Hasil untuk "Highway engineering. Roads and pavements"

Piotr Mackiewicz, Antoni Szydło

Abstract: Using Fieldorfa Street in Wrocław as an example, the impact of concrete pavement construction technology on selected performance characteristics was analyzed. The street in question was constructed in two sections. The first section was constructed using commercial technology without the use of dedicated concrete paving machines. The second section was constructed using specialized concrete pavers. Based on measurements of the longitudinal evenness index (IRI), the macrotexture index (MPD), and the coefficient of friction, it was found that there was variation in results between the sections, but significant variation in the evenness index. Keywords: Texture; Roughness; Concrete Pavement, OBSI, IRI, MPD

Lei Zhang

The quantum threat to cybersecurity has accelerated the standardization of Post-Quantum Cryptography (PQC). Migrating legacy software to these quantum-safe algorithms is not a simple library swap, but a new software engineering challenge: existing vulnerability detection, refactoring, and testing tools are not designed for PQC's probabilistic behavior, side-channel sensitivity, and complex performance trade-offs. To address these challenges, this paper outlines a vision for a new class of tools and introduces the Automated Quantum-safe Adaptation (AQuA) framework, with a three-pillar agenda for PQC-aware detection, semantic refactoring, and hybrid verification, thereby motivating Quantum-Safe Software Engineering (QSSE) as a distinct research direction.

Alexander Korn, Lea Zaruchas, Chetan Arora et al.

Large Language Models, particularly decoder-only generative models such as GPT, are increasingly used to automate Software Engineering tasks. These models are primarily guided through natural language prompts, making prompt engineering a critical factor in system performance and behavior. Despite their growing role in SE research, prompt-related decisions are rarely documented in a systematic or transparent manner, hindering reproducibility and comparability across studies. To address this gap, we conducted a two-phase empirical study. First, we analyzed nearly 300 papers published at the top-3 SE conferences since 2022 to assess how prompt design, testing, and optimization are currently reported. Second, we surveyed 105 program committee members from these conferences to capture their expectations for prompt reporting in LLM-driven research. Based on the findings, we derived a structured guideline that distinguishes essential, desirable, and exceptional reporting elements. Our results reveal significant misalignment between current practices and reviewer expectations, particularly regarding version disclosure, prompt justification, and threats to validity. We present our guideline as a step toward improving transparency, reproducibility, and methodological rigor in LLM-based SE research.

Mohamed Abouras, Catherine M. Elias

On and off-ramps are understudied road sections even though they introduce a higher level of variation in highway interactions. Predicting vehicles' behavior in these areas can decrease the impact of uncertainty and increase road safety. In this paper, the difference between this Area of Interest (AoI) and a straight highway section is studied. Multi-layered LSTM architecture to train the AoI model with ExiD drone dataset is utilized. In the process, different prediction horizons and different models' workflow are tested. The results show great promise on horizons up to 4 seconds with prediction accuracy starting from about 76% for the AoI and 94% for the general highway scenarios on the maximum horizon.

Ran Zhu, Hongxin Xie, Chen Chen et al.

To enhance the situational awareness and decision-making capabilities of intelligent vehicle active safety systems, this study proposes a methodology for defining dynamic, scenario-based thresholds. In simulations of emergency braking maneuvers, the safe braking distance serves as the primary criterion for performance evaluation. This study quantifies the sensitivity of vehicle braking performance to the attenuation of the pavement skid resistance coefficient under a matrix of typical operational conditions (e.g., dry vs. wet surfaces) and highway scenarios (e.g., open sections, tunnels) with varying design speeds. Through this sensitivity analysis, we identify the minimum skid resistance coefficient required to guarantee vehicle safety under the most adverse, yet plausible, conditions. The primary contribution is a set of proposed scenariospecific skid resistance thresholds, which are directly correlated with roadway design speeds. These thresholds serve as critical input parameters for intelligent transportation systems (ITS). They can be used to inform vehicle-to-infrastructure safety alerts and enable onboard ADAS to adapt their control strategies—such as adjusting braking distance predictions or slip ratio limits—thereby bridging the gap between road infrastructure condition and intelligent vehicle control.

Olufemi Jacob Oyekanmi, Ejem A. Ejem, K. C. Okafor et al.

The sustainability of Nigeria's federal highway network is increasingly undermined by persistent axle load violations among heavy goods vehicles (HGVs). Overloaded axles accelerate pavement deterioration, escalate lifecycle maintenance costs, and compromise freight system reliability. This study integrates engineering-based deterioration modelling with operations management principles to estimate pavement damage costs and develop a penalty-based financing framework. Using weigh-in-motion (WIM) systems, traffic and axle load data were collected across three freight-intensive corridors, namely Lokoja-Abuja, Ilorin-Jebba, and Abakaliki-Ogoja. Equivalent Single Axle Load (ESAL) analysis and econometric modelling were employed to quantify incremental damage and calibrate penalty functions. Findings reveal systemic overloading, with corridor-specific damage costs ranging from ₦0.74 to ₦5.70 per ESAL and violation rates exceeding 70% on high-intensity routes. A loglinear penalty model was developed, explaining over 80% of the variability in cost recovery estimates. The study demonstrates that monetizing axle load violations through calibrated penalties can transform enforcement into a sustainable financing mechanism. The contribution lies in extending operations management theory by embedding asset management, externality internalization, and game-theoretic principles into road infrastructure governance. The proposed model offers a scalable framework for enhancing infrastructure resilience, optimizing maintenance funding, and improving regulatory compliance in Nigeria and other Sub-Saharan African economies.

Muhammad Isradi, Nur Aini Ruhiat, Salsa Baidillah Pagit et al.

Road infrastructure design is an important aspect of regional development, especially in areas with high mobility such as Waled District, Cirebon Regency. This study aims to redesign the ±2.8 km section of Jl. Raya Waled Desa – Jl. Raya Jatimulya, Mekarjaya to meet the geometric standards for secondary collector roads as stipulated by the Directorate General of Highways. The research method was conducted through field surveys to obtain primary data on existing road conditions, topography, drainage, and traffic flow, which were then analyzed using civil engineering software such as Autodesk Civil 3D. The analysis results showed that the average width of the existing pavement was 5.5 meters with moderate to severe damage, so it needed to be widened to 6 meters to meet the standards. The maximum slope value of 3.2% is still within tolerance limits, but several points require elevation improvements to overcome flooding. Curve analysis shows that several segments have a radius of less than 90 meters, so superelevation improvements and curve widening are needed to ensure vehicle safety. Traffic load calculations (ESA5) show a total design load of 6,491,947 ESA (left direction) and 8,712,590 ESA (right direction), which are used as the basis for pavement thickness planning. In addition, a hydrological analysis using the Manning method resulted in a channel capacity of 1,643 m³/second with a flow velocity of 0.6 m/second, indicating that the drainage system needs improvement to accommodate rainwater runoff.

Vitalii Vasylyshyn

Summary Introduction. Architecture and construction have always been important factors in the formation of the cultural, economic and social face of any region. This is especially true of the Carpathian region, a territory characterized by diverse natural conditions, rich history and unique traditions. The development of architecture in these lands took place in constant interaction with the natural environment, historical and political circumstances and social needs of the population. The study of this topic is relevant, as it makes it possible to trace the formation of architectural thought in the region, identify its features, determine the influence of external cultural factors and understand the role of the Carpathian region in the general context of the development of Ukrainian architecture. The article considers a wide range of issues related to the formation and transformation of the architectural environment of the Carpathian region. The stages of the development of architecture are highlighted — from the Old Russian period, when wooden sacral buildings dominated, to the Baroque, Classicism and Art Nouveau eras, which brought new forms and stylistic solutions to the region. Considerable attention is paid to folk architecture, which was formed under the influence of natural conditions and economic needs. Traditional wooden architecture of the Carpathians is a unique phenomenon that has become part of the cultural heritage not only of Ukraine, but also of Europe. Characteristic features are the use of local materials, organic integration with the landscape, as well as the symbolic fullness of architectural forms. Purpose. A special place in the study is occupied by the sacred architecture of the region. Churches, monasteries and chapels constitute a significant part of the architectural heritage of the Carpathians. They not only performed religious functions, but also served as centers of education, culture and national identity. The wooden churches of the Hutsul region and Boykiv region, which are included in the UNESCO World Heritage List, are examples of a unique architectural phenomenon. Their original compositional structure, decorative decoration and harmony with the natural environment have become a symbol of deep spirituality and high skill of local builders.

Tatyana Tereshchenko

Introduction. The introduction to the paper highlights the actuality of the issues of the design of roads/streets junctions within built-up areas. Problem statement. The topic of the paper concerns the advantages, as well as general issues of design and performance of at-grade junctions including roundabouts — PRC (German: der Kreisverkehr) compared to other types of roads and streets junctions within built-up areas. The topic of the paper concerns the advantages of PRC (English: roundabout, German: der Kreisverkehr) compared to other types of roads / streets junctions within built-up areas, as well as general issues of the design and operation of PRC. Purpose. The purpose of the paper is a general analysis of the experience of EU countries in design of roads / streets junctions within built-up areas and highlighting solutions that are priority in terms of road user safety and the operational efficiency of such junctions. Results. A general comparative analysis of various types of roads/streets junctions within built-up areas, including the PRC, has been carried out and the recognized advantages and basic requirements for the design and features of the PRC’s operation within built-up areas according to the experience of EU countries have been highlighted. The issue of compatibility of terms definition within the scope of the analysis was briefly reviewed.

Marc Bruni, Fabio Gabrielli, Mohammad Ghafari et al.

Prompt engineering reduces reasoning mistakes in Large Language Models (LLMs). However, its effectiveness in mitigating vulnerabilities in LLM-generated code remains underexplored. To address this gap, we implemented a benchmark to automatically assess the impact of various prompt engineering strategies on code security. Our benchmark leverages two peer-reviewed prompt datasets and employs static scanners to evaluate code security at scale. We tested multiple prompt engineering techniques on GPT-3.5-turbo, GPT-4o, and GPT-4o-mini. Our results show that for GPT-4o and GPT-4o-mini, a security-focused prompt prefix can reduce the occurrence of security vulnerabilities by up to 56%. Additionally, all tested models demonstrated the ability to detect and repair between 41.9% and 68.7% of vulnerabilities in previously generated code when using iterative prompting techniques. Finally, we introduce a "prompt agent" that demonstrates how the most effective techniques can be applied in real-world development workflows.

Shavindra Wickramathilaka, John Grundy, Kashumi Madampe et al.

The use of diverse mobile applications among senior users is becoming increasingly widespread. However, many of these apps contain accessibility problems that result in negative user experiences for seniors. A key reason is that software practitioners often lack the time or resources to address the broad spectrum of age-related accessibility and personalisation needs. As current developer tools and practices encourage one-size-fits-all interfaces with limited potential to address the diversity of senior needs, there is a growing demand for approaches that support the systematic creation of adaptive, accessible app experiences. To this end, we present AdaptForge, a novel model-driven engineering (MDE) approach that enables advanced design-time adaptations of mobile application interfaces and behaviours tailored to the accessibility needs of senior users. AdaptForge uses two domain-specific languages (DSLs) to address age-related accessibility needs. The first model defines users' context-of-use parameters, while the second defines conditional accessibility scenarios and corresponding UI adaptation rules. These rules are interpreted by an MDE workflow to transform an app's original source code into personalised instances. We also report evaluations with professional software developers and senior end-users, demonstrating the feasibility and practical utility of AdaptForge.

Qiaolin Qin, Ronnie de Souza Santos, Rodrigo Spinola

Context. The rise of generative AI (GenAI) tools like ChatGPT and GitHub Copilot has transformed how software is learned and written. In software engineering (SE) education, these tools offer new opportunities for support, but also raise concerns about over-reliance, ethical use, and impacts on learning. Objective. This study investigates how undergraduate SE students use GenAI tools, focusing on the benefits, challenges, ethical concerns, and instructional expectations that shape their experiences. Method. We conducted a survey with 130 undergraduate students from two universities. The survey combined structured Likert-scale items and open-ended questions to investigate five dimensions: usage context, perceived benefits, challenges, ethical and instructional perceptions. Results. Students most often use GenAI for incremental learning and advanced implementation, reporting benefits such as brainstorming support and confidence-building. At the same time, they face challenges including unclear rationales and difficulty adapting outputs. Students highlight ethical concerns around fairness and misconduct, and call for clearer instructional guidance. Conclusion. GenAI is reshaping SE education in nuanced ways. Our findings underscore the need for scaffolding, ethical policies, and adaptive instructional strategies to ensure that GenAI supports equitable and effective learning.

Mauro Marcelino, Marcos Alves, Bianca Trinkenreich et al.

[Context] An evidence briefing is a concise and objective transfer medium that can present the main findings of a study to software engineers in the industry. Although practitioners and researchers have deemed Evidence Briefings useful, their production requires manual labor, which may be a significant challenge to their broad adoption. [Goal] The goal of this registered report is to describe an experimental protocol for evaluating LLM-generated evidence briefings for secondary studies in terms of content fidelity, ease of understanding, and usefulness, as perceived by researchers and practitioners, compared to human-made briefings. [Method] We developed an RAG-based LLM tool to generate evidence briefings. We used the tool to automatically generate two evidence briefings that had been manually generated in previous research efforts. We designed a controlled experiment to evaluate how the LLM-generated briefings compare to the human-made ones regarding perceived content fidelity, ease of understanding, and usefulness. [Results] To be reported after the experimental trials. [Conclusion] Depending on the experiment results.

Max Ofsa, Taylan G. Topcu

Systems engineering (SE) is evolving with the availability of generative artificial intelligence (AI) and the demand for a systems-of-systems perspective, formalized under the purview of mission engineering (ME) in the US Department of Defense. Formulating ME problems is challenging because they are open-ended exercises that involve translation of ill-defined problems into well-defined ones that are amenable for engineering development. It remains to be seen to which extent AI could assist problem formulation objectives. To that end, this paper explores the quality and consistency of multi-purpose Large Language Models (LLM) in supporting ME problem formulation tasks, specifically focusing on stakeholder identification. We identify a relevant reference problem, a NASA space mission design challenge, and document ChatGPT-3.5's ability to perform stakeholder identification tasks. We execute multiple parallel attempts and qualitatively evaluate LLM outputs, focusing on both their quality and variability. Our findings portray a nuanced picture. We find that the LLM performs well in identifying human-focused stakeholders but poorly in recognizing external systems and environmental factors, despite explicit efforts to account for these. Additionally, LLMs struggle with preserving the desired level of abstraction and exhibit a tendency to produce solution specific outputs that are inappropriate for problem formulation. More importantly, we document great variability among parallel threads, highlighting that LLM outputs should be used with caution, ideally by adopting a stochastic view of their abilities. Overall, our findings suggest that, while ChatGPT could reduce some expert workload, its lack of consistency and domain understanding may limit its reliability for problem formulation tasks.

A. Onyshchenko, I. Soloviov, Serhiy Khudolii et al.

Abstract. The article is devoted to the analysis of the stress-strain state of a rigid pavement structure, arranged on a multilayer basis, depending on various options for the location of the axial transport load and the design features of the concrete layer. The purpose of the work is to carry out finite element modeling of the stress-strain state of a concrete pavement of a highway, which is arranged on a multilayer basis and contains expansion joints between the plates, depending on various options for the location of the load relative to the expansion joints and structural features of the concrete pavement, such as its modulus of elasticity and thickness. The object of study is concrete slab for road pavement. Research method: statistical analysis of scientific publications, technical and regulatory literature, numerical calculation using the finite element method. Considering that a complex spatial load acts on the concrete pavement of a highway, it is advisable to use a numerical method for determining the stress-strain state of a pavement based on solving the equations of elasticity theory - the finite element method as the most universal and effective. Its feature is a direct transition from a continuous object to a discrete analysis by dividing the area of the object under study into a number of subareas and approximating the fields of displacements, forces, stresses, for example, using an engineering and calculation complex. Three options for the location of transport loading are considered. As a result of the performed numerical modeling, the analysis of the stress-strain state of the cement concrete pavement was carried out, taking into account various design parameters, which makes it possible to establish the areas of stress concentration and predict the nature of the destruction of the cement concrete pavement. Key words: automobile road, concrete covering, transport loads, stress fields, stress-strain state.

Yong shun Zhao Yong shun Zhao

Pavement distress detection forms a fundamental part of highway maintenance, among which cracks are the most common type of defect. Cracks not only compromise the structural integrity and aesthetic appearance of the pavement, but may also pose serious risks to driving safety. Traditional inspection methods often suffer from low efficiency, high labor costs, insufficient accuracy, and potential disruptions to traffic flow, highlighting the urgent need for more advanced alternatives. With the rapid advancement of computer vision and deep learning technologies, automated approaches based on object detection have been widely adopted in pavement distress inspection. Simultaneously, unmanned aerial vehicles (UAVs) have demonstrated significant potential in pavement image acquisition due to their high mobility, low cost, and ease of operation. This paper proposes a novel pavement crack detection method that integrates deep learning algorithms with UAV aerial imagery, aiming to achieve automated crack identification and precise localization. The proposed approach significantly improves detection efficiency and accuracy, offering strong engineering adaptability and promising potential for widespread application. It provides an effective technical foundation for the intelligent development of road maintenance

王建光 Jianguang Wang

Abstract： In the construction of secondary highways, the subgrade serves as the foundation of the pavement, and its construction quality directly affects the overall performance and service life of the highway. Currently, subgrade construction of secondary highways often faces various problems, such as improper foundation treatment, inadequate control of fill materials, insufficient compaction quality, and slope instability. If these issues are not effectively addressed, they will significantly impair the bearing capacity, stability, and durability of the highway. Therefore, systematically analyzing common problems in subgrade construction and proposing scientific and feasible quality control and technical countermeasures are of critical engineering practical value for improving the quality of secondary highways, ensuring driving safety, and extending the road's service life. This study aims to provide theoretical references and practical guidance for standardizing and refining subgrade construction of similar highways by examining typical problems in construction processes and exploring corresponding countermeasures.

Haoyu Sun, Xiaoming Yi, Zongjun Pan et al.

Reinforcement learning (RL) has been widely applied in decision-making and decision-optimization tasks. This work proposes a feasible framework which adapts the RL to achieve scientific decision-making for highway maintenance by formulating an explicable reward function which uses optimal maintenance strategy selection as essential evidence. To this end, the proposed method (1) uses historical data on pavement distress to predict the rating of highway performance (state sequence) in the next 1–5 years; (2) mixes the highway maintenance records and the necessary road information to construct management preferences and maintenance (action) sequence; (3) uses the traffic volume records and the output data from previous steps to construct the reward function. From experiments, after training the agent in this framework with an in-home dataset collected from engineering, it shows an efficient convergence and makes similar decisions as human experts. Even for the discrepant cases, our agent still gives more scientific plans than the human experts considering its effects on maintaining relatively high performance of highway.

A. Ramadhani, Syamsul Arifin, Novita Pradani

The use of LDPE plastic waste in asphalt mixtures is an innovation aimed at improving road pavement quality while reducing environmental pollution. The purpose of this study was to determine the effect of heating temperature on the stability value of conventional asphalt mixtures and modified LDPE plastic mixtures (AC-WC) through Marshall characteristic testing. It also examined changes in microscopic structure using SEM and changes in chemical composition using X-Ray Fluorescence. This study used a laboratory experimental method with varying LDPE content and asphalt heating temperatures (135°C for conventional asphalt, and 165°C, 170°C, 175°C, and 180°C for modified asphalt). The study was conducted at the Transportation and Highway Laboratory, Faculty of Engineering, Tadulako University, and the Integrated Laboratory of Tadulako University. The results showed that the addition of LDPE significantly increased the stability of the mixture, with the highest value of 2236.09 kg at a content of 1% and a temperature of 180°C, meeting the 2018 Bina Marga specifications. SEM analysis revealed the best microscopic structure at a 0.25% LDPE content (temperature 165°C), with a homogeneous distribution and reduced microcracks, while high content (>0.75%) caused agglomeration. XRF analysis showed an increase in light elements from LDPE, with fluctuations in SiO₂, Al₂O₃, and MgO, without disturbing the balance of the main minerals.

J. Waani, Mecky R. E. Manoppo, Agnes T. Mandagi

Expansive clays is one of the problematic soils which cause numerous problems in pavement engineering and construction such as on airports, highways and roads. Although cement is widely used commonly perceived as the most conventional materials used in treating expansive soils in geotechnical and geoenvironmental engineering applications, of treating expansive soils the increasing trend of cement production has resulted in considerable environmental issues like raising the greenhouse gas emission. The present investigation aims at documenting the effect of adding zeolite a natural pozzolans as a supplementary cementitious material - on the mechanical and physical behaviour of cement stabilized expansive soil mixture. Specifically the Influence of cement-zeolite ratio and level. Soil samples for testing consisted of two different mixtures, namely Clay Soil with 15% bentonite addition and Clay Soil without bentonite addition, each with five binder contents (5%, 7%,10%, 12%, 14%) and various cement to zeolite ratios (5:0; 7:0; 5:5; 7:3; 5:7; 7:5; 5:9; 7:7) were prepared for experimentation. Tests conducted on all soil mixture samples, namely Compaction Test, CBR and UCS revealed that the effectiveness of adding zeolite on the strength of expansive clay soil mixtures is at cement-zeolite percentages of 10%; 12% and 14%, at all cement-zeolite ratios.