Hasil untuk "Highway engineering. Roads and pavements"

Timothy Proctor, Robin Blume-Kohout, Andrew Baczewski

Building a useful quantum computer is a grand science and engineering challenge, currently pursued intensely by teams around the world. In the 1980s, Richard Feynman and Yuri Manin observed independently that computers based on quantum mechanics might enable better simulations of quantum phenomena. Their vision remained an intellectual curiosity until Peter Shor published his famous quantum algorithm for integer factoring, and shortly thereafter a proof that errors in quantum computations can be corrected. Since then, quantum computing R&D has progressed rapidly, from small-scale experiments in university physics laboratories to well-funded industrial efforts and prototypes. Hype notwithstanding, quantum computers have yet to solve scientifically or practically important problems -- a target often called quantum utility. In this article, we describe the capabilities of contemporary quantum computers, compare them to the requirements of quantum utility, and illustrate how to track progress from today to utility. We highlight key science and engineering challenges on the road to quantum utility, touching on relevant aspects of our own research.

Sevil Kofteci, Mansor Nazary, Ahmad Masbah et al.

Due to the increasing volume of traffic on the world’s highways, researchers have been searching for new composite techniques and methods to develop durable and cost-effective pavement structures. The semi-rigid pavement is a composite pavement consisting of a porous asphalt mix with air voids between 25 and 30% and a high-fluidity cementitious grout. In this study, different cementitious grout mixes were prepared. Then a porous asphalt mix with almost 30% air void content was designed. After evaluating the workability, mechanical strength, and volume stability of the prepared grout mixes, the most suitable mix is proposed to fill the voids in the porous asphalt mix. Finally, the prepared semi-rigid pavement specimens were subjected to various tests to evaluate the performance characteristics of the designed pavement. The research concludes that the grout mixture ratio proposed in this study has good grouting ability and the semi-rigid pavement has superior performance characteristics.

Volodymyr Sistuk

Introduction. Road traffic surveys based on visual field observations continue to be the primary method for collecting traffic flow data. However, in recent years, the adoption of automated video analysis software utilizing artificial intelligence technologies has gained significant traction. This approach is emerging as a viable alternative to traditional data collection techniques, offering enhanced efficiency and precision in measuring traffic parameters. By processing traffic video footage, it is possible to generate origin-destination matrices for specific vehicle types and analyze individual vehicle performance. This enables the collection of detailed traffic flow data, thereby improving the planning and management of road infrastructure. Problem statement. The approach of utilizing traffic data video analysis with DataFromSky software by R.C.E. Systems can be effectively employed to calculate node impedance with intersection capacity analysis (ICA) within a transport macro model developed using PTV Visum software. However, to date, no studies have been conducted to assess the effectiveness of integrating these two technologies. Purpose. Evaluation of the capabilities of software for automated video analysis of traffic data for modeling impedance in the nodes of a transport macro-model. Materials and Methods. The study utilized traffic data video analysis powered by artificial intelligence, traffic indicator calculation based on the Highway Capacity Manual (HCM) methodology, and transport modeling of node impendence using ICA in PTV Visum.

Toktam Mohammadnejad, Jovin D'sa, Behdad Chalaki et al.

Merging onto a highway is a complex driving task that requires identifying a safe gap, adjusting speed, often interactions to create a merging gap, and completing the merge maneuver within a limited time window while maintaining safety and driving comfort. In this paper, we introduce a Safe Merging and Real-Time Merge (SMART-Merge) planner, a lattice-based motion planner designed to facilitate safe and comfortable forced merging. By deliberately adapting cost terms to the unique challenges of forced merging and introducing a desired speed heuristic, SMART-Merge planner enables the ego vehicle to merge successfully while minimizing the merge time. We verify the efficiency and effectiveness of the proposed merge planner through high-fidelity CarMaker simulations on hundreds of highway merge scenarios. Our proposed planner achieves the success rate of 100% as well as completes the merge maneuver in the shortest amount of time compared with the baselines, demonstrating our planner's capability to handle complex forced merge tasks and provide a reliable and robust solution for autonomous highway merge. The simulation result videos are available at https://sites.google.com/view/smart-merge-planner/home.

Xinyi Wang, Shaukat Ali, Paolo Arcaini

In order to handle the increasing complexity of software systems, Artificial Intelligence (AI) has been applied to various areas of software engineering, including requirements engineering, coding, testing, and debugging. This has led to the emergence of AI for Software Engineering as a distinct research area within the field of software engineering. With the development of quantum computing, the field of Quantum AI (QAI) is arising, enhancing the performance of classical AI and holding significant potential for solving classical software engineering problems. Some initial applications of QAI in software engineering have already emerged, such as test case optimization. However, the path ahead remains open, offering ample opportunities to solve complex software engineering problems cost-effectively with QAI. To this end, this paper presents a roadmap towards the application of QAI in software engineering. Specifically, we consider two of the main categories of QAI, i.e., quantum optimization algorithms and quantum machine learning. For each software engineering phase, we discuss how these QAI approaches can address some of the tasks associated with that phase. Moreover, we provide an overview of some of the possible challenges that need to be addressed to make the application of QAI for software engineering successful.

Siddharth Srikanth, John Krumm, Jonathan Qin

Road traffic congestion is a persistent problem. Focusing resources on the causes of congestion is a potentially efficient strategy for reducing slowdowns. We present NEXICA, an algorithm to discover which parts of the highway system tend to cause slowdowns on other parts of the highway. We use time series of road speeds as inputs to our causal discovery algorithm. Finding other algorithms inadequate, we develop a new approach that is novel in three ways. First, it concentrates on just the presence or absence of events in the time series, where an event indicates the temporal beginning of a traffic slowdown. Second, we develop a probabilistic model using maximum likelihood estimation to compute the probabilities of spontaneous and caused slowdowns between two locations on the highway. Third, we train a binary classifier to identify pairs of cause/effect locations trained on pairs of road locations where we are reasonably certain a priori of their causal connections, both positive and negative. We test our approach on six months of road speed data from 195 different highway speed sensors in the Los Angeles area, showing that our approach is superior to state-of-the-art baselines in both accuracy and computation speed.

Reni Suryanita, Azlansyah Mudahir Putra, Harnedi Maizir

Bata ringan cellular lightweight concrete (CLC) merupakan alternatif bahan bangunan untuk dinding yang memiliki densitas lebih rendah daripada bata merah, sehingga dapat memperkecil beban yang diterima oleh struktur dan memperkecil dimensi strukturnya. Namun bata ringan memiliki kelemahan rentan rapuh dan patah karena mengandung pori-pori akibat campuran material menggunakan busa dari foam agent. Umumnya bata ringan dibuat dengan menambahkan bahan aditif untuk meningkatkan mutu berdasarkan sifat mekanis kuat tekan, tegangan dan regangannya agar dapat memikul beban yang lebih berat. Salah satunya dengan menggunakan limbah abu terbang (fly ash) yang merupakan hasil pembakaran batu bara. Tujuan dari penelitian adalah untuk menentukan kadar penggunaan fly ash yang optimum dalam menentukan bata ringan dengan kuat tekan maksimum melalui studi eksperimental sifat mekanis bata ringan CLC. Penelitian menggunakan variasi komposisi dengan kadar fly ash sebesar 0%, 5%, 10%, 15%, 20% dan 25% dari berat semen pada sampel kubus dengan panjang sisi 10 cm. Pengujian kuat tekan dilakukan  pada umur 7, 14, dan 28 hari. Pengujian deformasi (penurunan) dilakukan pada umur 28 hari. Hasil kuat tekan dan penurunan digunakan untuk analisis nilai tegangan dan regangan pada bata ringan. Berdasarkan hasil penelitian variasi fly ash 10% pada umur 28 hari mendapatkan nilai kuat tekan yang paling besar yaitu sebesar 10,20 kg/cm2, penurunan sebesar 9,440 mm, tegangan sebesar 1,20 N/mm2 dan regangan sebesar 0,094. Kesimpulannya yaitu penambahan fly ash 10% dapat meningkatkan nilai kuat tekan bata ringan. Sehingga dapat memberikan rekomendasi kepada produsen bata ringan untuk komposisi campuran bata ringan yang optimal menggunakan fly ash.

Yusup Hi Sergi, Mufti Amir Sultan, Muhammad Amin

Smelting atau peleburan adalah proses mengekstraksi bijih logam murni dari dalam tanah. Dengan kata lain, ini adalah proses pemisahan logam murni dari bijih yang mengandungnya. Untuk mengekstraksi logam, bijih dipanaskan hingga suhu tinggi (di atas titik lelehnya). Untuk proses ini digunakan smelter yang dalam prosesnya akan menghasilkan limbah cair dan limbah padat (sludge). Sludge tersebut biasanya digunakan sebagai penutup lubang bekas tambang. Sludge digunakan sebagai material dasar pembentuk paving block untuk mengurangi limbah dan peningkatan nilai ekonomis. Pada penelitian ini sludge atau lumpur digunakan sebagai pengganti pasir pada produksi paving block. Kadar sludge yang digunakan adalah 10%, 25% dan 50% menggantikan volume pasir, paving block tanpa sludge sebagai benda uji kontrol. Untuk mengetahui mutu paving block yang dihasilkan dilakukan pengujian kuat tekan dan penyerapan. Hasil penelitian menunjukkan bahwa paving block dengan kadar 10% menghasilkan paving block mutu B, pada kadar 25% dan 50% menghasilkan paving block mutu C.

Ali Saleh, László Gáspár

Introduction. Rutting of flexible, super flexible and semi-rigid pavement structures is a typical and frequently decisive condition parameter, form of pavement deterioration. That is why, any research result in the field can have of high importance for the road engineers. Problem Statement Rutting poses a significant challenge to asphalt pavements, causing permanent deformation under heavy loads, particularly in warm and wet conditions. Purpose. This pavement distress type has — in addition to riding comfort challenges — important traffic safety consequences (e.g. aquaplaning), as well. The research work concentrates on the influence of the use of warm mix asphalt, reclaimed asphalt material and foamed bitumen binder on the rut depth of asphalt pavements. Materials and Methods. In integration of machine learning techniques, a Feedforward Neural Network model was presented to analyse the relationship between pavement rut depth and Reclaimed Asphalt Pavement (RAP) content. The model, trained for RAP content ranging from 0 % to 100 %, showcased varying R-squared values, with the highest at 50 % RAP content. Additionally, a Gaussian Process Regression (GPR) model was employed, highlighting the significant effects of RAP content between 75 % and 100 %. Sensitivity analysis on the GPR model provided insights into parameter effects, while the significant influence of the number of wheel passes on pavement rut depth values emphasized the importance of optimal road maintenance timing. Results The results of the machine learning model indicated a R-squared value of 0.476 for 0 % RAP content and higher values for mixtures containing RAP, with the highest value of 0.897 was found for 50 % RAP content in the asphalt mixture. A Gaussian Process Regression (GPR) model applied showed paradoxical effects between 75 % and 100 % RAP content. The derivative of the predicted mean rut depth as a function of RAP content revealed varying effects on Rut depth values in the case of different RAP content ranges. Sensitivity analysis on the GPR model was conducted by varying parameters such as Length Scale, Noise Level, and Amplitude. The results of this analysis provided insights into how changes in these parameters affected the mean squared error (MSE) for their various combinations. The influence of the number of wheel passes on rut depth values was examined, showing a significant increase in rut depth after 12,000 passes and reaching its maximum value after 20,000 passes.

Serhii Illiash, Tetiana Stasiuk

Introduction. The development of Ukraine's road network under current conditions is characterized by limited funding for road maintenance. At the same time, determining the scope and list of works based on the actual operational condition of the roads is extremely important, as it significantly affects the safety and comfort of road users, as well as the efficiency of vehicle operation. A standard norm is used to determine the planned scope of work, which is averaged for roads of the corresponding category. This simplifies calculations, but such an approach does not precisely establish the annual planned volumes of maintenance work for a specific section, as it does not consider its actual operational condition. Given the current level of funding, it is relevant to develop a methodology for determining the planned volumes and lists of maintenance work that is accurate enough, but does not require significant costs for road section inspections. Problem Statement. The determination of the scope of maintenance work is based on a comprehensive analysis of the road surface condition, forecasted traffic loads, and the allocation of budgetary resources. However, under martial law, the country’s priorities have shifted, with the focus on ensuring state defense, providing humanitarian aid, etc. Based on the current trends in the development of Ukraine’s road industry, the main task is the rational use of limited financial resources and maintaining roads in proper operational condition. The standards for the scope of maintenance work are approved in accordance with the Methodology for Determining the Funding for Road Construction, Reconstruction, Repair, and Maintenance (hereinafter — the Methodology) [1] and are averaged across Ukraine. According to this standard, a specific list and volume of works for 1 km of a national category II road is set, which is adjusted by correction coefficients and the length of the corresponding category sections to fit the required network, but does not take into account their actual operational condition. National roads usually have higher traffic intensity compared to local roads. Also, newly repaired roads significantly differ in operational condition from those that have not undergone repair for an extended period. Therefore, establishing a differentiated approach to updating the volumes of maintenance work for national and local roads is extremely important.

Edmond V. Muho, Niki D. Beskou

This paper reviews works on the dynamic analysis of flexible and rigid pavements under moving vehicles on the basis of continuum-based plane strain models and linear theories. The purpose of this review is to provide information about the existing works on the subject, critically discuss them and make suggestions for further research. The reviewed papers are presented on the basis of the various models for pavement-vehicle systems and the various methods for dynamically analyzing these systems. Flexible pavements are modeled by a homogeneous or layered half-plane with isotropic or anisotropic and linear elastic, viscoelastic or poroelastic material behavior. Rigid pavements are modeled by a beam or plate on a homogeneous or layered half-plane with material properties like the ones for flexible pavements. The vehicles are modeled as concentrated or distributed over a finite area loads moving with constant or time dependent speed. The above pavement-vehicle models are dynamically analyzed by analytical, analytical/numerical or purely numerical methods working in the time or frequency domain. Representative examples are presented to illustrate the models and methods of analysis, demonstrate their merits and assess the effects of the various parameters on pavement response. The paper closes with conclusions and suggestions for further research in the area. The significance of this research effort has to do with the presentation of the existing literature on the subject in a critical and easy to understand way with the aid of representative examples and the identification of new research areas.

Jongmin Yu, Chen Bene Chi, Sebastiano Fichera et al.

Road pavement detection and segmentation are critical for developing autonomous road repair systems. However, developing an instance segmentation method that simultaneously performs multi-class defect detection and segmentation is challenging due to the textural simplicity of road pavement image, the diversity of defect geometries, and the morphological ambiguity between classes. We propose a novel end-to-end method for multi-class road defect detection and segmentation. The proposed method comprises multiple spatial and channel-wise attention blocks available to learn global representations across spatial and channel-wise dimensions. Through these attention blocks, more globally generalised representations of morphological information (spatial characteristics) of road defects and colour and depth information of images can be learned. To demonstrate the effectiveness of our framework, we conducted various ablation studies and comparisons with prior methods on a newly collected dataset annotated with nine road defect classes. The experiments show that our proposed method outperforms existing state-of-the-art methods for multi-class road defect detection and segmentation methods.

Karol Wach

Abstract: Transport exclusion is one of the phenomena constituting a barrier to the functioning of local communities. The proposed legal solutions did not always bring the desired effect, therefore it was advisable to look for new mechanisms. One of them is co- financing of the reactivated communication lines from the special purpose fund. Transport exclusion primarily affects residents of smaller towns, for whom the lack of access to public transport may make it impossible to reach a doctor, school or workplace. This study analyzes the activity of voivodeship self-governments in organizing public collective transport in the field of bus transport. Until the establishment of the Fund for the development of public utility bus transport, it was insignificant. Significant changes in this respect took place after 2019, although not all voivodeships have yet undertaken to organize bus connections. Keywords: Mobility; Transport exclusion; Local community; Voivodeship

Juliusz Engelhardt

Abstract: The first part of the article presents investment projects in the field of railway infrastructure implemented in the Zachodniopomorskie Voivodeship under the National Railway Program until 2023. While positively assessing the scope of the implemented investments, delays in the completion of some projects were pointed out. In the second part of the article, on the basis of existing documents, numerous modernization and revitalization projects, as well as construction of new sections of railway lines in Western Pomerania in the perspective of 2030-2040 are indicated. The importance of the geopolitical location of the transport infrastructure of the Zachodniopomorskie Voivodeship in the transport system of the country is also indicated. Keywords: Transport policy; Railway infrastructure; Line and station investments

Sajjad Mozaffari, Mreza Alipour Sormoli, Konstantinos Koufos et al.

Accurate trajectory prediction of nearby vehicles is crucial for the safe motion planning of automated vehicles in dynamic driving scenarios such as highway merging. Existing methods cannot initiate prediction for a vehicle unless observed for a fixed duration of two or more seconds. This prevents a fast reaction by the ego vehicle to vehicles that enter its perception range, thus creating safety concerns. Therefore, this paper proposes a novel transformer-based trajectory prediction approach, specifically trained to handle any observation length larger than one frame. We perform a comprehensive evaluation of the proposed method using two large-scale highway trajectory datasets, namely the highD and exiD. In addition, we study the impact of the proposed prediction approach on motion planning and control tasks using extensive merging scenarios from the exiD dataset. To the best of our knowledge, this marks the first instance where such a large-scale highway merging dataset has been employed for this purpose. The results demonstrate that the prediction model achieves state-of-the-art performance on highD dataset and maintains lower prediction error w.r.t. the constant velocity across all observation lengths in exiD. Moreover, it significantly enhances safety, comfort, and efficiency in dense traffic scenarios, as compared to the constant velocity model.

Jorge Alberto Vasquez Rodriguez

La reorientación de la política pública de la infraestructura vial nacional de 1998 incorporó aspectos claves del Nuevo Estilo Nacional de Desarrollo vigente en el país en el momento de su oficialización. Este estilo desde principios de los años 80 promulga el protagonismo del mercado, en deterioro del papel del Estado, de ahí, que concordante con el mismo se trasladó la construcción, conservación y mantenimiento de la Red Vial Nacional del Estado al empresario privado, mediante contrataciones administrativas a cargo de un ente público denominado el Consejo Nacional de Vialidad, en donde en su consejo de administración, máximo jerarca de esa institución, estarían incorporados tres miembros de los empresarios organizados del mercado de la construcción de carreteras, con voz y voto, que coadministrarían la institución, con otros tres miembros representantes del gobierno de turno y uno de los gobiernos locales, con recursos provenientes de un Fondo Vial Nacional. La formulación de la política presenta un déficit de formulación, generada principalmente por la reformulación del problema público y de la estrategia de intervención de la política pública, generada desde “lo político” en la Asamblea Legislativa en el primer cuatrimestre de 1998, de ahí, que no se le brindó una posible respuesta a algunas de las causas del problema público como la relocalización de servicios, las expropiaciones, la coordinación con entes públicos que determinan el avance de la obra vial, la protección del medio ambiente, el control y calidad de las carreteras, el control excesivo sobre las obras viales, ejercidos directamente o indirectamente por entes públicos controladores, generándose así un déficit de formulación en la política pública, que incide negativamente en los resultados de la misma

Daihai Chen, Yanchang Wan, Shizhan Xu et al.

By the theory of vehicle-bridge coupled vibration analysis in railways, the dynamic analysis model for space of the train-track-bridge-steel wires coupled system was established. Moreover, a corresponding program was compiled based on the train-track-bridge-steel wires coupling vibration analysis method. Taking a 32 m simple beam which is in high-speed railways as the subject of study, the influence of effective prestress, steel wires eccentricity and vehicle speed on the dynamic response of the vehicle-bridge coupled vibration was analysed. The results show that the bridge dynamic response is remarkably influenced by prestressed steel wires. With the prestress increasing, the crest of the vertical dynamic response at the midspan decreased first, then increased. Moreover, the minimum peak value appeared when the prestress was 1300 MPa. When the steel wires were deflected downward relative to the design position, the vertical displacement of the bridge decreased by more than when the downshift occurred. The extreme values of the bridge lateral dynamic response and the train body acceleration response appeared when the train ran at 300 km/h. Prestressed steel wires had little effect on the dynamic response in the transverse direction of the bridge and train body.

Jan Pila, Frantisek Martinec

Abstract: The article is aimed to the possible trajectory of unmanned aerial vehicles in built- up agglomerations. It points out problems relating to safety, selection of flight corridors and description of the method of movement control of unmanned aerial vehicle according to specified trajectory of its movement. Design proposal of UAV reference trajectory memory block and methods of solving safety and reliability in built-up agglomerations are presented in the article Keywords: Aviation unmanned system; Built-up agglomerations; Safety; Pilot operator; Flight route; Control method; Established trajectory

Guijie Zhu, Zhun Fan, Jiacheng Liu et al.

The acquisition and evaluation of pavement surface data play an essential role in pavement condition evaluation. In this paper, an efficient and effective end-to-end network for automatic pavement crack segmentation, called RHA-Net, is proposed to improve the pavement crack segmentation accuracy. The RHA-Net is built by integrating residual blocks (ResBlocks) and hybrid attention blocks into the encoder-decoder architecture. The ResBlocks are used to improve the ability of RHA-Net to extract high-level abstract features. The hybrid attention blocks are designed to fuse both low-level features and high-level features to help the model focus on correct channels and areas of cracks, thereby improving the feature presentation ability of RHA-Net. An image data set containing 789 pavement crack images collected by a self-designed mobile robot is constructed and used for training and evaluating the proposed model. Compared with other state-of-the-art networks, the proposed model achieves better performance and the functionalities of adding residual blocks and hybrid attention mechanisms are validated in a comprehensive ablation study. Additionally, a light-weighted version of the model generated by introducing depthwise separable convolution achieves better a performance and a much faster processing speed with 1/30 of the number of U-Net parameters. The developed system can segment pavement crack in real-time on an embedded device Jetson TX2 (25 FPS). The video taken in real-time experiments is released at https://youtu.be/3XIogk0fiG4.

Rong Qin, Luwen Huangfu, Devon Hood et al.

Pavement Distress Recognition (PDR) is an important step in pavement inspection and can be powered by image-based automation to expedite the process and reduce labor costs. Pavement images are often in high-resolution with a low ratio of distressed to non-distressed areas. Advanced approaches leverage these properties via dividing images into patches and explore discriminative features in the scale space. However, these approaches usually suffer from information loss during image resizing and low efficiency due to complex learning frameworks. In this paper, we propose a novel and efficient method for PDR. A light network named the Kernel Inversed Pyramidal Resizing Network (KIPRN) is introduced for image resizing, and can be flexibly plugged into the image classification network as a pre-network to exploit resolution and scale information. In KIPRN, pyramidal convolution and kernel inversed convolution are specifically designed to mine discriminative information across different feature granularities and scales. The mined information is passed along to the resized images to yield an informative image pyramid to assist the image classification network for PDR. We applied our method to three well-known Convolutional Neural Networks (CNNs), and conducted an evaluation on a large-scale pavement image dataset named CQU-BPDD. Extensive results demonstrate that KIPRN can generally improve the pavement distress recognition of these CNN models and show that the simple combination of KIPRN and EfficientNet-B3 significantly outperforms the state-of-the-art patch-based method in both performance and efficiency.