Hasil untuk "Highway engineering. Roads and pavements"

Volodymyr Abramov

ntroduction. In order to improve the design methodology, particularly in the calculation of transport construction objects made of metal corrugated structures (MCS) with increased hole size (small bridges and arch-shaped overpasses, drainage pipes under road embankments), which are still relatively new in our country, it is important to have a better understanding of the features of different approaches to calculation and their impact on the results. Problem Statement. The current regulatory and methodological documents in our country concerning the design of road structures made of corrugated metal [1] include a methodology for analytical calculation of such structures only in the form of round pipes with a diameter of up to 6 meters and it requires improvement, while structures of other shapes and sizes are recommended to be calculated using the finite element method (FEM). It is advisable to improve and supplement the existing normative analytical methodology for calculating structures made of corrugated metal with a better understanding of the characteristics of existing approaches.

Muhammad Naveed, Nazia Perwaiz, Sidra Sultana et al.

Road traffic accidents remain a major public health challenge, particularly in countries with heterogeneous road conditions, mixed traffic flow, and variable driving discipline, such as Pakistan. Reliable detection of unsafe driving behaviours is a prerequisite for improving road safety, enabling advanced driver assistance systems (ADAS), and supporting data driven decisions in insurance and fleet management. Most of existing datasets originate from the developed countries with limited representation of the behavioural diversity observed in emerging economies and the driver's face recording voilates the privacy preservation. We present V-SenseDrive, the first privacy-preserving multimodal driver behaviour dataset collected entirely within the Pakistani driving environment. V-SenseDrive combines smartphone based inertial and GPS sensor data with synchronized road facing video to record three target driving behaviours (normal, aggressive, and risky) on multiple types of roads, including urban arterials, secondary roads, and motorways. Data was gathered using a custom Android application designed to capture high frequency accelerometer, gyroscope, and GPS streams alongside continuous video, with all sources precisely time aligned to enable multimodal analysis. The focus of this work is on the data acquisition process, covering participant selection, driving scenarios, environmental considerations, and sensor video synchronization techniques. The dataset is structured into raw, processed, and semantic layers, ensuring adaptability for future research in driver behaviour classification, traffic safety analysis, and ADAS development. By representing real world driving in Pakistan, V-SenseDrive fills a critical gap in the global landscape of driver behaviour datasets and lays the groundwork for context aware intelligent transportation solutions.

Haoxuan Wang, Yifan Wang, Xu Liang et al.

Dislocations are line defects in crystalline solids and often exert a significant influence on the mechanical properties of metals. Recently, there has been a growing interest in using dislocations in ceramics to enhance materials performance. However, dislocation engineering has frequently been deemed uncommon in ceramics owing to the brittle nature of ceramics. Contradicting this conventional view, various approaches have been used to introduce dislocations into ceramic materials without crack formation, thereby paving the way for controlled ceramics performance. However, the influence of dislocations on functional properties is equally complicated owing to the intricate structure of ceramic materials. Furthermore, despite numerous experiments and simulations investigating dislocation-controlled properties in ceramics, comprehensive reviews summarizing the effects of dislocations on ceramics are still lacking. This review focuses on some representative dislocation-controlled properties of ceramic materials, including mechanical and some key functional properties, such as transport, ferroelectricity, thermal conductivity, and superconducting properties. A brief integration of dislocations in ceramic is anticipated to offer new insights for the advancement of dislocation engineering across various disciplines.

Xin Bi, Zhichao Li, Yuxuan Xia et al.

Accurate online map matching is fundamental to vehicle navigation and the activation of intelligent driving functions. Current online map matching methods are prone to errors in complex road networks, especially in multilevel road area. To address this challenge, we propose an online Standard Definition (SD) map matching method by constructing a Hidden Markov Model (HMM) with multiple probability factors. Our proposed method can achieve accurate map matching even in complex road networks by carefully leveraging lane markings and scenario recognition in the designing of the probability factors. First, the lane markings are generated by a multi-lane tracking method and associated with the SD map using HMM to build an enriched SD map. In areas covered by the enriched SD map, the vehicle can re-localize itself by performing Iterative Closest Point (ICP) registration for the lane markings. Then, the probability factor accounting for the lane marking detection can be obtained using the association probability between adjacent lanes and roads. Second, the driving scenario recognition model is applied to generate the emission probability factor of scenario recognition, which improves the performance of map matching on elevated roads and ordinary urban roads underneath them. We validate our method through extensive road tests in Europe and China, and the experimental results show that our proposed method effectively improves the online map matching accuracy as compared to other existing methods, especially in multilevel road area. Specifically, the experiments show that our proposed method achieves $F_1$ scores of 98.04% and 94.60% on the Zenseact Open Dataset and test data of multilevel road areas in Shanghai respectively, significantly outperforming benchmark methods. The implementation is available at https://github.com/TRV-Lab/LMSR-OMM.

Cesar Portocarrero Rodriguez, Laura Vandeweyen, Yosuke Yamamoto

The American Society of Civil Engineers has graded Americas infrastructure condition as a C, with the road system receiving a dismal D. Roads are vital to regional economic viability, yet their management, maintenance, and repair processes remain inefficient, relying on outdated manual or laser-based inspection methods that are both costly and time-consuming. With the increasing availability of real-time visual data from autonomous vehicles, there is an opportunity to apply computer vision (CV) methods for advanced road monitoring, providing insights to guide infrastructure rehabilitation efforts. This project explores the use of state-of-the-art CV techniques for road distress segmentation. It begins by evaluating synthetic data generated with Generative Adversarial Networks (GANs) to assess its usefulness for model training. The study then applies Convolutional Neural Networks (CNNs) for road distress segmentation and subsequently examines the transformer-based model MaskFormer. Results show that GAN-generated data improves model performance and that MaskFormer outperforms the CNN model in two metrics: mAP50 and IoU.

Anton Zheltobriukh, Ivan Kopynets, Vasiliy Golovchenko et al.

ntroduction. DSTU EN 13108-1 establishes requirements for asphalt mixtures used for the arrangement of pavement layers of roads, airfields, etc. These asphalt mixtures are used for arranging the base layer, binding layer, and a surface layer. Problem statement. A special feature of DSTU EN 13108-1 is that it establishes general requirements for all indicators, in particular for grading. That is there are no specific requirements for the grading of asphalt mixtures depending on the road category, traffic loading and the location of the asphalt concrete layer in the road pavement structure. Therefore, it is advisable to consider in detail the requirements for the grading of asphalt mixtures, compare them with the requirements of national standards and propose appropriate national requirements. Purpose. Establishment of national requirements for the grading of asphalt mixtures according to DSTU EN 13108-1. Materials and methods. Analysis of literary sources, comparison of the requirements of regulatory documents for the grading of asphalt concrete mixtures.

Mukola Hukov, Mykhailo Dulia

Introduction. Various contactless vehicle identification systems on public roads are widely used in global practice. They solve a wide range of problems, from tracking traffic flows and collecting tolls for road usage to designating parking spots and digital identification. A key role in implementing the state's transportation strategy is played by the development of transport infrastructure, the most crucial component of which is the public road network of national importance. This network has suffered damage due to the full-scale invasion by the Russian Federation. The network is vital for the country's defense logistics, industrial and agricultural efficiency, and ensuring adequate societal communication. The main source of road infrastructure funding is the Road Fund, formed from revenues from excise duties and import tariffs on petroleum products, as well as excise duties and import tariffs on vehicles and tires imported into Ukraine. Problem Statement. To increase state budget revenues, it is necessary to introduce a socially fair road toll for heavy vehicles with a maximum permissible gross weight of 12 tons or more on public roads. The wear and tear on road surfaces caused by trucks is significantly greater than that caused by other vehicles. Road tolls should be collected based on the damage inflicted by a vehicle on the roads, which requires developing a scheme for terminal placement to collect vehicle movement data (hereafter referred to as terminals) on public roads of national importance, along with algorithms for determining the traveled distance.

Rasmus Adler, Frank Elberzhager, Florian Balduf

Engineering a sustainable world requires to consider various systems that interact with each other. These systems include ecological systems, economical systems, social systems and tech-nical systems. They are loosely coupled, geographically distributed, evolve permanently and generate emergent behavior. As these are characteristics of systems of systems (SoS), we discuss the engi-neering of a sustainable world from a SoS engineering perspective. We studied SoS engineering in context of a research project, which aims at political recommendations and a research roadmap for engineering dynamic SoS. The project included an exhaustive literature review, interviews and work-shops with representatives from industry and academia from different application domains. Based on these results and observations, we will discuss how suitable the current state-of-the-art in SoS engi-neering is in order to engineer sustainability. Sustainability was a major driver for SoS engineering in all domains, but we argue that the current scope of SoS engineering is too limited in order to engineer sustainability. Further, we argue that mastering dynamics in this larger scope is essential to engineer sustainability and that this is accompanied by dynamic adaptation of technological SoS.

Pou-Chun Kung, Xianling Zhang, Katherine A. Skinner et al.

Photorealistic 3D scene reconstruction plays an important role in autonomous driving, enabling the generation of novel data from existing datasets to simulate safety-critical scenarios and expand training data without additional acquisition costs. Gaussian Splatting (GS) facilitates real-time, photorealistic rendering with an explicit 3D Gaussian representation of the scene, providing faster processing and more intuitive scene editing than the implicit Neural Radiance Fields (NeRFs). While extensive GS research has yielded promising advancements in autonomous driving applications, they overlook two critical aspects: First, existing methods mainly focus on low-speed and feature-rich urban scenes and ignore the fact that highway scenarios play a significant role in autonomous driving. Second, while LiDARs are commonplace in autonomous driving platforms, existing methods learn primarily from images and use LiDAR only for initial estimates or without precise sensor modeling, thus missing out on leveraging the rich depth information LiDAR offers and limiting the ability to synthesize LiDAR data. In this paper, we propose a novel GS method for dynamic scene synthesis and editing with improved scene reconstruction through LiDAR supervision and support for LiDAR rendering. Unlike prior works that are tested mostly on urban datasets, to the best of our knowledge, we are the first to focus on the more challenging and highly relevant highway scenes for autonomous driving, with sparse sensor views and monotone backgrounds. Visit our project page at: https://umautobots.github.io/lihi_gs

Edson OliveiraJr, Fernanda Madeiral, Alcemir Rodrigues Santos et al.

Open Science aims to foster openness and collaboration in research, leading to more significant scientific and social impact. However, practicing Open Science comes with several challenges and is currently not properly rewarded. In this paper, we share our vision for addressing those challenges through a conceptual framework that connects essential building blocks for a change in the Software Engineering community, both culturally and technically. The idea behind this framework is that Open Science is treated as a first-class requirement for better Software Engineering research, practice, recognition, and relevant social impact. There is a long road for us, as a community, to truly embrace and gain from the benefits of Open Science. Nevertheless, we shed light on the directions for promoting the necessary culture shift and empowering the Software Engineering community.

Muhammad Ramdhan Olii, Azhar A Wahab, Ilyas Ichsan et al.

Perkembangan infrastruktur berbanding lurus dengan tingkat kebutuhan akan semen sebagai bahan utama dalam konstruksi bangunan.  Industri semen menghasilkan 8-10% dari total emisi CO2 dunia. Penelitian ini bertujuan untuk menemukan alternatif atau penggantian sebagian material beton hijau sehingga meminimalkan dampak lingkungan dari pembuatan beton dan meningkatkan kekuatan beton, salah satunya adalah fly ash. Fly ash dapat digunakan bersama dengan semen portland dalam beton yang berkontribusi terhadap sifat-sifat beton melalui aktivitas hidrolik atau pozzolan, atau keduanya. Hasil pengujian kuat tekan karakteristik beton dengan substitusi parsial semen dengan variasi fly ash (9%, 9.5%, 10%, dan 10.5%) pada umur 28 hari adalah masing-masing 36.70 Mpa, 35.11 Mpa, 33.37 Mpa, dan 30.38 Mpa. Kuat tekan beton meningkat sebesar 5% pada variasi fly ash sebesar 9% dan 9.5% dan menurun sebesar 13% pada variasi fly ash sebesar 10% dan 10.5%. Dari hasil tersebut dapat disimpulkan bahwa semakin besar persentase penggunaan fly ash sebagai subtitusi parsial semen maka semakin menurun kuat tekannya. Jumlah optimum fly ash bervariasi sangat bergantung pada komposisi dan proporsi semua bahan dalam campuran beton (terutama fly ash), kondisi selama penempatan (terutama suhu), praktik konstruksi (misalnya, finishing dan curing) dan kondisi paparan. Dengan demikian, kadar fly ash yang optimal akan bervariasi berdasarkan kasus per kasus.

Janusz Dyduch, Adam Pawlik

Abstract: This article analyzes the network of railway lines located within the Poznań Metropolitan Area (POM) concerning the improvement of service quality provided by rail transport to residents. It is assumed that the optimal solution ensuring proper communication services in the context of increasing road congestion due to rising car traffic is rail transport. At the beginning of the article, a description and evaluation of the layout and operational parameters of the railway lines located within the Poznań Metropolitan Area are presented, with particular emphasis on nine (9) railway lines radiating from the Poznań Railway Junction. The conducted evaluation serves to formulate conclusions aimed at identifying the needs for complementing the existing track network in future financial perspectives for the development of railway infrastructure. Keywords: Railway infrastructure; Poznań Metropolitan Railway; Poznań Railway Junction

Alina Yunak, Ivan Kopynets, Oksana Sokolova

Introduction. Stone mastic asphalt mixtures are probably the most popular road construction material for paving roads not only in Ukraine but also around the world. State construction standards provide for the mandatory use of SMA mixtures for paving roads of category I, and it is also possible to use SMA mixtures for paving roads of II – III categories. Problem Statement. For the first time, the properties of SMA mixtures, as well as stone mastic asphalt concrete, were standardized in DSTU B V.2.7-127 in 2016. Since then, two amendments to this standard have been developed (2012 and 2014), its revision has been carried out (2015), an amendment to the revised standard has been developed (2019) and another revision is currently underway. Thus, we can conclude that there is a significant interest in these road construction materials. In 2018, as part of its European integration efforts, Ukraine adopted DSTU EN 13108-5 which sets harmonized requirements for SMA mixtures and SMA used in the European Union. However, this standard has not yet been implemented in Ukraine, which is due to the lack of specific requirements for SMA mixtures, SMA, as well as their components depending on the field of application. In the literature sources, it is almost impossible to find information on the establishment of requirements for SMA mixtures and SMA, as well as their components during the development of DSTU B V.2.7-127 with regard to climatic conditions and traffic load, which is obviously due to the significant affinity of this standard with the Soviet one. Therefore, to be able to establish national requirements for SMA mixtures and SMA in accordance with DSTU EN 13108-5, it is advisable to perform a detailed analysis of the literature sources on this issue.

Meng Guo, Xiupeng Yao, Xiuli Du

Low temperature cracking (LTC) distress on pavement seriously affects road life. This paper finished a literature review of the research on the mechanism of LTC of asphalt composites (asphalt composites refers to asphalt binder and asphalt mixture in this article), test methods, factors contributing to LTC, measures to prevent and control the distress, and prediction of LTC in asphalt pavements. The following conclusions were obtained: the cracking mechanism of asphalt mixtures needs to be further revealed by means of simulation at the micro level, the BBR and 4 ​mm plate test (by DSR) methods are currently optimal, and a correlation between asphalt and asphalt mixture evaluation indexes needs to be established. Sensitivity analyses are needed for the factors affecting LTC of asphalt mixtures. It is necessary to calculate the contribution of each factor to the LTC of asphalt mixtures. The aim is to propose targeted improvement measures for the most unfavourable factors, as well as to carry out research and development of key materials for anti-cracking. Measures for the prevention and control of LTC of asphalt pavement are analyzed and discussed. Existing researches on the prediction of LTC of asphalt pavements is discussed. It is necessary to analyse the mechanical response of asphalt pavement, the damage process and the sensitivity of anti-cracking parameters on the basis of considering the complex geometrical characteristics and material properties of asphalt pavement materials. Finally, the mechanism of LTC, evaluation methods, factors influencing LTC, and remedial measures for asphalt composites were summarized, and future research prospects were suggested. This paper provides theoretical support for the further solution of LTC distress of asphalt pavement, which is effective on the improvement of pavement life.

Javed Iqbal, Aliza Masood, Waqas Sultani et al.

Getting precise aspects of road through segmentation from remote sensing imagery is useful for many real-world applications such as autonomous vehicles, urban development and planning, and achieving sustainable development goals. Roads are only a small part of the image, and their appearance, type, width, elevation, directions, etc. exhibit large variations across geographical areas. Furthermore, due to differences in urbanization styles, planning, and the natural environments; regions along the roads vary significantly. Due to these variations among the train and test domains, the road segmentation algorithms fail to generalize to new geographical locations. Unlike the generic domain alignment scenarios, road segmentation has no scene structure, and generic domain adaptation methods are unable to enforce topological properties like continuity, connectivity, smoothness, etc., thus resulting in degraded domain alignment. In this work, we propose a topology-aware unsupervised domain adaptation approach for road segmentation in remote sensing imagery. Specifically, we predict road skeleton, an auxiliary task to impose the topological constraints. To enforce consistent predictions of road and skeleton, especially in the unlabeled target domain, the conformity loss is defined across the skeleton prediction head and the road-segmentation head. Furthermore, for self-training, we filter out the noisy pseudo-labels by using a connectivity-based pseudo-labels refinement strategy, on both road and skeleton segmentation heads, thus avoiding holes and discontinuities. Extensive experiments on the benchmark datasets show the effectiveness of the proposed approach compared to existing state-of-the-art methods. Specifically, for SpaceNet to DeepGlobe adaptation, the proposed approach outperforms the competing methods by a minimum margin of 6.6%, 6.7%, and 9.8% in IoU, F1-score, and APLS, respectively.

Eligiusz Mieloszyk, Anita Milewska, Mariusz Wyroślak

Abstract: After analyzing the impact of aircraft on the airport pavement (parking spaces, runways, startways), it was considered advisable to consider the problem of deep improvement or strengthening of its subsoil. This is especially true for low-bearing soil. The paper presents a quick and effective method of strengthening the subsoil intended for the construction of engineering structures used for civil or military air operations. It allows the use of wastelands, wetlands, swamps, etc. for the above-mentioned purposes, thus creating a dispersed network of landing sites increasing the security of the country and increasing the availability of air transport for large society groups. Keywords: Runways; Runways load; Ground reinforcement; Blasting agents

Alina Yunak, Ivan Kopynets, Oksana Sokolova

Introduction. Currently, in Ukraine, there are restrictions on the traffic of vehicles with an actual weight of more than 24 tons and an axle loading of 7 tons during the day at an air temperature above 28 °C, except for vehicles carrying dangerous, perishable goods, live animals and poultry, and as well as transportation related to the prevention or liquidation of the consequences of emergency situations. An air temperature of 28 °C is considered to be the temperature at which the road pavement structure under the influence of dynamic loadings can sharply lose its load-bearing capacity, which is one of the conditions under which a threat to traffic safety is created or roads can be damaged and destroyed. Problem statement. The analysis of the regulatory documentation showed that during designing of pavement structure, the climatic conditions of asphalt concrete performance should be taken into account and pavement must withstand the accumulation of plastic strains in summer, which requires measures to ensure its rutting resistance. At the same time, the algorithm for ensuring rut stability does not exist yet. It is quite likely that this issue can be resolved by performing appropriate research work and implementing harmonized European standards, respectively, by amending the building codes, etc. However, the question arises whether we do not perform the requirements of the regulatory documentation and design the pavement structure without considering the climatic conditions and ensuring the rut resistance of asphalt pavement, or still comply with these requirements, which should be clarified. Objective. Development of criteria for analyzing the performance conditions of asphalt concrete in the pavement structure and ensuring its rutting resistance during operation. Materials and methods. Prerequisites for the establishment of restrictions on the movement of freight vehicles at air temperatures above 28 ° C, analysis of operating conditions of asphalt concrete in the construction of pavement. Results. According to the results of the work, the influence of temperature, bitumen properties and loading time on the change of asphalt concrete properties has been established. Criteria for the analysis of climatic conditions of asphalt concrete have been developed and criteria for taking into account operating conditions have been established. Approximate bitumen grades for ensuring the asphalt concrete rutting resistance have been established on the basis of establishing the relationship between the standard properties of bitumen and operating properties. Conclusions. For evaluation of possible rut formation resistance of asphalt concrete, it is needed to perform an analysis by the bitumen grade in its composition, the total number of passes of vehicles with estimated loadings during the pavement operational term, the category of road, the type of asphalt concrete, the speed of traffic, as well as the year of pavement arrangement. In order to ensure the rut resistance of asphalt concrete, it is advisable to use the established criteria in the future during the pavement design.

Filippo Giammaria Praticò

Despite almost a century of studies dealing with traffic noise, researchers and practitioners still face old and new issues when designing a low-noise pavement. Given that, this manuscript aims at focusing on a number of unsolved questions, namely theoretical or technological. 1) Is it viable to balance diverse road-related needs (i.e., noise, expected life, texture levels, and friction)? 2) How much does the pavement material affect its acoustic performance (the remaining factors being constant)? 3) How much reliable is the relationship between road texture and mixture aggregate gradation? Based on the analysis of these issues, it emerges that: 1) optimal pavement design involves complex mix optimization and there are theoretical and practical bases to set up a balanced approach to address the complexity of pavement design; 2) high percentages of crumb rubber could optimise road acoustic response but this latter has a relationship with the tyre/road noise (expressed, for example, in terms of close proximity index) that calls for further investigation; 3) aggregate gradation appears to be a reliable basis to predict surface texture and therefore, under given boundary conditions, tyre/road noise; and 4) further studies and investigations are needed in terms of local calibration of deterioration curves and setting up of a sound method to assess the frequency response of asphalt concretes and to govern on-site noise indicators based on mixture properties.

Mustafa Yildirim, Sajjad Mozaffari, Luc McCutcheon et al.

Autonomous driving decision-making is a challenging task due to the inherent complexity and uncertainty in traffic. For example, adjacent vehicles may change their lane or overtake at any time to pass a slow vehicle or to help traffic flow. Anticipating the intention of surrounding vehicles, estimating their future states and integrating them into the decision-making process of an automated vehicle can enhance the reliability of autonomous driving in complex driving scenarios. This paper proposes a Prediction-based Deep Reinforcement Learning (PDRL) decision-making model that considers the manoeuvre intentions of surrounding vehicles in the decision-making process for highway driving. The model is trained using real traffic data and tested in various traffic conditions through a simulation platform. The results show that the proposed PDRL model improves the decision-making performance compared to a Deep Reinforcement Learning (DRL) model by decreasing collision numbers, resulting in safer driving.

Łukasz Rawicki, Jacek Słania

Abstract: Non-destructive testing is a key element in ensuring the safe operation of the railway track. They allow for the detection of discontinuities arising both at the stage of production and operation. However, non-destructive testing has some limitations due to its nature. The vast majority of them are indirect methods in which the occurrence of discontinuities is inferred from the course of specific physical phenomena. Non-destructive testing methods provide information about the properties of the tested object. Their goals are to detect and estimation the nature of the discontinuities. The article presents some of the methods that can be used in the examination of railway rails, such as visual and ultrasonic tests. Attention was also paid to unconventional tests used in practice and allowing the detection of discontinuities, such as the method of the scatter field flux and the measurement of the alternating current field. Keywords: VT research; MFL method; MPM method; AFCM method; UT method, PA technique