were evaluated based on seven techno-operational criteria using an integrated Multi-criteria decision-making (MCDM) model. The data refer to buses as a vehicle category. The Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA) method was chosen to determine the weights of criteria, while the road sections were ranked using the Evaluation based on distance from average solution (EDAS). In addition, in one of the stages of applying the model when it comes to AADT, the Bonferroni operator (BFO) is used. The results show that the highest level of safety refers to a main road section with the following characteristics: average AADT, minimal deviation from the speed limit, an ascent of 7% and the lowest number of traffic accidents by all categories. In the paper, it was performed a multi-phase sensitivity analysis in order to identify possible differences in results when determining new circumstances.

The operating speed is the average value of the speed of traffic flow under normal conditions, i.e., the conditions of mutual interference of traffic participants. The operating speed serves as a gauge for how well a given roadway is performing under the applicable traffic conditions. All key decisions in the management of the growth and utilization of a road network, including planning, designing, evaluating, and implementing road projects, depend on accurate measures of capacity and level of service. This paper aims to develop a recommended model for operating speed on two-lane roads under local conditions by analyzing the operating speeds of the traffic flow on representative sections of such roads. Through the modeling process, the values of the 85th percentile of the operating speed were determined, and compared with relevant studies. The results show that the authors have successfully modeled operating speeds as a function of longitudinal gradient in local conditions on two-lane roads.

Any deviation of speed in a traffic flow from a speed limit represents a potential risk of traffic accidents, so speed management appears as an imperative. However, an inadequately set speed limit often causes drivers’ noncompliance to it in the conditions of real traffic flow. By determining the value of exceeding the speed limit according to vehicle classes, it is possible to recommend a credible speeding value that can be considered credible up to a value above the speed limit. In this paper, deterministic multistep mathematical models of speed deviation from the speed limit as a function of longitudinal gradient for the proposed vehicle classes were developed. A total of 11 measuring sections with different traffic flow types were analyzed. Based on a detailed analysis of speeding, models for the deviation of the 15th, 50th, and 85th percentiles were obtained, with the aim of adjusting the credible deviation to control measures. The results obtained in this study were compared with a survey of traffic flow speeding on two-lane roads conducted in Serbia.

Traffic management is a significantly difficult and demanding task. It is necessary to know the main parameters of road networks in order to adequately meet traffic management requirements. Through this paper, an integrated fuzzy model for ranking road sections based on four inputs and four outputs was developed. The goal was to determine the safety degree of the observed road sections by the methodology developed. The greatest contribution of the paper is reflected in the development of the improved fuzzy step-wise weight assessment ratio analysis (IMF SWARA) method and integration with the fuzzy measurement alternatives and ranking according to the compromise solution (fuzzy MARCOS) method. First, the data envelopment analysis (DEA) model was applied, showing that three road sections have a high traffic risk. After that, IMF SWARA was applied to determine the values of the weight coefficients of the criteria, and the fuzzy MARCOS method was used for the final ranking of the sections. The obtained results were verified through a three-phase sensitivity analysis with an emphasis on forming 40 new scenarios in which input values were simulated. The stability of the model was proven in all phases of sensitivity analysis.

There are numerous algorithms and solutions for car or object detection as humanity is aiming towards the smart city solutions. Most solutions are based on counting, speed detection, traffic accidents and vehicle classification. The mentioned solutions are mostly based on high-quality videos, wide angles camera view, vehicles in motion, and are optimized for good visibility conditions intervals. A novelty of the proposed algorithm and solution is more accurate digital data extraction from video file sources generated by security cameras in Bosnia and Herzegovina from M18 roadway, but not limited only to that particular source. From the video file sources, data regarding number of vehicles, speed, traveling direction, and time intervals for the region of interest will be collected. Since finding contours approach is effective only on objects that are mobile, and because the application of this approach on traffic junctions did not yield desired results, a more specific approach of classification using a combination of Histogram of Oriented Gradients (HOG) and Support Vector Machines (Linear SVM) has shown to be more appropriate as the original source data can be used for training where the main benefit is the preservation of local second-order interactions, providing tolerance to local geometric misalignment and ability to work with small data samples. The features of the objects within a frame are extracted first by standardizing the feature variables and then computing the first order gradients of the frame. In the next stage, an encoding that remains robust to small changes while being sensitive to local frame content is produced. Finally, the HOG descriptors are generated and normalized again. In this way the channel histogram and spatial vector becomes the feature vector for the Linear SVM classifier. With the following parameters and setup system accuracy was around 85 to 95%. In the next phase, after cleaning protocols on collected data parameters, data will be used to research asphalt deformation effects.

In this paper, empirical research about Passenger Car Equivalents (PCEs) on the longitudinal downgrade of two-lane roads in Bosnia and Herzegovina has been conducted in order to determine the influence of vehicle structure under free traffic flow conditions. The research has been carried out considering the classes of vehicles at cross-sections on the downgrade of two-lane roads. As a result, the negative influence of vehicle structure under free traffic flow conditions using passenger car equivalents (PCEs) has been determined. The results show that on the downgrade of two-lane roads, the value of passenger car equivalent decreases from the level terrain to the boundary minimum value for the determined downgrade g = −3.00%, after which its value starts to increase slightly. Based on the obtained values, the models calibrated with a second-degree polynomial have been developed to determine the average value of passenger car equivalent as a function of its boundary value. The paper also compares the results obtained by the developed models with the models from the Highway Capacity Manual under free traffic flow conditions. In addition, models for the percentage values of PCE15%, PCE50% and PCE85% have been established.

This paper demonstrates and provides additional findings and instructions to produce new cold-recycled layers of pavement structures spatially and temporally sustainable. At the same time, recycled pavement structures have been enhanced with optimum amounts of new stone materials and binders made of cement and foamed bitumen. The subject of the research is based on the examination of recycled asphalt from surface and bituminous base courses of pavement structures for use on higher-type roads. The aim of the research is to model the process of producing recycled asphalt by cold recycling to optimize the process of influential parameters. In addition, one of the primary goals of the research is to demonstrate a sustainable way of producing new cold-recycled layers of pavement structures. The obtained results indicated the inevitability of the use of recycled material from pavement structures with the possibility of applying secondary and tertiary crushing of recycled mass, which depends on the type of layer for which the recycled material would be used. The research resulted in an optimum mixture variant of the stabilization layer of pavement structure that consists mainly of recycled material from a worn pavement structure improved with a relatively small amount of new aggregate with the addition of minimal stabilizers made of cement and foamed bitumen. The results showed that the optimum mixture variant of the stabilization layer is spatially and temporally stable. Additionally, the presented optimum variant of the stabilization layer enables sustainable development of road networks with minimum consumption of new natural resources.

This paper deals with the analysis of traffic on the three-leg intersection in the city Cazin, at the junction of the three-leg intersection. The main issue of this research refers to the left-turn of vehicles coming from the merging road of the given intersection. The extensive analysis covered the current state of traffic flow by using the software tool, SIDRA INTERSECTION program. Within the suggested measures of improvement, the construction of a unsignalised roundabout was proposed. Implementation of the construction of a unsingalised roundabout would increase the level of traffic safety, reduce time losses while taking a left turn and therefore improve the Level of Service (LOS) as a qualitative indicator of traffic flow.