Hasil untuk "Highway engineering. Roads and pavements"

Nerijus Bareikis, Algirdas Juozapaitis, Ilze Paeglīte

Corrugated soil-steel composite bridges due to their out-of-plane stiffness and interaction with surrounding soil are extensively used in the underground engineering. The demand for larger span of corrugated soil-steel structures is rising due to their high strength-to-cost ratio. Larger spans are usually related to the bigger cross-sections of corrugation profile. The use of the deepest corrugations like 500 mm pitch and 237 mm depth is associated with a higher risk of local buckling of straight region (tangent mt) of corrugation. This study analyses the resistance to local buckling of four widely used corrugation profiles. It also examines the impact of circular hollow section steel pipes and high strength steel influence on plate width-to-thickness ratio limit. The numerical three-dimensional model was developed for the investigation. At first, parametric study was conducted to reveal the influence mechanisms on critical parameters, incorporating finite element mesh size, number of corrugations, plate height, and plate thickness. Afterwards, local buckling behaviour of corrugated steel plate was studied and width-to-thickness ratio limit was proposed considering that local buckling of the plate would not occur before steel yielding. It was found that corrugated plate thickness could be significantly reduced as a result of the reduction of buckling length by steel pipes. Therefore, innovative corrugation profile has the great potential to be rational more than the increase of the thickness of the regular corrugated steel plate.

Marcin Switala, Maciej Maliszewski

This study examines the challenges and potential solutions associated with the retention of stormwater from road surfaces – a critical component of urban infrastructure in the face of climate change. The research highlights that intensified urbanisation and the increasing prevalence of extreme weather events have exacerbated issues related to rapid rainwater runoff, leading to urban flooding and infrastructural degradation. Employing quantitative empirical methods, a survey was conducted among 362 road infrastructure managers in Poland, assessing the technical condition of roads, drainage system performance, and the barriers to adopting modern retention and infiltration solutions. Findings reveal a mixed perception of current drainage performance, with many respondents reporting inadequate solutions that compromise both safety and sustainability. Key barriers include high implementation costs, technical and infrastructural challenges, resistance to change, and limited public awareness. The results underscore the necessity for modern, integrated stormwater management practices that not only protect infrastructure but also enhance urban water balance and sustainability.

Chao Zhang, Neha Arora, Christopher Bian et al.

Estimating Origin-Destination (OD) travel demand is vital for effective urban planning and traffic management. Developing universally applicable OD estimation methodologies is significantly challenged by the pervasive scarcity of high-fidelity traffic data and the difficulty in obtaining city-specific prior OD estimates (or seed ODs), which are often prerequisite for traditional approaches. Our proposed method directly estimates OD travel demand by systematically leveraging aggregated, anonymized statistics from Google Maps Traffic Trends, obviating the need for conventional census or city-provided OD data. The OD demand is estimated by formulating a single-level, one-dimensional, continuous nonlinear optimization problem with nonlinear equality and bound constraints to replicate highway path travel times. The method achieves efficiency and scalability by employing a differentiable analytical macroscopic network model. This model by design is computationally lightweight, distinguished by its parsimonious parameterization that requires minimal calibration effort and its capacity for instantaneous evaluation. These attributes ensure the method's broad applicability and practical utility across diverse cities globally. Using segment sensor counts from Los Angeles and San Diego highway networks, we validate our proposed approach, demonstrating a two-thirds to three-quarters improvement in the fit to segment count data over a baseline. Beyond validation, we establish the method's scalability and robust performance in replicating path travel times across diverse highway networks, including Seattle, Orlando, Denver, Philadelphia, and Boston. In these expanded evaluations, our method not only aligns with simulation-based benchmarks but also achieves an average 13% improvement in it's ability to fit travel time data compared to the baseline during afternoon peak hours.

Bertrand Meyer

Software engineering concepts and processes are worthy of formal study; and yet we seldom formalize them. This "research ideas" article explores what a theory of software engineering could and should look like. Software engineering research has developed formal techniques of specification and verification as an application of mathematics to specify and verify systems addressing needs of various application domains. These domains usually do not include the domain of software engineering itself. It is, however, a rich domain with many processes and properties that cry for formalization and potential verification. This article outlines the structure of a possible theory of software engineering in the form of an object-oriented model, isolating abstractions corresponding to fundamental software concepts of project, milestone, code module, test and other staples of our field, and their mutual relationships. While the presentation is only a sketch of the full theory, it provides a set of guidelines for how a comprehensive and practical Theory of Software Engineering should (through an open-source community effort) be developed.

Xiaowen Tao, Yinuo Wang, Jinzhao Zhou

End-to-end reinforcement learning (RL) for motion control trains policies directly from sensor inputs to motor commands, enabling unified controllers for different robots and tasks. However, most existing methods are either blind (proprioception-only) or rely on fusion backbones with unfavorable compute-memory trade-offs. Recurrent controllers struggle with long-horizon credit assignment, and Transformer-based fusion incurs quadratic cost in token length, limiting temporal and spatial context. We present a vision-driven cross-modal RL framework built on SSD-Mamba2, a selective state-space backbone that applies state-space duality (SSD) to enable both recurrent and convolutional scanning with hardware-aware streaming and near-linear scaling. Proprioceptive states and exteroceptive observations (e.g., depth tokens) are encoded into compact tokens and fused by stacked SSD-Mamba2 layers. The selective state-space updates retain long-range dependencies with markedly lower latency and memory use than quadratic self-attention, enabling longer look-ahead, higher token resolution, and stable training under limited compute. Policies are trained end-to-end under curricula that randomize terrain and appearance and progressively increase scene complexity. A compact, state-centric reward balances task progress, energy efficiency, and safety. Across diverse motion-control scenarios, our approach consistently surpasses strong state-of-the-art baselines in return, safety (collisions and falls), and sample efficiency, while converging faster at the same compute budget. These results suggest that SSD-Mamba2 provides a practical fusion backbone for resource-constrained robotic and autonomous systems in engineering informatics applications.

Zhouyu Qu, Andreas Willig, Xiaobing Wu

Unmanned Aerial Vehicles (UAVs), commonly known as drones, have experienced expanding use in urban environments in recent years. However, the growing density of drones raises significant challenges, such as avoiding collisions and managing air traffic efficiently, especially in congested areas. To address these issues, a structured road system and an effective guidance algorithm are essential. In this paper, we introduce a markup language allowing to describe drone road systems (DRS), in which a road system is given by a set of individual roads, each of which can have a varying number of lanes. Roads can be linked through connecting lanes. Furthermore, we propose a novel short-term decentralized greedy (STDG) guidance algorithm that uses only the position and speed information of nearby drones -- communicated via periodically transmitted beacons -- to make real-time decisions such as stopping, changing lanes, or adjusting speed for the next few seconds. Unlike existing methods that rely on centralized coordination, our algorithm enables drones to operate independently while ensuring safety and efficiency. We present simulation results showing the impact of key wireless and algorithm parameters on performance metrics like the drone collision rate, average speed and throughput of the drone road system.

Alexandros Gazis, Ioannis Papadongonas, Athanasios Andriopoulos et al.

This article provides a comprehensive overview of sensors commonly used in low-cost, low-power systems, focusing on key concepts such as Internet of Things (IoT), Big Data, and smart sensor technologies. It outlines the evolving roles of sensors, emphasizing their characteristics, technological advancements, and the transition toward "smart sensors" with integrated processing capabilities. The article also explores the growing importance of mini-computing devices in educational environments. These devices provide cost-effective and energy-efficient solutions for system monitoring, prototype validation, and real-world application development. By interfacing with wireless sensor networks and IoT systems, mini-computers enable students and researchers to design, test, and deploy sensor-based systems with minimal resource requirements. Furthermore, this article examines the most widely used sensors, detailing their properties and modes of operation to help readers understand how sensor systems function. The aim of this study is to provide an overview of the most suitable sensors for various applications by explaining their uses and operations in simple terms. This clarity will assist researchers in selecting the appropriate sensors for educational and research purposes or understanding why specific sensors were chosen, along with their capabilities and possible limitations. Ultimately, this research seeks to equip future engineers with the knowledge and tools needed to integrate cutting-edge sensor networks, IoT, and Big Data technologies into scalable, real-world solutions.

Nikolaos Kalyviotis

Road infrastructure significantly impacts how people move and live and the emissions associated with travel behaviour. The design of roads is crucial in mitigating emissions. This paper reviews existing transport life cycle assessment tools that have been developed by various entities and can be used for roads. The review focuses on data sources used in the analysis, methods of estimating carbon dioxide emissions, the underlying software that is used to make the estimates, and any limitations of the tools. A critical issue identified in life cycle assessment analysis is the erroneous assumption that relationships within the assessed systems are linear. The current tools focusing on transport infrastructure assessment were developed based on the linear assumptions and limitations of the life cycle assessment analysis. A significant research gap identified is that existing life cycle assessment tools are not integrated with the design process. The analysis is an add-on process to design and the results of an assessment are not then used iteratively to enhance the design. A case study on aggregate road design found that road area significantly correlates with emissions, slope adjustments reduce emissions, and soil type impacts emissions, suggesting future research should explore non-linear relationships for sustainable road design.

Dongryul Kim, Hyeonjeong Kim, Kyoungseok Han

This paper proposes collision-free optimal trajectory planning for autonomous vehicles in highway traffic, where vehicles need to deal with the interaction among each other. To address this issue, a novel optimal control framework is suggested, which couples the trajectory of surrounding vehicles with collision avoidance constraints. Additionally, we describe a trajectory optimization technique under state constraints, utilizing a planner based on Pontryagin's Minimum Principle, capable of numerically solving collision avoidance scenarios with surrounding vehicles. Simulation results demonstrate the effectiveness of the proposed approach regarding interaction-based motion planning for different scenarios.

Oscar Amador, Manuel Urueña, Maria Calderon et al.

This paper evaluates the performance of the ETSI Contention-Based Forwarding (CBF) GeoNetworking protocol for distributing warning messages in highway scenarios, including its interaction with the Decentralized Congestion Control (DCC) mechanism. Several shortcomings of the standard ETSI CBF algorithm are identified, and we propose different solutions to these problems, which are able to reduce the number of transmissions by an order of magnitude, while reducing the message end-to-end delay and providing a reliability close to 100% in a large area of interest.

Hossein Kashiani, Niloufar Alipour Talemi, Fatemeh Afghah

Recent advancements in anomaly detection have shifted focus towards Multi-class Unified Anomaly Detection (MUAD), offering more scalable and practical alternatives compared to traditional one-class-one-model approaches. However, existing MUAD methods often suffer from inter-class interference and are highly susceptible to domain shifts, leading to substantial performance degradation in real-world applications. In this paper, we propose a novel robust prompt-driven MUAD framework, called ROADS, to address these challenges. ROADS employs a hierarchical class-aware prompt integration mechanism that dynamically encodes class-specific information into our anomaly detector to mitigate interference among anomaly classes. Additionally, ROADS incorporates a domain adapter to enhance robustness against domain shifts by learning domain-invariant representations. Extensive experiments on MVTec-AD and VISA datasets demonstrate that ROADS surpasses state-of-the-art methods in both anomaly detection and localization, with notable improvements in out-of-distribution settings.

Heyang Ding, Hainian Wang, Ziye Ma et al.

Cohesive failure is one of the primary reasons for low-temperature cracking in asphalt pavements. Understanding the micro-level mechanism is crucial for comprehending cohesive failure behavior. However, previous literature has not fully reported on this aspect. Moreover, there has been insufficient attention given to the correlation between macroscopic and microscopic failures. To address these issues, this study employed molecular dynamics simulation to investigate the low-temperature tensile behavior of asphalt binder. By applying virtual strain, the separation work during asphalt binder tensile failure was calculated. Additionally, a correlation between macroscopic and microscopic tensile behaviors was established. Specifically, a quadrilateral asphalt binder model was generated based on SARA fractions. By applying various combinations of virtual strain loading, the separation work at tensile failure was determined. Furthermore, the impact of strain loading combinations on separation work was analyzed. Normalization was employed to establish the correlation between macroscopic and microscopic tensile behaviors. The results indicated that thermodynamic and classical mechanical indicators validated the reliability of the tetragonal asphalt binder model. The strain loading combination consists of strain rate and loading number. All strain loading combinations exhibited the similar tensile failure characteristic. The critical separation strain was hardly influenced by strain loading combination. However, increasing strain rate significantly enhanced both the maximum traction stress and separation work of the asphalt binder. An increment in the loading number led to a decrease in separation work. The virtual strain combination of 0.5%-80 provided a more accurate representation of the actual asphalt's tensile behavior trend.

Faizan M. Tariq, David Isele, John S. Baras et al.

This paper proposes a hierarchical autonomous vehicle navigation architecture, composed of a high-level speed and lane advisory system (SLAS) coupled with low-level trajectory generation and trajectory following modules. Specifically, we target a multi-lane highway driving scenario where an autonomous ego vehicle navigates in traffic. We propose a novel receding horizon mixed-integer optimization based method for SLAS with the objective to minimize travel time while accounting for passenger comfort. We further incorporate various modifications in the proposed approach to improve the overall computational efficiency and achieve real-time performance. We demonstrate the efficacy of the proposed approach in contrast to the existing methods, when applied in conjunction with state-of-the-art trajectory generation and trajectory following frameworks, in a CARLA simulation environment.

Minjin Lee, SangHyun Cheon, Seung-Woo Son et al.

Urban road networks are well known to have universal characteristics and scale-invariant patterns, despite the different geographical and historical environments of cities. Previous studies on universal characteristics of the urban road networks mostly have paid attention to their network properties but often ignored the spatial networked structures. To fill the research gap, we explore the underlying spatial patterns of road networks. In doing so, we inspect the travel-route efficiency in a given road network across 70 global cities which provides information on the usage pattern and functionality of the road structure. The efficiency is quantified by the detour patterns of the travel routes, estimated by the detour index (DI). The DI is a long-standing popular measure, but its spatiality has been barely considered so far. In this study, we probe the behavior of DI with respect to spatial variables by scanning the network radially from a city center. Through empirical analysis, we first discover universal properties in DI throughout most cities, which are summarized as a constant behavior of DI regardless of the radial position from a city center and clear collapse into a single curve for DIs for various radii with respect to the angular distance. Especially, the latter enables us to know the scaling factor in the length scale. We also reveal that the core-periphery spatial structure of the roads induces the universal pattern, which is supported by an artificial road network model. Furthermore, we visualize the spatial DI pattern on the city map to figure out the city-specific characteristics. The most and least efficient connections of several representative cities show the potential for practical implications in analyzing individual cities.

Sahil Gangurde

In city, information about urban objects such as water supply, railway lines, power lines, buildings, roads, etc., is necessary for city planning. In particular, information about the spread of these objects, locations and capacity is needed for the policymakers to make impactful decisions. This thesis aims to segment the building and roads from the aerial image captured by the satellites and UAVs. Many different architectures have been proposed for the semantic segmentation task and UNet being one of them. In this thesis, we propose a novel architecture based on Google's newly proposed EfficientNetV2 as an encoder for feature extraction with UNet decoder for constructing the segmentation map. Using this approach we achieved a benchmark score for the Massachusetts Building and Road dataset with an mIOU of 0.8365 and 0.9153 respectively.

Piotr Mackiewicz, Eryk Mączka

Abstract: The timely use of appropriate renovation measures can effectively extend the life of road surfaces. For this purpose, it is necessary to carry out a detailed identification of damage, and then on its basis to assess the condition of road surfaces. Due to the development of advanced measurement techniques and computer applications, damage to pavements can be monitored faster and more accurately. This article presents a method of identifying damage to the pavement of a large area of the square with the use of a drone. The applicated method allowed to visualize and differentiate various surface defects faster and more preciously. The method also enabled determine causes and genesis of damage more greatly. Keywords: Drone; Pavement damage; DJI SPARK, Damage Identification

Muhammad Amri Imaduddin Maghribi, Ketut A Wiswamitra, Jojok Widodo S

Grand Shamaya Apartment Building, 44 Floor Apartment, is one of the buildings using a dual system construction. The system includes shear walls and moment-bearing frames (columns and beams) that work side by side to support lateral to gravity loads (earthquake and wind loads). The maximum load shear wall or 75% of the lateral load (wind and earthquake), and the size of the shear wall required is relatively large because it must withstand shear forces and bending moments. More treatment is needed to overcome this problem, namely by modifying the building's structure and adding an outrigger system. The Outrigger System itself is a wall component that functions as a one-floor beam. From the preliminary design, the column design is 1300mm x 1850 mm; beam measuring 900mm x 600 mm; plate thickness of 200 mm; shear wall thickness of 450 mm and outrigger design measuring 600 mm x 2000 mm thick. Then install the Outrigger System with axis positions T1 N ', T1 M', T1 E ', and T1 D' on floors 40 and 44. After re-analysis using the outrigger system, the deviation between floors can show a smaller value than before the outrigger system was applied. P-Delta effect control shows that the P-Delta effect in two structural directions can be neglected or safe because the maximum stability value of the structure in the X and Y directions is less than 0.09091. The latter fulfills the drift control. This result is the maximum value among several models that have been executed.

Rolands Izaks, Liga Gebauere, Romans Kornisovs et al.

Due to environmental issues and rising costs of construction materials, there is an increasing desire to use reclaimed asphalt pavement (RAP) material in road construction. However, using too much of this material may lead to impairment of fundamental properties of asphalt mix. Glass fibre material is a well-known modifier and could be used to compensate possible downgrade of properties. Research articles and theoretical material have shown that adding too much fibre glass reinforcement could cause damage to asphalt mixture. Therefore, in this research, reference mixture has been compared to three projected AC 11 surface mixtures with different amount of fibre glass. The same has been done to HMAC mixtures, but in this case, there is crumb rubber used as mixture modifier. Experimental part has shown that using fibre glass in asphalt mixtures for both construction layers may have positive influence on fundamental parameters of HMAC and AC asphalt mixes, which can be a good solvation for using waste glass fibre in road construction.

Mohamad Izuddin Saikhon, K. A. Masri, A. Arshad et al.

A study was carried out to evaluate the flexible pavement distresses for cracking and potholes in the parking area with and without commercial activity. Infrastructures such as parking areas are commonly used for another activity rather than for car park only. For example, fresh market, ceremony, and concert. This Study focusing on open space parking area as the gaps between other researchers that studied on highways or road network. The chosen of site location were divide into two categories which are urban area, Kuantan city and the educational area, Universiti Malaysia Pahang, Gambang. The aim is to study the severity level of distresses appeared on parking area. Therefore, the main objective is determining the most severe area of distresses by visual observation and performing the image software analysis to analyze the severity level of distresses with the guideline in collecting data based on national guidelines, published by the Public Works Department. Besides, performing Image Interpretation Group (IIG) as the method to classified the severity level by using Gwyddion Software. The data shows, 5 sample distresses for potholes were founded and 7 sample for cracking was collected at each site area. For the conclusion, parking area with commercial activity at urban area recorded the high number distresses and classified as the worst condition among the other site of parking area.

Balise Dabou, Christopher Kanali, zachary Abiero-Gariy

This study examines the effect of partially replacing cement with blue gumwood ash (BGWA) in stabilizing laterite soil to be used as a potential road base material. Initially, Ordinary Portland Cement was introduced to the soil at varying contents from 0 to 12% in steps of 3% by weight of the soil sample. Each wet sample of the soil was subjected to the Californian bearing ratio (CBR) and unconfined compressive strength (UCS) tests in determining the optimal soil-cement mix. Results show that CBR and UCS values increased as cement content increased, and a 6% cement content corresponding to a UCS value of 2.88 MPa at 7 days of curing met the specifications of the Overseas Road Note 31 to be used in the construction of road bases. The second treatment involved partially replacing the 6% cement content with BGWA in decreasing steps of 1%. Peak CBR value of 348% at 2% BGWA content (>160% recommended by Kenya road design manual) and UCS value of 2.99 MPa at 7 days of curing were obtained. Thus, BGWA can partially replace cement in stabilizing laterite soil for use in the construction of road bases as per the Overseas Road Note 31 specifications.