Hasil untuk "Highway engineering. Roads and pavements"

Tanmay Vilas Samak, Chinmay Vilas Samak, Julia Brault et al.

The engineering community currently encounters significant challenges in the systematic development and validation of autonomy algorithms for off-road ground vehicles. These challenges are posed by unusually high test parameters and algorithmic variants. In order to address these pain points, this work presents an optimized digital engineering framework that tightly couples digital twin simulations with model-based systems engineering (MBSE) and model-based design (MBD) workflows. The efficacy of the proposed framework is demonstrated through an end-to-end case study of an autonomous light tactical vehicle (LTV) performing visual servoing to drive along a dirt road and reacting to any obstacles or environmental changes. The presented methodology allows for traceable requirements engineering, efficient variant management, granular parameter sweep setup, systematic test-case definition, and automated execution of the simulations. The candidate off-road autonomy algorithm is evaluated for satisfying requirements against a battery of 128 test cases, which is procedurally generated based on the test parameters (times of the day and weather conditions) and algorithmic variants (perception, planning, and control sub-systems). Finally, the test results and key performance indicators are logged, and the test report is generated automatically. This then allows for manual as well as automated data analysis with traceability and tractability across the digital thread.

Kaustav Chatterjee, Joshua Q. Li, Fatemeh Ansari et al.

Hump crossings, or high-profile Highway Railway Grade Crossings (HRGCs), pose safety risks to highway vehicles due to potential hang-ups. These crossings typically result from post-construction railway track maintenance activities or non-compliance with design guidelines for HRGC vertical alignments. Conventional methods for measuring HRGC profiles are costly, time-consuming, traffic-disruptive, and present safety challenges. To address these issues, this research employed advanced, cost-effective techniques and innovative modeling approaches for HRGC profile measurement. A novel hybrid deep learning framework combining Long Short-Term Memory (LSTM) and Transformer architectures was developed by utilizing instrumentation and ground truth data. Instrumentation data were gathered using a highway testing vehicle equipped with Inertial Measurement Unit (IMU) and Global Positioning System (GPS) sensors, while ground truth data were obtained via an industrial-standard walking profiler. Field data was collected at the Red Rock Railroad Corridor in Oklahoma. Three advanced deep learning models Transformer-LSTM sequential (model 1), LSTM-Transformer sequential (model 2), and LSTM-Transformer parallel (model 3) were evaluated to identify the most efficient architecture. Models 2 and 3 outperformed the others and were deployed to generate 2D/3D HRGC profiles. The deep learning models demonstrated significant potential to enhance highway and railroad safety by enabling rapid and accurate assessment of HRGC hang-up susceptibility.

Sharon Guardado, Risha Parveen, Zheying Zhang et al.

The integration of Large Language Models (LLMs) in Requirements Engineering (RE) education is reshaping pedagogical approaches, seeking to enhance student engagement and motivation while providing practical tools to support their professional future. This study empirically evaluates the impact of integrating LLMs in RE coursework. We examined how the guided use of LLMs influenced students' learning experiences, and what benefits and challenges they perceived in using LLMs in RE practices. The study collected survey data from 179 students across two RE courses in two universities. LLMs were integrated into coursework through different instructional formats, i.e., individual assignments versus a team-based Agile project. Our findings indicate that LLMs improved students' comprehension of RE concepts, particularly in tasks like requirements elicitation and documentation. However, students raised concerns about LLMs in education, including academic integrity, overreliance on AI, and challenges in integrating AI-generated content into assignments. Students who worked on individual assignments perceived that they benefited more than those who worked on team-based assignments, highlighting the importance of contextual AI integration. This study offers recommendations for the effective integration of LLMs in RE education. It proposes future research directions for balancing AI-assisted learning with critical thinking and collaborative practices in RE courses.

Iryna Kinash, Maria Berlous

Introduction. Managerial education plays a crucial role in today’s dynamic world. It is influenced by the Fourth Industrial Revolution, economic integration, demographics, information and communication technologies, the global search for goods and services, social responsibility, governance, and sustainability. Problem Statement. The culture, traditions, and unique features of educational systems are the heritage of every country. The primary task is to preserve them while also stimulating their development. At the same time, open labor markets and the right of citizens to free movement (particularly within the European Union) create the basis for defining and forming the knowledge, skills, and abilities of managers that would be universal for all countries. Therefore, studying the foreign experience of professional manager training in various countries determined the relevance of this research. Purpose. The purpose of the article is to study the features of professional manager training in leading countries of the world. Materials and Methods. Various research methods were used to achieve this goal, including historical, synthesis, comparison, and generalization. Additionally, statistical methods were applied to analyze trends in professional manager training, and a tabular method was used for the visual representation of the results. Results. It was found that the structure of global higher education for professional manager training is diverse, but two trends dominate: a single system where professional managers are trained by universities or equivalent institutions (Italy, Spain, Austria, Finland, Sweden); and a dual system with both a traditional university and a non-university sector (USA, Belgium, Great Britain, Denmark, Ireland, Netherlands, Norway, Germany, France, Switzerland). MBA programs are considered prestigious for manager training. An analysis of the trends in professional manager training at the bachelor’s, master’s, and PhD levels was conducted. Conclusions. The reviewed foreign experience of professional manager training in leading countries, which considers historical chronology, formalizes the stages of this process’s development, and generalizes and compares educational systems, indicates a process of transformation.

Lyudmyla Shevchuk, Nataliia Shlyun, Serhii Hudolìj et al.

Introduction. In regions with sharp temperature fluctuations during their seasonal and daily changes, the phenomenon of local defects and cracks forming in the asphalt concrete pavements of roads and bridges is very often observed. This is largely due to the heterogeneity of the thermomechanical properties of the materials in the pavement layers and base. To prevent these phenomena, reinforcing rods and grids are introduced into the pavement structure. Problems. The problem addressed in the conducted research is to establish the patterns of thermomechanical deformation of composite materials (specifically, asphalt concrete) reinforced with steel rods under the influence of variable temperature fields. Purpose. The objective of this work is to derive mathematical relationships that define the internal structural thermal stresses in composites, caused by variable temperature fields and material heterogeneity. Materials and methods. Based on the theory of thermoelasticity, the problem of a plane thermodeformed state of an elastic medium containing a circular elastic rod with different thermomechanical parameters was formulated. For the case of a constant change in the system’s temperature, an analytical solution to the equations was constructed, and expressions for thermal deformations and thermal stresses were obtained. The results. Using the example of asphalt concrete material reinforced with fiberglass rods, analytical expressions for the values of additional contact thermal stresses were constructed, and the conditions for the thermomechanical incompatibility of asphalt concrete and reinforcement materials were formulated. Conclusions. Using the methods of thermoelasticity theory, it was shown that in cases of incompatibility of the thermomechanical characteristics of asphalt concrete and reinforcement materials, additional localized thermal stresses arise in their immediate vicinity. These stresses, even at moderate temperature changes, can reach critical values and lead to local defects and cracks. Since these defects are hidden, they cannot always be detected in practice.

Jiale Li, Jiayin Guo, Bo Li et al.

The deep learning method has been widely used in the engineering field. The availability of the training dataset is one of the most important limitations of the deep learning method. Accurate prediction of pavement performance plays a vital role in road preventive maintenance (PM) and decision-making. Pavement performance prediction based on deep learning has been widely used around the world for its accuracy, robustness, and automation. However, most of the countries in the world have not built their pavement performance historical database, which prevents preventive maintenance using the deep learning method. This study presents an innovative particle swarm optimization (PSO) algorithm-enhanced two-stage TrAdaBoost.R2 transfer learning algorithm, which could significantly increase the pavement performance prediction database. The Long-Term Pavement Performance (LTPP) database is used as the source domain data, and one of the highways in China is chosen as the target domain to predict pavement performance. The results show that the proposed PSO-Two-stage TrAdaBoost.R2 model has the highest accuracy compared with AdaBoost.R2 model and traditional regression decision tree model. The validation case study shows significant consistency between the predicted International Roughness Index (IRI) and the whole-year measurement data with an R2 of 0.7. This study demonstrates the great potential of the innovative instance-based transfer learning method in pavement performance prediction of a region’s lack of data. This study also contributes to other engineering fields that could greatly increase the universality of deep learning.

Larry Schester, Luis E. Ortiz

Vehicles today can drive themselves on highways and driverless robotaxis operate in major cities, with more sophisticated levels of autonomous driving expected to be available and become more common in the future. Yet, technically speaking, so-called "Level 5" (L5) operation, corresponding to full autonomy, has not been achieved. For that to happen, functions such as fully autonomous highway ramp entry must be available, and provide provably safe, and reliably robust behavior to enable full autonomy. We present a systematic study of a highway ramp function that controls the vehicles forward-moving actions to minimize collisions with the stream of highway traffic into which a merging (ego) vehicle enters. We take a game-theoretic multi-agent (MA) approach to this problem and study the use of controllers based on deep reinforcement learning (DRL). The virtual environment of the MA DRL uses self-play with simulated data where merging vehicles safely learn to control longitudinal position during a taper-type merge. The work presented in this paper extends existing work by studying the interaction of more than two vehicles (agents) and does so by systematically expanding the road scene with additional traffic and ego vehicles. While previous work on the two-vehicle setting established that collision-free controllers are theoretically impossible in fully decentralized, non-coordinated environments, we empirically show that controllers learned using our approach are nearly ideal when measured against idealized optimal controllers.

Horia Mărgărit, Amanda Bowman, Krishnageetha Karuppasamy et al.

In this work, we present a case study in implementing a variational quantum algorithm for solving the Poisson equation, which is a commonly encountered partial differential equation in science and engineering. We highlight the practical challenges encountered in mapping the algorithm to physical hardware, and the software engineering considerations needed to achieve realistic results on today's non-fault-tolerant systems.

Mohamed Younis, Sookyoung Lee, Wassila Lalouani et al.

Traffic management and on-road safety have been a concern for the transportation authorities and the engineering communities for many years. Most of the implemented technologies for intelligent highways focus on safety measures and increased driver awareness, and expect a centralized management for the vehicular traffic flow. Leveraging recent advances in wireless communication, researchers have proposed solutions based on vehicle-to-vehicle (V2V) and vehicle-to-Infrastructure (V2I) communication in order to detect traffic jams and better disseminate data from on-road and on-vehicle sensors. Moreover, the development of connected autonomous vehicles (CAV) have motivated a paradigm shift in how traffic will be managed. Overall, these major technological advances have motivated the notion of dynamic traffic management (DTM), where smart road reconfiguration capabilities, e.g., dynamic lane reversal, adaptive traffic light timing, etc. will be exploited in real-time to improve traffic flow and adapt to unexpected incidents. This chapter discusses what the challenges in realizing DTM are and covers how CAV has revolutionized traffic management. Moreover, we highlight the issues for handling human-driven vehicles while roads are transitioning to CAV only traffic. Particularly, we articulate a new vision for inter-vehicle communication and assessment of road conditions, and promote a novel system for traffic management. Vehicle to on-road sensors as well as inter-vehicle connectivity will be enabled through the use of handheld devices such as smartphones. This not only enables real-time data sharing but also expedites the adoption of DTM without awaiting the dominant presence of autonomous vehicle on the road. ...

Anatolii Mudrychenko, Serhii Illiash, Valentin Goncharenko et al.

Introduction. The article investigates the effect of the preparation temperature, the amount of energy-saving additive and the amount of asphalt crumb on the physical and mechanical properties of warm asphalt mixtures. The method of experimental and statistical modeling was used in the study, and mathematical models describing the dependence of water saturation and compressive strength of asphalt concrete were developed. Based on the analysis of the results obtained, the areas of optimal values of the preparation temperature, the amount of energy-saving additive, and the amount of asphalt crumb during the production of warm asphalt mixtures were determined. In this case, the resulting mixture meets the standard requirements for hot fine-grained asphalt mixtures in terms of physical and mechanical properties. Problem statement. Studies by the authors of [1] have shown that when preparing an asphalt mixture, it is very important to take into account changes in the properties of bitumen, which is the main component that characterizes the behavior of asphalt concrete. In the preparation of warm asphalt mixtures, it is advisable to use energy-saving additives, the introduction of which provides relatively new chemical effects that improve the workability, mobility and energy saving of mixtures made at lower temperatures than traditional hot mixtures.

Junxian Chen, Yonggang Wang

Sharp curves are vulnerable sections for rollover accidents. This study was conducted to investigate the effects of transition curve and superelevation on the critical speed and critical braking distance of truck rollovers. Using different transition types (spiral, Bloss and Grabowski curve) and different superelevation values (6%, 120 m transition length and 8%, 160 m) as variables, experiments of constant speed driving and hard braking were simulated and conducted by Trucksim. Conclusions regarding the influence of these road design factors on the stability of vehicles were then proposed. Grabowski curve allowed for the maximum critical rollover speed. The difference in critical rollover speed between different transition types was only determined by the length of the transition section. Simply extending the length of the transition section increased the critical rollover speed of spiral curve, at the same time decreasing the critical speed of Bloss and Grabowski curve. Hard braking experiments showed completely different characteristics. As the initial speed increased, only spiral curve became safer. Increasing superelevation made the braking behaviour of the vehicle more dangerous and fraught with uncertainties due to different target speed, starting curvature and changing superelevation. Based on these findings, a number of useful recommendations for drivers and road designers were put forward.

Junqing Li, Linbing Wang, Y. Miao et al.

Dongwei Xiao, Zhibo Liu, Shuai Wang

A physical simulation engine (PSE) is a software system that simulates physical environments and objects. Modern PSEs feature both forward and backward simulations, where the forward phase predicts the behavior of a simulated system, and the backward phase provides gradients (guidance) for learning-based control tasks, such as a robot arm learning to fetch items. This way, modern PSEs show promising support for learning-based control methods. To date, PSEs have been largely used in various high-profitable, commercial applications, such as games, movies, virtual reality (VR), and robotics. Despite the prosperous development and usage of PSEs by academia and industrial manufacturers such as Google and NVIDIA, PSEs may produce incorrect simulations, which may lead to negative results, from poor user experience in entertainment to accidents in robotics-involved manufacturing and surgical operations. This paper introduces PHYFU, a fuzzing framework designed specifically for PSEs to uncover errors in both forward and backward simulation phases. PHYFU mutates initial states and asserts if the PSE under test behaves consistently with respect to basic Physics Laws (PLs). We further use feedback-driven test input scheduling to guide and accelerate the search for errors. Our study of four PSEs covers mainstream industrial vendors (Google and NVIDIA) as well as academic products. We successfully uncover over 5K error-triggering inputs that generate incorrect simulation results spanning across the whole software stack of PSEs.

Orhan Kaya, Hatice Merve Annagur, Olcay Altintas

This study experimentally investigates the usability of asphalt concrete pavement containing five different ratios of graphite powder (0%, 1.25%, 2.5%, 3.75% and 5% by weight of the aggregate blend or 0%, 25%, 50%, 75% and 100% of the filler content) as a filler to be potentially used as part of wireless electric roads (ER). As part of the study, first, optimum asphalt binder content for the asphalt mixes without graphite powder was determined as 5%. Then, using the determined optimum asphalt binder content, asphalt mixes containing five different ratios of graphite powder as a filler were prepared and their mechanical and volumetric properties based on Marshall mix design methodology were evaluated. As graphite powder ratios in the asphalt mixes increased, their Marshall stability, flow, voids filled with asphalt and unit weight test results mostly decreased but their air content and voids in mineral aggregate test results increased. Possible reasons for this could be: (1) lower bulk specific gravity of graphite powder, (2) higher asphalt absorbance, (3) having greater surface area compared to that of limestone filler, and (4) weak bonds between sheet-like graphite layers. Furthermore, another batch of asphalt mixes containing five different ratios of graphite powder were prepared and tested in the frequency range of 3–18 GHz for their electromagnetic permittivity properties. It was observed in this study that, except for the specimens with 100% graphite powder ratios, transmission magnitudes of all specimens were above 50% up to 8 GHz, indicating that they had comparably high transmission magnitudes so as comparably low tangent loss values. In the frequency range of 3–13 GHz, transmission magnitudes of the specimens with 25% and 50% graphite powder ratios were consistently higher than that having no graphite powder, the ones with 25% powder ratios had the highest transmission magnitudes in most of the cases in this frequency range. Considering the mechanical, volumetric and electromagnetic property test results of the asphalt mixes with five different ratios of graphite powder, it can be concluded that the use of 25% graphite powder ratio (corresponding to 1.25% of the aggregate blend used in the mixes), has a comparably lower negative effect on mechanical and volumetric properties of asphalt mixes and has a positive effect on electromagnetic permittivity properties of asphalt mixes. Asphalt mixes produced with this graphite powder ratio can be considered to be used as part of wireless ER.

Tetyana Tereshchenko

Introduction. The introduction to the paper highlights the importance of the design and construction of highways of various link functions levels as a key factor in modern integration processes and also emphasizes the role of highways for substantial increasing of the road network safety. Problem statement. The issues of the paper concern aspects of highways design based on the experience of European colleagues in the context of the provisions of the relevant legislative acts of EU. Purpose. The goal of the paper is to analyze the main provisions for the design of continental, subcontinental and transregional highways considering, within the format of the publication, the design features of the highways elements which are universal for various design systems. Results. The highways categorization regarding their link functions levels and with this categorization linked classification by design classes were reviewed which accept the highways jurisdiction and the build-up areas related location and also the corresponding restrictions on vehicle speed limits. The highways characteristics were defined allowing the determination of highways as a separate category of motor roads in the world-wide practice of the road building industry.

Yiqiu Tan, Jilu Li, Huining Xu et al.

The anti-skid performance of snowy and icy pavements is a popular research topic among road workers. Snow and ice are pollutants on a road surface. They significantly reduce the skid resistance of pavements, and thus, cause traffic accidents. Pertinent research progress on the skid resistance of snowy and icy pavements was reviewed and summarized in this work. The formation and classification of snowy and icy pavements were described on the basis of the state of snow and ice. The friction mechanisms between tires and snowy and icy pavements were revealed. Measurement methods and their applicability to the skid resistance of snowy and icy pavements were summarized. Factors that affect the skid resistance of pavements were discussed from the perspectives of pavement, environment, and vehicle. In addition, models of snowy and icy pavement resistance were classified into experience, mechanical, and numerical models. The advantages and disadvantages of these models were then compared and analyzed. Some suggestions regarding snowy and icy pavements were presented in accordance with the aforementioned information, including the development of efficient testing tools, the quantification of skid resistance under the coupling effects of multiple factors, the establishment of unified evaluation standards, and the development of more effective skid resistance models.

S. I. Haruna, Han Zhu, Y. Ibrahim et al.

The prolonged service life of civil engineering structures, such as buildings and highway pavement, means that they deteriorate with time, requiring frequent repair work. Polyurethane (PU) materials can effectively maintain engineering structures such as road pavement, runways, and buildings. Thus, the mechanical properties and dynamic performance of these materials for repair are essential to guarantee the safe usage of the facilities. This study investigated the strain–stress behavior and impact strength of polyurethane-based polymer concrete (PUPC) mixtures. Moreover, the tensile stress–strain behavior of rigid PU grout (PUGC) materials was evaluated. The result indicated that the U-shaped PUPC with 20% PU by weight experienced a maximum failure strain of 0.9% and 4.2% under static and dynamic loads, respectively. The average impact energy of PUPC was 3825% higher than that of normal concrete. According to PUGC’s mixing ratios, the average elastic modulus revealed an increasing trend, whereas ultimate strength, yield strain, yield stress, and failure stress showed a decreasing trend. Weibull distribution results showed that the probabilistic distribution of the impact strength followed the two-parameter Weibull distribution.

T. Harianto

Some laterite soil is an inferior material for engineering applications such as road and highway pavement, dam construction and filling material. Laterite soil stabilization is required to increase its strength for field application purposes. The potential use of zeolite and waterglass as stabilizing agents is their pozzolanic properties. This study aims to analyze the strength and bearing capacity of laterite soil stabilized by waterglass-activated zeolite and reinforced with geogrid. The soil sample was prepared with a zeolite percentage of 4, 8, 12, 16 and 20%, and waterglass as much as 2, 4 and 6% with curing times of 0, 7, 14 and 28 days. Furthermore, the physical model test was carried out in the container with the optimum composition obtained from the compressive strength (UCS) and California bearing test (CBR) test. The stabilized subbase layer with geogrid reinforcement was placed on a subgrade layer with a substandard CBR value. The results showed that the compressive strength (UCS) of stabilized soil with a curing time of 7 days was found significantly increased. The CBR value also increased with the content of additive and curing time compared to the untreated soil. The physical model test results showed that the performance of stabilized laterite soil with additives and reinforced by geogrid (ZW-geogrid) as a subbase layer provides more optimal performance in carrying the load compared to the sand-gravel mixtures material. Doi: 10.28991/CEJ-2022-08-02-05 Full Text: PDF

Tao Chen, Miqing Li

In presence of multiple objectives to be optimized in Search-Based Software Engineering (SBSE), Pareto search has been commonly adopted. It searches for a good approximation of the problem's Pareto optimal solutions, from which the stakeholders choose the most preferred solution according to their preferences. However, when clear preferences of the stakeholders (e.g., a set of weights which reflect relative importance between objectives) are available prior to the search, weighted search is believed to be the first choice since it simplifies the search via converting the original multi-objective problem into a single-objective one and enable the search to focus on what only the stakeholders are interested in. This paper questions such a "weighted search first" belief. We show that the weights can, in fact, be harmful to the search process even in the presence of clear preferences. Specifically, we conduct a large scale empirical study which consists of 38 systems/projects from three representative SBSE problems, together with two types of search budget and nine sets of weights, leading to 604 cases of comparisons. Our key finding is that weighted search reaches a certain level of solution quality by consuming relatively less resources at the early stage of the search; however, Pareto search is at the majority of the time (up to 77% of the cases) significantly better than its weighted counterpart, as long as we allow a sufficient, but not unrealistic search budget. This, together with other findings and actionable suggestions in the paper, allows us to codify pragmatic and comprehensive guidance on choosing weighted and Pareto search for SBSE under the circumstance that clear preferences are available. All code and data can be accessed at: https://github.com/ideas-labo/pareto-vs-weight-for-sbse.

Zheng Li, Rajiv Ranjan

By seamlessly integrating everyday objects and by changing the way we interact with our surroundings, Internet of Things (IoT) is drastically improving the life quality of households and enhancing the productivity of businesses. Given the unique IoT characteristics, IoT applications have emerged distinctively from the mainstream application types. Inspired by the outlook of a programmable world, we further foresee an IoT-native trend in designing, developing, deploying, and maintaining software systems. However, although the challenges of IoT software projects are frequently discussed, addressing those challenges are still in the "crossing the chasm" period. By participating in a few various IoT projects, we gradually distilled three fundamental principles for engineering IoT-native software systems, such as just enough, just in time, and just for "me". These principles target the challenges that are associated with the most typical features of IoT environments, ranging from resource limits to technology heterogeneity of IoT devices. We expect this research to trigger dedicated efforts, techniques and theories for the topic IoT-native software engineering.