Hasil untuk "Highway engineering. Roads and pavements"

Oleksandr Kosenkov, Ehsan Zabardast, Jannik Fischbach et al.

Implementing privacy by design (PbD) according to the General Data Protection Regulation (GDPR) is met with a growing number of requirements engineering (RE) approaches. However, the question of which RE method for PbD fits best the goals of organisations remains a challenge. We report our endeavor to close this gap by synthesizing a goal-centric approach for PbD methods assessment. We used literature review, interviews, and validation with practitioners to achieve the goal of our study. As practitioners do not approach PbD systematically, we suggest that RE methods for PbD should be assessed against organisational goals, rather than process characteristics only. We hope that, when further developed, the goal-centric approach could support the development, selection, and tailoring of RE practices for PbD.

Authors Anatolii Tsynka, Serhii Illiash, Vitaliy Raykovskiy et al.

Introduction. The article deals with the issue of analyzing the technical parameters of EuroCombi road trains (overall dimensions, loads on the road pavement structure and transport facilities, etc.) and establishing the possibility of their movement on the state highway. The objective of the study is to analyze the experience of using large and heavy-goods vehicles (overall dimensions, loads on the pavement structure and transport facilities, etc.) with the possibility of their movement on roads of national importance. Materials and methods. The methodological basis is a scientific approach to the analysis of research issues questions through the use of statistical, formal and logical, and complex research methods. The sources of research are the data of completed scientific works and current regulatory documents. Results. In order to introduce modern methods of designing roads using vehicles with a total length of more than 25 m, the parameters of the turning radius (internal, external and path length) and their impact on route planning were analyzed. Conclusions. The conducted research will be used in the design of new roads of national importance, adaptation of existing road infrastructure (turning radii at junctions and intersections), and will also help logisticians in planning LHV routes (three-link road trains of the EuroCombi type) to ensure their safe passage / maneuvering along the route.

Anna Kyrychenko, Ivan Kopynets, Oksana Sokolova

Introduction. Increasing the durability of pavement structures and harmonizing the national regulatory framework with European standards are key tasks for Ukraine’s road sector. The quality of stone mastic asphalt (SMA), as one of the most effective materials for surface courses, directly depends on the relevance of regulatory requirements. In Ukraine, these requirements were standardized by DSTU B V.2.7-127:2015 until 2024. However, in order to introduce modern approaches, a new standard, DSTU 9290-5:2024, has been developed and adopted. Problem Statement. Analysis shows that the requirements of DSTU B V.2.7-127:2015, although providing a basic quality level, had a number of shortcomings: insufficiently strict requirements for the geometric characteristics of aggregates, reliance on outdated nomenclature of bituminous binders, and most importantly, the absence of testing methods directly assessing asphalt performance, in particular rutting resistance. Such discrepancies with European practice restrained the real service life improvement of road pavements. Objective. To carry out a detailed comparative analysis of the requirements for stone mastic asphalt mixtures and SMA according to DSTU B V.2.7-127:2015 and the new DSTU 9290-5:2024, in order to identify key innovations and scientifically substantiate their impact on improving road construction quality.

Hamad I. Al Abdul Wahhab, Farag Ali Salem Balbahaith, Waqas Rafiq et al.

In highly populated cities, road damage inspection is a critical and pressing issue for economic traffic. Despite the development of several techniques, the visual method remains popular due to its simplicity and speed of inspection. The Pavement Condition Index (PCI) method is a widely used visual inspection technique for evaluating pavement conditions, valued for its speed, simplicity, and ability to provide a standardized numerical rating based on observed surface distress. In contrast, the Bina Marga analytical method-developed and standardized by Indonesia’s Directorate General of Highways-adopts a mathematical and structural analysis approach, incorporating parameters such as pavement deflection, material properties, and load repetitions. Both methods analyze the type and level of road damage to be a reference for road maintenance programs. The research location was chosen in a densely populated, suburban area and experienced substantial deterioration due to traffic loads, environmental factors, and inadequate maintenance. Based on the results of field data, the types of damage found on Bogor district roads are 4 types of damage, namely: edge cracks, longitudinal cracks, patches, and holes. By using the PCI method, the total PCI obtained is 546 with an average PCI of 45.50. So that the condition has a value in a moderate condition (Fair). For the Bina Marga method, the priority sequence value obtained is 5, which indicates that periodic maintenance is needed.

Georgi Markov, Jon G. Hall, Lucia Rapanotti

Many organisational problems are addressed through systemic change and re-engineering of existing Information Systems rather than radical new design. In the face of widespread IT project failure, devising effective ways to tackle this type of change remains an open challenge. This work discusses the motivation, theoretical foundation, characteristics and evaluation of a novel framework - referred to as POE-$Δ$, which is rooted in design and engineering and is aimed at providing systematic support for representing, structuring and exploring change problems of a socio-technical nature, including implementing their solutions when they exist. We generalise an existing framework of greenfield design as problem solving for application to change problems. From a theoretical perspective,POE-$Δ$ is a strict extension to its parent framework, allowing the seamless integration of greenfield and brownfield design to tackle change problems. A Design Science Research methodology was applied over a decade to define and evaluate POE-$Δ$, with significant case study research conducted to evaluate the framework in its application to real-world change problems of varying criticality and complexity. The results show that POE-$Δ$ exhibits desirable characteristics of a design approach to organisational change and can bring tangible benefits when applied in practice as a holistic and systematic approach to change in socio-technical contexts.

Andrews Danyo, Anthony Dontoh, Armstrong Aboah

Accurately predicting the Pavement Condition Index (PCI), a measure of roadway conditions, from pavement images is crucial for infrastructure maintenance. This study proposes an enhanced version of the Residual Network (ResNet50) architecture, integrated with a Convolutional Block Attention Module (CBAM), to predict PCI directly from pavement images without additional annotations. By incorporating CBAM, the model autonomously prioritizes critical features within the images, improving prediction accuracy. Compared to the original baseline ResNet50 and DenseNet161 architectures, the enhanced ResNet50-CBAM model achieved a significantly lower mean absolute percentage error (MAPE) of 58.16%, compared to the baseline models that achieved 70.76% and 65.48% respectively. These results highlight the potential of using attention mechanisms to refine feature extraction, ultimately enabling more accurate and efficient assessments of pavement conditions. This study emphasizes the importance of targeted feature refinement in advancing automated pavement analysis through attention mechanisms.

Sebastian Baltes, Florian Angermeir, Chetan Arora et al.

Large Language Models (LLMs) are now ubiquitous in software engineering (SE) research and practice, yet their non-determinism, opaque training data, and rapidly evolving models threaten the reproducibility and replicability of empirical studies. We address this challenge through a collaborative effort of 22 researchers, presenting a taxonomy of seven study types that organizes the landscape of LLM involvement in SE research, together with eight guidelines for designing and reporting such studies. Each guideline distinguishes requirements (must) from recommended practices (should) and is contextualized by the study types it applies to. Our guidelines recommend that researchers: (1) declare LLM usage and role; (2) report model versions, configurations, and customizations; (3) document the tool architecture beyond the model; (4) disclose prompts, their development, and interaction logs; (5) validate LLM outputs with humans; (6) include an open LLM as a baseline; (7) use suitable baselines, benchmarks, and metrics; and (8) articulate limitations and mitigations. We complement the guidelines with an applicability matrix mapping guidelines to study types and a reporting checklist for authors and reviewers. We maintain the study types and guidelines online as a living resource for the community to use and shape (llm-guidelines$.$org).

Mahdi Azhdari, Ali Tavakoli Kashani, Saeideh Amirifar et al.

Accurately modeling crash severity on rural two-lane roads is essential for effective safety management, yet standard single level approaches often overlook unobserved heterogeneity across road segments. In this study, we analyze 19 956 crash records from 99 rural roads in Iran during recent four years incorporating crash level predictors such as driver age, education, gender, lighting and pavement conditions, along with road level covariates like annual average daily traffic, heavy-vehicle share and terrain slope. We compare three binary logistic frameworks: a single level generalized linear model, a multilevel model with a random intercept capturing latent road level effects (intraclass correlation = 21 %), and a multilevel model with random coefficients that allows key predictor effects to vary by road. The random coefficient model achieves the best fit in terms of deviance, AIC and BIC, and substantially improves predictive performance: classification accuracy rises from 0.62 to 0.71, recall from 0.32 to 0.63, and AUC from 0.570 to 0.775. Results from 200 simulation runs reveal notable variability in slopes for pavement and lighting variables, underscoring how local context influences crash risk. Overall, our findings demonstrate that flexible multilevel modeling not only enhances prediction accuracy but also yields context-specific insights to guide targeted safety interventions on rural road networks.

Shilin Tong, Difei Wu, Xiaona Liu et al.

Pavement distress significantly compromises road integrity and poses risks to drivers. Accurate prediction of pavement distress deterioration is essential for effective road management, cost reduction in maintenance, and improvement of traffic safety. However, real-world data on pavement distress is usually collected irregularly, resulting in uneven, asynchronous, and sparse spatial-temporal datasets. This hinders the application of existing spatial-temporal models, such as DCRNN, since they are only applicable to regularly and synchronously collected data. To overcome these challenges, we propose the Spatial-Temporal Graph Autoregression Network (STGAN), a novel graph neural network model designed for accurately predicting irregular pavement distress deterioration using complex spatial-temporal data. Specifically, STGAN integrates the temporal domain into the spatial domain, creating a larger graph where nodes are represented by spatial-temporal tuples and edges are formed based on a similarity-based connection mechanism. Furthermore, based on the constructed spatiotemporal graph, we formulate pavement distress deterioration prediction as a graph autoregression task, i.e., the graph size increases incrementally and the prediction is performed sequentially. This is accomplished by a novel spatial-temporal attention mechanism deployed by STGAN. Utilizing the ConTrack dataset, which contains pavement distress records collected from different locations in Shanghai, we demonstrate the superior performance of STGAN in capturing spatial-temporal correlations and addressing the aforementioned challenges. Experimental results further show that STGAN outperforms baseline models, and ablation studies confirm the effectiveness of its novel modules. Our findings contribute to promoting proactive road maintenance decision-making and ultimately enhancing road safety and resilience.

Allysson Allex Araújo, Marcos Kalinowski, Maria Teresa Baldassarre

In recent years, Software Engineering (SE) scholars and practitioners have emphasized the importance of integrating soft skills into SE education. However, teaching and learning soft skills are complex, as they cannot be acquired passively through raw knowledge acquisition. On the other hand, hackathons have attracted increasing attention due to their experiential, collaborative, and intensive nature, which certain tasks could be similar to real-world software development. This paper aims to discuss the idea of hackathons as an educational strategy for shaping SE students' soft skills in practice. Initially, we overview the existing literature on soft skills and hackathons in SE education. Then, we report preliminary empirical evidence from a seven-day hybrid hackathon involving 40 students. We assess how the hackathon experience promoted innovative and creative thinking, collaboration and teamwork, and knowledge application among participants through a structured questionnaire designed to evaluate students' self-awareness. Lastly, our findings and new directions are analyzed through the lens of Self-Determination Theory, which offers a psychological lens to understand human behavior. This paper contributes to academia by advocating the potential of hackathons in SE education and proposing concrete plans for future research within SDT. For industry, our discussion has implications around developing soft skills in future SE professionals, thereby enhancing their employability and readiness in the software market.

Оleksii Sokolov

Introduction. In Ukraine, about 30 % of all electricity is generated from the combustion of solid fuels — coal, shale, peat. In our country, there are about 15 operating thermal power plants that generate about 5 – 6 million tons of ash and slag waste per year as a secondary product. Thus, the fuel and energy complex waste generated in the furnaces of thermal power plants is a huge accumulation of ash in the form of dusty residues and lumpy sludge, as well as various ash and slag mixtures. These products of high-temperature processing (1 200 – 1 700 ºС) of the mineral part of the fuel are widely used in many countries of the world and, given the global trend towards an increase in the share of the secondary market for the use of waste, it is necessary to predict an increase in the rate of their processing in Ukraine. Problem Statement. The road construction industry is one of the strategic industries of Ukraine, and the issue of quality and availability of basic building materials for road construction is particularly acute now, which is directly related to its high material intensity. The known reserves of high-quality raw materials that could be used as asphalt concrete components are constantly decreasing, so it is necessary to look for alternative sources of raw materials for construction materials and explore the possibility of their use. In this regard, the most effective use of local raw materials is the use of industrial waste, which can be one of the solutions to the problem of lack of raw materials of inorganic origin.

Serhii Zavhorodniy, Vasyl Redchenko

Introduction. This article deals with the issue of relevance of dynamic testing of bridges in Ukraine, an overview of dynamic testing methods and the prospects for the development of this type of bridge testing. Problem statement. Monitoring the technical condition of bridges is an urgent problem for maintenance services and requires the use of the most advanced methods to quickly identify possible defects and damage in their structures. Dynamic testing is one of such methods, the development and implementation of which requires joint efforts of engineers and the scientific community. Objective. The main purpose of the article is to evaluate and analyze existing approaches to dynamic testing of bridges to diagnose their condition. This study aims to highlight the need to apply these methods to improve the reliability and safety of bridges, as well as to improve strategies for the maintenance and repair of bridge structures. Materials and methods. The material for the article is the experience of performing dynamic tests of bridges in Ukraine, including an example of testing a 420-meter-long reinforced concrete road bridge located in the Western Ukraine.

Andrzej Ambroziak, Maciej Malinowski, Mirosław Wałęga

The structural analysis of a road foldable prefabricated steel Bailey- type bridge located over the Tuga River in Żelichowo, Poland is performed in this paper. Interesting and untypical bridge redevelopment performed made it possible to lift the middle foldable bridge span by approximately 4.0 m concerning the existing state. The paper begins with a survey of literature carried out on the investigations of foldable Bailey-type bridge subject matter. A description of the numerical modelling of foldable prefabricated bridges is performed. The comparison of the proof load test results with the FEM numerical model results has shown very good compatibility. This paper can provide scientists, engineers, and designers the basis for structural analysis in the field of foldable Bailey-type bridge constructions and numerical simulations.

Azka Rodoshi Oishi, Md Jamil Ahsan, Azka Sejuti et al.

Traumatic Brain Injuries (TBIs) resulting from Road Traffic Crashes (RTCs) can have fatal and disabling effects on patients. In this study, we evaluated the TBIs outcomes of patients involved in RTCs and identify key contributing factors affecting these outcomes. Data on 207 patients recorded by physicians at a tertiary hospital in Bangladesh was collected. A random parameters multinomial logit model with heterogeneity in the means was utilized to assess patients outcomes in three categories: Non-surgical, Surgical, and Fatal. From the random parameters, the study found that male patients (55.48%) are more likely to experience surgical and fatal outcomes. Male motorcycle users have a higher probability of experiencing fatal consequences. Additionally, 60.94% of incidents on rural roads result in surgeries and fatalities, with nighttime crashes on these roads significantly increasing the likelihood of fatal outcomes. Key factors impacting the likelihood of TBIs outcomes include older age, pedestrian involvement, bus and truck crashes, speeding, wet pavements, overtaking, low visibility, and weekday crashes. The study identified two significant interaction variables that increase the probability of fatal outcomes from TBIs: the interactions between low visibility and bus involvement, and between overtaking and wet pavements. While these factors individually had a higher probability of leading to both surgical and fatal outcomes, together these factors increase the risks to fatalities. Overall, our findings provide more detailed insights about the impact of TBIs outcomes resulting from RTCs and emphasize the need to develop more effective measures to improve road safety and patient outcomes.

Emeralda Sesari, Federica Sarro, Ayushi Rastogi

Software practitioners discuss problems at work with peers, in-person and online. These discussions can be technical (e.g., how to fix a bug?) and social (e.g., how to assign work fairly?). While there is a growing body of knowledge exploring fairness problems and solutions in the human and social factors of software engineering, most focus has been on specific problems. This study provides fairness discussions by software practitioners on Stack Exchange sites. We present an exploratory study presenting the fairness experience of software practitioners and fairness expectations in software teams. We also want to identify the fairness aspects software practitioners talk about the most. For example, do they care more about fairness in income or how they are treated in the workplace? Our investigation of fairness discussions on eight Stack Exchange sites resulted in a list of 136 posts (28 questions and 108 answers) manually curated from 4,178 candidate posts. The study reveals that the majority of fairness discussions (24 posts) revolve around the topic of income suggesting that many software practitioners are highly interested in matters related to their pay and how it is fairly distributed. Further, we noted that while not discussed as often, discussions on fairness in recruitment tend to receive the highest number of views and scores. Interestingly, the study shows that unfairness experiences extend beyond the protected attributes. In this study, only 25 out of 136 posts mention protected attributes, with gender mainly being discussed.

Zidu Yin, Zhen Zhang, Dong Gong et al.

Reinforcement Learning (RL) algorithms often struggle with low training efficiency. A common approach to address this challenge is integrating model-based planning algorithms, such as Monte Carlo Tree Search (MCTS) or Value Iteration (VI), into the environmental model. However, VI requires iterating over a large tensor which updates the value of the preceding state based on the succeeding state through value propagation, resulting in computationally intensive operations. To enhance the RL training efficiency, we propose improving the efficiency of the value learning process. In deterministic environments with discrete state and action spaces, we observe that on the sampled empirical state-transition graph, a non-branching sequence of transitions-termed a highway-can take the agent to another state without deviation through intermediate states. On these non-branching highways, the value-updating process can be streamlined into a single-step operation, eliminating the need for step-by-step updates. Building on this observation, we introduce the highway graph to model state transitions. The highway graph compresses the transition model into a compact representation, where edges can encapsulate multiple state transitions, enabling value propagation across multiple time steps in a single iteration. By integrating the highway graph into RL, the training process is significantly accelerated, particularly in the early stages of training. Experiments across four categories of environments demonstrate that our method learns significantly faster than established and state-of-the-art RL algorithms (often by a factor of 10 to 150) while maintaining equal or superior expected returns. Furthermore, a deep neural network-based agent trained using the highway graph exhibits improved generalization capabilities and reduced storage costs. Code is publicly available at https://github.com/coodest/highwayRL.

Jun Li, Mingliang Li, Hao Wu

In the maintenance engineering of asphalt pavement, it is often encountered that both the surface and middle layers are damaged and need to be maintained. The cold in-place recycling technology can be used to simultaneously treat multi-layer diseases and reduce the waste of pavement materials. The cold in-place recycling mixture is rarely used for high layer of pavement structure in high-grade highway. In the supporting practical engineering, the emulsified asphalt cold in-place recycling mixtures were paved as the middle layer of pavement structure by the laying of an overlay. In order to comprehensively evaluate the material performances, coring samples were drilled after cold recycling pavement opening to traffic, and different performance tests were carried out based on the coring samples. The newly paved SMA mixtures were set as the control group. The high temperature stability of cold recycling mixture was analyzed by dynamic creep test and MMLS3 accelerated loading test. Then, the cracking resistance of cold recycling mixture was studied by semi-circular bending test. Finally, the effect of curing time on splitting strength of cold recycling mixture was measured, and the moisture susceptibility was analyzed by dry–wet splitting test and freeze–thaw splitting test. The test results showed that the high temperature stability of cold recycling mixture was worse than SMA mixture. For the cold recycling mixture, the deformation value at the early stage and deformation rate at the stable stage were larger than SMA mixture in the accelerated loading process, and shear failure at high temperature occurred earlier. The cracking resistance of cold recycling mixture was worse than SMA mixture because of the aging effect of the old asphalt and adverse influence of the added cement binder. The effect of curing time on splitting strength of cold recycling mixture was significant, and two stable periods of early strength were, respectively, reached after curing 3 days and 7 days. The indexes of moisture susceptibility, including dry–wet splitting strength ratio and freeze–thaw splitting strength ratio, were obviously lower than that of SMA mixture, and the test values not up to the standard requirement existed. For the emulsified asphalt cold in-place recycling mixture, the improvement of material performances should be focused on, especially the moisture susceptibility. In the research, the emulsified asphalt cold in-place recycling mixtures were acceptably used as the middle layer of maintenance pavement structure. The reliable discussions were summarized based on coring samples collected from real-life road sections. The case can provide guidance and reference for similar engineering applications.

Widy Christianto Silamba, Isdaryanto Iskandar

The topography in Jayapura regency is generally an area consisting of mountains and valleys that have various elevations, and the transportation facilities are also diverse. Geometric evaluation on the Camp road section. Wolker – Buper Waena conducted a topographic survey of existing roads. To obtain geometric data, then geometric evaluation is carried out based on RSNI T-14-2004 (Guidelines for Geometric Planning of Urban Roads) and Inter-City Geometric Planning Procedures, Department of PU, Directorate General of Highways, 1997. Road pavement analysis based on the Road Pavement Design Manual of the Ministry of PU No. 04/SE/DB/2017 and the Regulation of the Minister of PU No. 04/SE/M/2010.The conclusion of the study on geometric evaluation of horizontal alinyemen roads on the bends PI – 10 and PI – 11 did not meet the standard provisions. Similarly, vertical alinyemen exceeds the maximum limit of road slump, which is 10%. The slump is at sta 0+450 – 0+650 and sta 0+800 – 1+400. Thus, it needs re-planning. Analysis of road pavement at the  Cbr point of the field > 6%, the basic soil strength class SG6. Basic soil improvement foundation structure stabilization segment or preferred heap material (compaction of ≤ layer 200 mm loose thickness), no need for improvement. Then for the field Cbr < 2.5%, the basic soil strength class SG1 with a support layer of 700 mm. For a field Cbr of 2.5%, the base soil strength class is SG2.5 with a minimum soil improvement thickness of 175 mm. For field Cbr, 3 % uses basic soil strength class SG3 with a minimum thickness of soil improvement of 150 mm. For a field Cbr of 4%, a base soil strength grade of SG4 with a minimum soil improvement thickness of 100 mm. The pavement layer design obtained AC WC = 40 mm, AC BC = 60 mm and LPA Class A adjusts the minimum thickness of soil improvement of each segment.

Anton Zheltobriukh, Ivan Kopynets, Vasiliy Golovchenko et al.

Introduction. One of the aspects of Ukraine's European integration is the introduction of European approaches to the design of asphalt mixtures. In Ukraine, as in other European countries, when designing the asphalt mixtures, asphalt concrete samples are made by compaction in the laboratory; however, different compaction methods are used for this purpose. Statement of the problem. In Ukraine, the method of compaction of asphalt mixtures in the laboratory at a pressure of (30.0 ± 0.3) MPa is used if the crushed stone content in the mixture is higher than or equal to 35%, or at a pressure of (40.0 ± 0.4) MPa if the crushed stone content in the mixture is up to 35%. In the countries of the European Union, the Marshall impact compaction method of 100 strokes (50 strokes on each side) is mainly used for this purpose. Therefore, it is advisable to determine the effect of the method of compaction of asphalt mixtures on the volumetric properties of asphalt concrete, depending on the largest nominal grain size of the aggregate and the compaction method.