Kaushlendra Pandey, Harpreet S. Dhillon, Abhishek K. Gupta
Vehicular platooning refers to coordinated and close movement of vehicular users (VUs) traveling together along a common route segment, offering strategic benefits such as reduced fuel costs, lower emissions, and improved traffic flow. {Highways offer a natural setting for platooning due to extended travel distances, yet their potential remains underexplored, particularly in terms of communication and connectivity. Given that effective platooning relies on robust vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) links, understanding connectivity dynamics on highways is essential.} In this paper, we analyze the dynamics of vehicular platooning on a highway and its impact on the performance of two forms of vehicular communications -- namely V2V and V2I communication -- compared to independent vehicle movement on a highway. The vehicular networks consists of road-side units (RSUs), modeled as a 1D Poisson point process (PPP), to provide the vehicular connectivity to the VUs. VUs are modeled as 1D PPP under the non-platooned traffic scenario (N-PTS) and as a 1D Matern cluster process (MCP) under the platooned traffic scenario (PTS). We evaluate the distribution on the per-RSU load, representing the number of VUs served, for the typical and tagged RSU. Additionally, we derive coverage probability (CP) and rate coverage (RC), which measures the probability of the signal-to-interference-plus-noise ratio (SINR) and achievable rate above a specified threshold at the typical VU along with their meta distribution (MD), providing a deeper understanding of the reliability and variability of these metrics across different spatial distributions of VUs and RSUs. Finally, we validate our theoretical findings through simulations and provide numerical insights into the impact of different traffic patterns on RSU load distribution, CP, and RC performance.
Introduction. Temperature effects on bridge superstructure are a constant factor influencing their performance. Due to low thermal conductivity of concrete, temperature gradients develop across cross-section of the structure, causing additional deformations and internal stresses. With global climate change and rising average annual temperatures, this issue has become especially important.
Problem statement. Underestimating temperature effects during bridge design and operation can lead to structural damage, reduced service life, and decreased reliability. Although European and American standards include models for temperature effects, Ukraine lacks comprehensive studies considering local climate conditions. A significant gap exists in experimental data, which complicates adapting or developing accurate design models.
Purpose. The main goal is to develop and validate a mathematical model for temperature distribution in concrete bridge superstructure over a daily cycle, specific to the Ukrainian climate. The model incorporates external climate parameters and material properties. It is validated by field measurements to improve accuracy in estimating temperature-induced stresses and enhancing structural reliability.
Materials and methods. The study analyzes the impact of climatic factors on the temperature of concrete bridge structure under Ukrainian climate conditions. Both analytical and numerical modeling were used. Experimental temperature measurements were taken on the span surface, combined with theoretical temperature modeling over a daily cycle using the finite element method. The stress-strain state of the span elements was also analyzed.
Introduction. The introduction to the paper highlights the advantages of usage and also the relevance of works on standardization for two on the hydraulic binder based materials namely roller-compacted concrete (RCC) and hydraulically bound mixtures (HBM).
Problem statement. The issue of the paper covers the comparison of RCC and HBM the technology of application of which during constructing of motor roads and objects of the transport logistic envisages the laying by the asphalt pavers and the compaction by the roller thus providing economic effect in comparison with the usage of conventional concretes.
Purpose. The goal of the paper is to perform the comparative analysis for RCC and HBM in particular for in the worldwide practice implemented standard methods for testing these materials to emphasize the major differences between RCC and HBM as the objects of standardization and for drafting main propositions regarding the direction of following works to provide wider implementation of RCC and HBM for construction of objects of transport infrastructure and logistic.
Results. The principles for standardization of RCC and HBM including meaningful differences in their compositions and specifications relating those materials’ project age were analyzed. It was stated that the assignment of RCC to standard concretes assures the resolution of QC tasks with ensuring a design class of material and also provides the abilities to use the specimens scale factors for standard procedures of strength determination and to perform the recalculation of values of strength measured by different methods.
The differentiation between standard methods for mixtures testing was performed and principled differences between compositions were emphasized according to which RCC should be classified by consistency as it was accepted for conventional concretes whereas HBMs in their plastic condition are characterized in general by values accepted for soils.
Also, the comparative analysis for standard methods of specimens manufacturing for RCC and HBM was performed and the main problems of implementations of that materials within the frame of the national Ukrainian standards system was stated.
Conclusions. The difference between compositions of RCC and HBM determines the implementation of different standard methods for testing RCC and HBMs in their plastic condition as methods accepted for two different road materials: concrete mixtures and soils.
Summary
Introduction. The development of transport infrastructure in Ukraine’s mountainous regions faces the problem of active landslide processes, which have a significant impact on the stability of road networks.
Problem statement. A significant proportion of roads in the Carpathians pass through areas of increased geological risk. Construction work on roads can disrupt the natural stability of slopes (through cutting or embankments), alter drainage systems and cause moisture to accumulate. At the same time, there is insufficient spatial analysis of the relative location of landslides and the road network, which complicates risk assessment.
Objective. The aim is to study the spatial location of landslides in relation to roads using GIS methods, to categorise landslides by their vertical position and to evaluate their impact on road infrastructure.
Materials and methods. Digital elevation model (DEM) data and vector layers of landslides and motorways were used for the Verkhovyna and Kosiv districts of the Ivano-Frankivsk region. A spatial analysis was performed in QGIS to determine the direction and nature of landslide hazards, calculating the minimum distance to the road and the difference in absolute heights between the landslide body and the road surface.
Results. A total of 467 landslides were analysed. Three groups were identified: Landslides below the road (202 cases): average distance to the road: 206.8 m. Landslides at road level (29 cases): average distance: 20.1 m. Landslides above the road (236 cases): average distance: 169.5 m; average height difference: 34.1 m. The most dangerous landslides are those above the road, as they can block transport routes. Landslides below the road can cause slope erosion and undercutting, reducing slope stability. Landslides at road level reflect deformations on old landslide bodies and can manifest as cracks or subsidence of the road surface.
Conclusions. A GIS analysis of landslides identified three groups based on their relative height. The most dangerous landslides are located above the road (50.5 %), while those below the road pose erosion risks and those at road level indicate unstable slopes. Systematic GIS monitoring is recommended for infrastructure management.
Introduction. The rapid development of logistics as a science leads to its expansion beyond the classical understanding of the movement of material resources from supplier to consumer. It encompasses a wide range of processes related to the management of flows on both global and local scales. In this context, the material flow serves as the central object of study, as it reflects the actual movement of resources in space and time under the influence of logistics operations and external factors. However, rapid changes in the economic environment, the emergence of new technologies, and the need to integrate the principles of sustainable development necessitate a revision of classical approaches and the construction of new models of material flow that meet the contemporary challenges of the economic environment.
Problem Statement. Classical models of material flow, which focus on the linear movement of resources from supplier to consumer, do not fully reflect modern economic realities. They fail to take into account the impact of reverse processes, the multiple life cycle of products, the variability of logistics systems over time, and the constant interaction between competing systems.
Purpose. The purpose of this study is to revise the concept of material flow and to construct a model that combines classical approaches with current economic trends, while considering the influence of sustainable development, technological progress, and competitive environments on the functioning of logistics systems.
Materials and Methods. The study employs a comparative analysis of different authors’ scientific approaches to defining the concepts of «material flow» and «logistics system.» The research methodology includes critical literature analysis, systematization of scientific viewpoints, as well as the development of schemes and models that reflect the evolution of the concept of material flow and its transformation under modern conditions.
Results. The study has shown that material flow should be considered as a dynamic, multidirectional, and theoretically infinite process. The proposed model incorporates reverse logistics, which ensures the return and disposal of resources, and also demonstrates that material flow can simultaneously operate within several logistics systems, branching out and merging depending on market conditions.
The IT industry provides supportive pathways such as returnship programs, coding boot camps, and buddy systems for women re-entering their job after a career break. Academia, however, offers limited opportunities to motivate women to return. We propose a diverse multicultural research project investigating the challenges faced by women with software engineering (SE) backgrounds re-entering academia or related research roles after a career break. Career disruptions due to pregnancy, immigration status, or lack of flexible work options can significantly impact women's career progress, creating barriers for returning as lecturers, professors, or senior researchers. Although many companies promote gender diversity policies, such measures are less prominent and often under-recognized within academic institutions. Our goal is to explore the specific challenges women encounter when re-entering academic roles compared to industry roles; to understand the institutional perspective, including a comparative analysis of existing policies and opportunities in different countries for women to return to the field; and finally, to provide recommendations that support transparent hiring practices. The research project will be carried out in multiple universities and in multiple countries to capture the diverse challenges and policies that vary by location.
Artem Bezuglyi, Serhii Illiash, Tetiana Stasiuk
et al.
ntroduction. The article provides an overview of international measurement systems for works and services on the example of Great Britain, the peculiarities of their application, the main advantages and disadvantages. Using the example of the Standard Method of Measurement in Civil Engineering (CESMM), the article discusses how such systems can contribute to accurate measurements, time and resource savings in road construction. The experience of applying CESMM4 on road facilities in Ukraine is also considered.
Problem statement. In construction in general, the use of international measurement systems is crucial for optimizing processes and improving the quality of project implementation. According to the requirements of the modern construction sector, the ability to generate bill of quantities (BoQ) according to international standards defines a new stage in the planning and implementation of construction projects.
Due to the rapid advancement of the transportation industry and the continual increase in pavement infrastructure, it is difficult to keep up with the huge road maintenance task by relying only on the traditional manual detection method. Intelligent pavement detection technology with deep learning techniques is available for the research and industry areas by the gradual development of computer vision technology. Due to the different characteristics of pavement distress and the uncertainty of the external environment, this kind of object detection technology for distress classification and location still faces great challenges. This paper discusses the development of object detection technology and analyzes classical convolutional neural network (CNN) architecture. In addition to the one-stage and two-stage object detection frameworks, object detection without anchor frames is introduced, which is divided according to whether the anchor box is used or not. This paper also introduces attention mechanisms based on convolutional neural networks and emphasizes the performance of these mechanisms to further enhance the accuracy of object recognition. Lightweight network architecture is introduced for mobile and industrial deployment. Since stereo cameras and sensors are rapidly developed, a detailed summary of three-dimensional object detection algorithms is also provided. While reviewing the history of the development of object detection, the scope of this review is not only limited to the area of pavement crack detection but also guidance for researchers in related fields is shared.
Highway engineering. Roads and pavements, Engineering (General). Civil engineering (General)
To comprehensively assess the current state-of-art in asphalt foaming technology, the following four key aspects have been reviewed systematically: foaming principles, test methods, evaluation indicators, and influencing factors. Key findings reveal that asphalt foaming was primarily driven by the vaporization of water, with deterioration processes including bubble collapse and liquid film drainage. However, the current understanding of asphalt foaming principles remains limited, primarily due to difficulties in capturing and precisely measuring its microscopic behaviors during asphalt foaming process. Volume changes provided an intuitive means to evaluate the expansion capacity of asphalt and its foaming stability. Bubble evolution characteristics of foamed asphalt offered promising insights into its foaming performance. Traditional ruler and stopwatch-based assessments were being superseded by automated techniques like laser and ultrasonic ranging. Nevertheless, the current measuring equipment still lacks the capability to comprehensively evaluate the foaming effect of asphalt across various dimensions. Asphalt temperature and foaming water consumption significantly affected asphalt foaming performance, and the inclusion of foaming agents typically led to a notable increase in the half life of foamed asphalt. However, the interaction between foaming agents and asphalt, as well as the underlying mechanisms affecting the foaming effect, are still unclear and require further exploration. Future research should primarily focus on the correlation between asphalt foaming effect and mixture performance, aiming to guide the practical engineering application of foamed asphalt mixtures and enlarge the advantages of such low-emission and sustainable mixtures.
Highway engineering. Roads and pavements, Engineering (General). Civil engineering (General)
Satya R. Jaladi, Zhimin Chen, Narahari R. Malayanur
et al.
The current autonomous stack is well modularized and consists of perception, decision making and control in a handcrafted framework. With the advances in artificial intelligence (AI) and computing resources, researchers have been pushing the development of end-to-end AI for autonomous driving, at least in problems of small searching space such as in highway scenarios, and more and more photorealistic simulation will be critical for efficient learning. In this research, we propose a novel game-based end-to-end learning and testing framework for autonomous vehicle highway driving, by learning from human driving skills. Firstly, we utilize the popular game Grand Theft Auto V (GTA V) to collect highway driving data with our proposed programmable labels. Then, an end-to-end architecture predicts the steering and throttle values that control the vehicle by the image of the game screen. The predicted control values are sent to the game via a virtual controller to keep the vehicle in lane and avoid collisions with other vehicles on the road. The proposed solution is validated in GTA V games, and the results demonstrate the effectiveness of this end-to-end gamification framework for learning human driving skills.
Pablo Alonso, Jon Ander Iñiguez de Gordoa, Juan Diego Ortega
et al.
Runway and taxiway pavements are exposed to high stress during their projected lifetime, which inevitably leads to a decrease in their condition over time. To make sure airport pavement condition ensure uninterrupted and resilient operations, it is of utmost importance to monitor their condition and conduct regular inspections. UAV-based inspection is recently gaining importance due to its wide range monitoring capabilities and reduced cost. In this work, we propose a vision-based approach to automatically identify pavement distress using images captured by UAVs. The proposed method is based on Deep Learning (DL) to segment defects in the image. The DL architecture leverages the low computational capacities of embedded systems in UAVs by using an optimised implementation of EfficientNet feature extraction and Feature Pyramid Network segmentation. To deal with the lack of annotated data for training we have developed a synthetic dataset generation methodology to extend available distress datasets. We demonstrate that the use of a mixed dataset composed of synthetic and real training images yields better results when testing the training models in real application scenarios.
The increase in population has made it possible for better, more cost-effective vehicular services, which warrants good roadways. The sub-base that serves as a stress-transmitting media and distributes vehicle weight to resist shear and radial deformation is a critical component of the pavement structures. Developing novel techniques that can assess the sub-base soil’s geotechnical characteristics and performance is an urgent need. Laterite soil abundantly available in the West Godavari area of India was employed for this research. Roads and highways construction takes a chunk of geotechnical investigation, particularly, California bearing ratio (CBR) of subgrade soils. Therefore, there is a need for intelligent tool to predict or analyze the CBR value without time-consuming and cumbersome laboratory tests. An integrated extreme learning machine-cooperation search optimizer (ELM-CSO) approach is used herein to predict the CBR values. The correlation coefficient is utilized as cost functions of the CSO to identify the optimal activation weights of the ELM. The statistical measures are separately considered, and best solutions are reported in this article. Comparisons are provided with the standard ELM to show the superiorities of the proposed integrated approach to predict the CBR values. Further, the impact of each input variable is studied separately, and reduced models are proposed with limited and inadequate input data without loss of prediction accuracy. When 70% training and 30% testing data are applied, the ELM-CSO outperforms the CSO with Pearson correlation coefficient (R), coefficient of determination (R2), and root mean square error (RMSE) values of 0.98, 0.97, and 0.84, respectively. Therefore, based on the prediction findings, the newly built ELM-CSO can be considered an alternative method for predicting real-time engineering issues, including the lateritic soil properties.
Street of Karanja Lembah is a provincial road linking Palu City and Sigi Regency. After a visual survey, the road has suffered a lot of damage, especially on its surface. The purpose of this study was to determine the pavement condition values based on the Pavement Condition Index (PCI) method and the Present Serviceability Index (PSI) method, as well as to determine the type of road handling based on the PCI and PSI values obtained on these roads. The PCI method is carried out directly by dividing the road into several segments called segment units, then recording the type of damage, the dimensions of the damage, and the severity of the damage for each type of damage. In research using the PSI method, the PSI value was calculated using IRI (International Roughness Index) data obtained from the Highways Service of Central Sulawesi Province. From the results of the analysis, it was obtained that the average PCI value for Jalan Karaja Lembah was 79.95% with a "very good" pavement condition, while the average PSI value for Jalan Karaja Lembah was 2.13% with a pavement condition "moderate". For the right type of handling for the PSI and PCI methods, namely the type of periodic maintenance.
Edi Yusuf Adiman, Benny Hamdi Rhoma Putra, Muhammad Rilly Aka Yogi
The advantage of using RAP (Reclaimed Asphalt Pavement) materials in road pavement has economic and environmental benefits. The RAP materials are used in the form of bitumen only, aggregates only, or both of them. This study proposes to determine the potential of RAP aggregate as a material for an SMA mixture. The variation of RAP aggregate in this study is based on function use, the nominal maximum aggregate size (NMAS), and minimum thickness of use from the results of the RAP aggregate test. The method in the manufacture and testing of specimens using the Marshall method. From the results of the testing and analysis of the RAP aggregate, the variations in RAP aggregate used in this study were 0%, 33%, and 47%. The results of the marshall test on the SMA mixture, the optimum bitumen content (OBC) of the RAP 0% was 6.23%, and the RAP 33% was 6.1%, while the RAP 47% OBC could not be determined because it did not fulfill standard requirements of the Marshall based on the value of VMA and VITM. From these results, the potential use of RAP aggregate for SMA mixtures is 33%. This value is the percentage of the RAP aggregate potential in the SMA mixture that fulfills the standard requirements of the Marshall and testing aggregate.
Highway engineering. Roads and pavements, Engineering (General). Civil engineering (General)
Damtew Melese, Belete Aymelo, Tewodros Weldesenbet
et al.
Black cotton soil is highly susceptible to volume change due to moisture fluctuations. This leads to the deformation of structures built on such soil. Therefore, the aim of this study is to improve the soil-bearing capacity and deformation analysis of black cotton soil. The laboratory tests were done according to the American Association State of highway and Transport Official (AASHTO) and the American Society for Testing and Materials (ASTM). These tests were natural moisture content, grain size distribution, X-ray diffraction test, Atterberg limit test, modified compaction, California bearing ratio, and triaxial test. Soil sample was stabilized with a ratio of 0%, 4%, 8%, 12%, and 16% of brick dust and 0%, 1%, 3%, 5%, and 7% of lime, respectively. The result of the laboratory test at the optimum percentage of 12% brick dust and 5% lime shows that the liquid limit improved from 93.2% to 67.5%, plastic limit improved from 48.71%, to 58.2%. The optimum moisture content improved from 26.76 to18.5% and Maximum dry density improved from 1.42 g/cm3 to 1.58 g/cm3. The California bearing ratio improved from 1.29%, to 13.6%. The deformation analysis result shows that at optimum percentage of stabilizing agent, the deformation reduced from 2.087 mm to 0.973 mm. Therefore, brick dust-lime soil stabilization shows the promising improvement of weak subgrade soil.
Highway engineering. Roads and pavements, Bridge engineering
Software engineering capabilities are increasingly important to the success of economic and political blocs. This paper analyzes quantity and quality of software engineering research output originating from the US, Europe, and China over time. The results indicate that the quantity of research is increasing across the board with Europe leading the field. Depending of the scope of the analysis, either the US or China come in second. Regarding research quality, Europe appears to be lagging the other blocs, with China having caught up to and even having overtaken the US over time.
Fluorescent molecules are versatile nanoscale emitters that enable detailed observations of biophysical processes with nanoscale resolution. Because they are well-approximated as electric dipoles, imaging systems can be designed to visualize their 3D positions and 3D orientations, so-called dipole-spread function (DSF) engineering, for 6D super-resolution single-molecule orientation-localization microscopy (SMOLM). We review fundamental image-formation theory for fluorescent di-poles, as well as how phase and polarization modulation can be used to change the image of a dipole emitter produced by a microscope, called its DSF. We describe several methods for designing these modulations for optimum performance, as well as compare recently developed techniques, including the double-helix, tetrapod, crescent, and DeepSTORM3D learned point-spread functions (PSFs), in addition to the tri-spot, vortex, pixOL, raPol, CHIDO, and MVR DSFs. We also cover common imaging system designs and techniques for implementing engineered DSFs. Finally, we discuss recent biological applications of 6D SMOLM and future challenges for pushing the capabilities and utility of the technology.