The expansion of the open-pit exploitation of mineral raw materials, and especially the energy resources of fossil fuels, makes open-pit coal mines spatially dominant objects of large mining basins. Exploitation activities are accompanied by negative ecological impacts on the environment, which requires the integral planning, revitalization, reclamation, and rehabilitation of the disturbed area for human use in the post-exploitation period. The post-exploitation remediation and rehabilitation of open-pit mining areas and disposal sites, i.e., space disturbed by mining activities and accompanying facilities, are complex synthetic multidisciplinary multiphase engineering project tasks. In this paper, a hybrid fuzzy MCDM model (Multiple-Criteria Decision-Making) was developed for the selection of a reclamation solution for the Tamnava-West Field open-pit mine. IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) was applied to define the weights of 12 criteria of different structures used in the evaluation of reclamation solutions. The Fuzzy ROV (Range of Value) method was applied to select the reclamation solution from a total of 11 solutions previously obtained using a process approach. The results of the hybrid IMF SWARA—Fuzzy ROV model show that forestry is the best solution for the Tamnava-West Field open-pit mine. After the results had been obtained, verification analyses of the proposed model were performed and the best stable proposed reclamation solution was determined.

The capacity of transport infrastructure is one of the very important tasks in transport engineering, which depends mostly on the geometric characteristics of road and headway analysis. In this paper, we have considered 14 road sections and determined their efficiency based on headway analysis. We have developed a novel interval fuzzy-rough-number decision-making model consisting of DEA (data envelopment analysis), IFRN SWARA (interval-valued fuzzy-rough-number stepwise weight-assessment-ratio analysis), and IFRN WASPAS (interval-valued fuzzy-rough-number weighted-aggregate sum–product assessment) methods. The main contribution of this study is a new extension of WASPAS method with interval fuzzy rough numbers. Firstly, the DEA model was applied to determine the efficiency of 14 road sections according to seven input–output parameters. Seven out of the fourteen alternatives showed full efficiency and were implemented further in the model. After that, the IFRN SWARA method was used for the calculation of the final weights, while IFRN WASPAS was applied for ranking seven of the road sections. The results show that two sections are very similar and have almost equal efficiency, while the other results are very stable. According to the results obtained, the best-ranked is a measuring segment of the Ivanjska–Šargovac section, with a road gradient = −5.5%, which has low deviating values of headways according to the measurement classes from PC-PC to AT-PC, which shows balanced and continuous traffic flow. Finally, verification tests such as changing the criteria weights, comparative analysis, changing the λ parameter, and reverse rank analysis have been performed.

Road infrastructure management is an extremely important task of traffic engineering. For the purpose of efficient management, it is necessary to determine the efficiency of the traffic flow through PAE 85%, AADT and other exploitation parameters on the one hand, and the number of different types of traffic accidents on the other. In this paper, a novel TrIT2F (trapezoidal interval type-2 fuzzy) PIPRECIA (pivot pairwise relative criteria importance assessment)-TrIT2F MARCOS (measurement of alternatives and ranking according to compromise solution) was developed in order to, in a defined set of 14 road segments, identify the most efficient one for data related to light goods vehicles. Through this the aims and contributions of the study can be manifested. The evaluation was carried out on the basis of seven criteria with weights obtained using the TrIT2F PIPRECIA, while the final results were presented through the TrIT2F MARCOS method. To average part of the input data, the Dombi and Bonferroni operators have been applied. The final results of the applied TrIT2F PIPRECIA-TrIT2F MARCOS model show the following ranking of road segments, according to which Vrhovi–Šešlije M-I-103 with a gradient of −1.00 represents the best solution: A5 > A8 > A2 > A1 > A4 > A3 > A6 > A12 > A13 = A14 > A11 > A7 > A9 > A10. In addition, the validation of the obtained results was conducted by changing the values of the four most important criteria and changing the size of the decision matrix. Tests have shown great stability of the developed TrIT2F PIPRECIA-TrIT2F MARCOS model.

Ovaj rad demonstrira primenu alata poka-yoke na stolovima za testiranje kablovskih snopova u auto industriji

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 impact of geometric characteristics on traffic risk is reflected through identifying conflict points on roads,traffic accidents, and any other unforeseen situation that is inherently hazardous for traffic participants. In order to identify the road sections with the highest risk, it is necessary to consider a number of criteria that affect risk, and conduct extensive empirical research, analysis and data synthesis. This paper evaluates 9 sections of two-lane roads in the territory of Bosnia and Herzegovina (the Republic of Srpska) using an integrated Multi-Criteria Decision-Making (MCDM) model.To determine the significance of 8 criteria for the evaluation of the sections, it was applied a subjective–objective model consisting of 3 methods: (1) CRiteria Importance Through Inter-criteria Correlation (CRITIC), (2) FUll COnsistency Method (FUCOM) and (3) fuzzy PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA). The aggregation of the criterion values obtained using the methods yielded the final criterion values. Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS) method was used to evaluate the sections and determine their objective diversity. The obtained results identified one location as extremely hazardous by most of analysed input parameters. The section with the highest risk is the Rudanka – Doboj section (A4), which represents a section of the road infrastructure of the 105 road. The validation of the results obtained by applying the integrated MCDM model was performed through an extensive sensitivity analysis. The weights of criteria were observed through initially individual methods implemented in the MARCOS method. Then, a comparative analysis was performed with 6 other MCDM methods and Spearman’s Correlation Coefficient (SCC) was calculated as a statistical indicator of rank correlation in a sensitivity analysis. In addition,the Standard Deviation (STDEV) of the obtained results was determined.

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.

Spatial constraints in urban areas very often lead to the application of traffic management measures to meet transport demands. Accordingly, it is very important to identify all potential impacts that could lead to reductions in the street network’s capacity. One such impact is weather conditions. The main motivation of this research is to analyze the impacts of rainfall on one of the most important segments of Belgrade’s street network that represents part of a freeway passing the city center. Our focus is on quantifying the impact of rainfall on speed and capacity. This paper proposes a new approach to analyzing the rainfall impact at the traffic lane level that provides additional possibilities to apply traffic management measures on the traffic lane level instead of at the direction level only. Functional dependences and differences in capacity and speed on traffic lanes were found under the influence of different rainfall intensities. Reductions in free-flow speed depend on the rain category and traffic lanes and vary from 4.5% to 11.58%, while reductions in traffic lane capacity range from 2.46% to 12.97%. We demonstrate the importance of considering the impact of rainfall at the traffic lane level, which could be quality input data for defining appropriate traffic management measures to mitigate the negative impacts.

Purpose . The purpose of this study is to examine the causes of delays in road construction projects in the Benin Republic from the consultant, client, and contractor perspectives. Design/Methodology/Approach . Through construction project reports, 20 factors that could cause delays in road construction projects were identified. The factors were arranged into a questionnaire, which was distributed to three separate experts. The fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Relevance Assessment) method was used to calculate the independent importance of each delay factor. The Spearman and Pearson correlation coefficients were used to test the method’s consistency. Findings . The top five road construction project delays in the Benin Republic, according to the analysis of the 20 factors considered, are project funding, slowness during the client-endorsed payment process, scarcity of professional personnel, delay in indemnifying reimbursement (land-owners), and price escalation. This shows that of the various types of delays, the financial delay group is the most crucial. Originality/value. This study evaluates the causes of delays in road construction projects in the Benin Republic for the first time in literature. This study also examined the top 5 delay factors in road construction projects. This study is based on reports from road construction projects and a performed questionnaire survey. Based on the findings, measures have been formulated to aid project managers to alleviate the road construction delays in the Benin Republic. In addition, this study is practical for both scholars and road construction parties and provides a complete and verifiable analysis of the progress of a road construction project to make it easier and attain a competitive level of time, cost, and quality for successful road construction.

Abstract – In this paper, an extensive analysis of the number of access points on a rural road network in the territory of Bosnia and Herzegovina has been performed. The HCM methodology defines that each access point adversely affects the speed of free traffic flow. The negative impact is quantitatively shown through 19 sections of rural roads, as well as a trend of reducing traffic flow speed on each of the analyzed sections. By analyzing and synthesizing the data, the values obtained indicate that access points affect reducing free traffic flow speed in the Federation of Bosnia and Herzegovina twice more than in the Republic of Srpska. The analysis also shows the spatial distribution of accesses points on the main roads section, which has been measured on 200 m subsections. Keywords – access points, traffic flow, speed.

Increasing mobility directly affects traffic frequency and thus increases the possible risk of traffic accident occurrences. Taking this into account, it is necessary to create models for determining risk and to act preventively based on these models; this is of great importance both to society and science. In this paper, six measuring sections of a road network are considered on the basis of eight geometric-exploitation road parameters, taking into account the data for light goods vehicles. An original methodology is proposed for identifying risk levels of road sections through their evaluation. For identifying risk levels, the Dombi Logarithmic Methodology of Additive Weights (D’LMAW) was used, which was combined with the Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) method. Statistical indicators were processed using a hybrid methodology based on the application of rough numbers and Dombi–Bonferroni functions. The performance of the presented methodology was verified on a real-world example, processing the statistical parameters of six two-lane road sections, with the sixth measuring section showing the best performance, since it had the minimum risk. Research has shown that measuring sections with increasing longitudinal gradients are safer. The analysis of measuring sections from fall to rise reduces the deviation of speeds from the speed limit on the roads. The effectiveness, rationality, and robustness of the solution of the proposed methodology was confirmed through a sensitivity analysis.