Article
Chemistry, Multidisciplinary
Nam-Hyun Cho, Hong-Joon Kwon, Young-Chan Suh, Jangrak Kim
Summary: This study addresses the issues related to the application of the existing pavement condition index (PCI) in Korean airports. By redefining distress types, developing deduct value curves, and proposing a Korea airport pavement condition index (KPCI), the study offers a more accurate evaluation of pavement conditions and resolves communication difficulties between maintenance staff and decision makers. The field application results demonstrate the adequacy and effectiveness of the KPCI in assessing pavement conditions.
APPLIED SCIENCES-BASEL
(2022)
Article
Green & Sustainable Science & Technology
Gaetano Bosurgi, Orazio Pellegrino, Alessia Ruggeri, Giuseppe Sollazzo
Summary: Traffic loads and environmental factors can cause distress on road pavements, leading to hazardous conditions for drivers, especially during rain. Current methods for evaluating road surfaces focus on the detection of distresses through synthetic indicators, but fail to consider the hydraulic efficiency of the carriageway. In this paper, a synthetic indicator called Hydraulic Condition Index (HCI) is proposed to evaluate the hydraulic quality of road pavement surfaces, which can help road agencies prioritize maintenance needs and improve traffic safety.
Article
Engineering, Civil
S. Madeh Piryonesi, Tamer E. El-Diraby
Summary: This study aims to investigate the relationship between the International Roughness Index (IRI) and the Pavement Condition Index (PCI) using Long-Term Pavement Performance (LTPP) data. The findings suggest that the relationship between PCI and IRI can vary significantly based on factors such as location, functional class, and slope.
TRANSPORTATION GEOTECHNICS
(2021)
Review
Chemistry, Analytical
Eshta Ranyal, Ayan Sadhu, Kamal Jain
Summary: This paper provides an exhaustive literature review of road condition monitoring (RCM) technologies published from 2017 to 2022. It discusses the methodologies, contributions, limitations, and the role of smart sensors and data acquisition platforms in RCM systems. The paper also highlights the challenges in developing AI technologies and suggests potential areas for further exploration.
Article
Engineering, Civil
Monica Meocci, Valentina Branzi, Andrea Sangiovanni
Summary: The paper introduces a novel distress detection approach based on vehicle black box data, which can efficiently detect road conditions and classify damages severity, with low cost and high efficiency.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
(2021)
Article
Construction & Building Technology
Shajib Guha, Kamal Hossain
Summary: Assessing the condition of roadway assets is crucial for an efficient road management system. This paper introduces the idea of using road users' feedback as a means to evaluate road conditions, particularly for municipality roads facing challenges such as lack of resources and funding. Through an analysis of feedback data and the development of a distress-based pavement performance model, this paper provides local agencies with a simple decision-making tool.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2023)
Article
Construction & Building Technology
K. Kavinmathi, S. P. Atul Narayan, Shankar C. Subramanian
Summary: The distress of asphalt pavements on horizontal curves can be higher due to lateral load transfer and increased lateral forces on vehicles during cornering. A study using vehicle dynamics software found that curved sections sustain 2-6 times more damage compared to straight sections, emphasizing the need for separate pavement design on horizontal curves.
ROAD MATERIALS AND PAVEMENT DESIGN
(2022)
Review
Construction & Building Technology
Nima Sholevar, Amir Golroo, Sahand Roghani Esfahani
Summary: This study reviews the latest techniques in pavement condition data evaluation using machine learning methods, specifically focusing on the application of image classification, object detection, and segmentation in pavement distress assessment. The study also evaluates pavement automated data collection tools and condition indices from the perspective of machine learning applications. The review concludes that the overall trend in pavement condition evaluation is to apply machine learning techniques, although there are some limitations in detecting certain pavement distresses with complex patterns and indicating the severity and density of distresses, which warrant further research.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Engineering, Civil
Jose R. Medina, Ali Zalghout, Akshay Gundla, Samuel Castro, Kamil Kaloush
Summary: This study establishes a relationship between IRI and PCI based on the concept of time-deterioration superposition, and develops threshold limits for IRI measurements as a general reference for pavement condition. The analysis shows a good relationship between IRI and PCI, with IRI changes over time being related to PCI changes over time.
TRANSPORTATION RESEARCH RECORD
(2021)
Article
Engineering, Multidisciplinary
Amjad Issa, Haya Samaneh, Mohammad Ghanim
Summary: This research models the relationship between distress types and severity and Pavement Condition Index (PCI) using Artificial Neural Networks (ANN). The results show that the ANN model can predict PCI with high reliability.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Review
Construction & Building Technology
Abdulnaser M. Al-Sabaeei, Mena I. Souliman, Ajayshankar Jagadeesh
Summary: Smartphones have the potential to be used for efficient and cost-effective pavement condition monitoring (PCM), but further research and development are needed. The challenge lies in ensuring the accuracy of the collected data.
CONSTRUCTION AND BUILDING MATERIALS
(2024)
Article
Construction & Building Technology
Afarin Kheirati, Amir Golroo
Summary: The study aims to develop a novel pavement condition index using a machine learning model to comprehensively represent pavement condition in terms of structural adequacy, pavement roughness, road safety, and surface distress. The outcome shows an approximately 84% reduction in pavement distress analysis efforts, with the model having more than 80% accuracy and precision highly correlated with the Pavement Condition Index (PCI).
AUTOMATION IN CONSTRUCTION
(2022)
Review
Construction & Building Technology
Ayman H. El Hakea, Mohamed W. Fakhr
Summary: This paper provides a comprehensive review of computer vision models and applications in pavement distress detection and condition assessment. It includes a bibliometric analysis of recent publications, identification of trending tools and research gaps, and guidance for future research in pavement asset management using computer vision.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Construction & Building Technology
Amr A. Elhadidy, Sherif M. El-Badawy, Emad E. Elbeltagi
Summary: This study developed a simplified regression model linking PCI with IRI using the LTPP database and found that a sigmoid function best expressed the relationship between the two indices. The model had a high coefficient of determination (R-2) and low bias in predicted IRI values, with validation on a different dataset also yielding highly accurate predictions. This research proposed a pavement condition rating system based on IRI that is equivalent to the widely-used PCI rating method.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2021)
Article
Engineering, Civil
Eyal Levenberg, Asmus Skar, Shahrzad M. Pour, Ekkart Kindler, Matteo Pettinari, Milena Bajic, Tommy S. Alstrom, Uwe Schlotz
Summary: Modern cars are equipped with sensors to collect vehicle and environmental data, which can be used to assess road conditions and support real-time updates for pavement management systems. The LiRA project is an ongoing pilot project that aims to realize this vision using an electric car fleet and IoT devices. By combining machine learning and physical models, data can be transformed into relevant information for PMSs.
TRANSPORTATION RESEARCH RECORD
(2021)
Article
Chemistry, Analytical
Giuseppe Loprencipe, Flavio Guilherme Vaz de Almeida Filho, Rafael Henrique de Oliveira, Salvatore Bruno
Summary: The study introduces a novel inertial sensor-based system for indirectly monitoring road conditions, which showed promising correlations between a(wz) values and typical pavement indices. The proposed sensor offers a reliable and easy-to-install method for assessing pavement conditions in urban road networks, compared to traditional systems that are difficult and/or expensive to use.
Article
Chemistry, Analytical
Salvatore Bruno, Giulia Del Serrone, Paola Di Mascio, Giuseppe Loprencipe, Eugenio Ricci, Laura Moretti
Summary: The paper presents a remote monitoring system for evaluating airport runway structural performance, monitoring pavement response to traffic and environmental loads using embedded sensors. Specific calculation models enable data acquisition and real-time information delivery to guide infrastructure management.
Article
Chemistry, Physical
Paola Di Mascio, Giuseppe Loprencipe, Laura Moretti
Summary: The Cement Grouted Bituminous Mix (CGBM) is an innovative material for airport pavements that offers different cost benefits depending on traffic loads. After comparing the construction and maintenance costs of CGBM and traditional flexible pavements, the study shows that economic feasibility of CGBM solutions varies based on the traffic loads they are subjected to.
Article
Green & Sustainable Science & Technology
Zhun Fan, Huibiao Lin, Chong Li, Jian Su, Salvatore Bruno, Giuseppe Loprencipe
Summary: In this study, the use of Convolutional Neural Networks (CNNs) for crack identification in road pavement health and safety assessment is explored. A novel deep residual convolutional neural network called Parallel ResNet is proposed to overcome the limitations of existing methods. Experimental results demonstrate that Parallel ResNet achieves high accuracy in crack detection and measurement, making it a reliable method for pavement crack image analysis.
Article
Construction & Building Technology
Giuseppe Cantisani, Juan David Correa Panesso, Giulia Del Serrone, Paola Di Mascio, Guido Gentile, Giuseppe Loprencipe, Laura Moretti
Summary: This paper investigates congestion and safety issues at a three-level intersection in Italy and proposes the construction of new overpasses and underpasses to eliminate conflict points and improve traffic flow. Simulation and cost analysis confirm the effectiveness of this approach.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Engineering, Multidisciplinary
Rafael Henrique de Oliveira, Giuseppe Loprencipe, Flavio Guilherme Vaz de Almeida Filho, Rodrigo de Sousa Pissardini
Summary: In this paper, the authors present the first experimental results on the use of multiple very low-cost sensors aboard trains for vibration monitoring. They propose a collective approach to provide more accurate and robust results. The potential of the collective approach is proven through noise reduction and discrepant sensor identification.
Article
Green & Sustainable Science & Technology
Laura Moretti, Giuseppe Cantisani, Marco Carpiceci, Antonio D'Andrea, Giulia Del Serrone, Paola Di Mascio, Paolo Peluso, Giuseppe Loprencipe
Summary: Urban heat islands (UHI) are a clear effect of climate change, and this study investigated the impact of road pavements as a passive countermeasure and different surface materials on air temperature and human comfort. The results showed that the existing asphalt pavement performed the worst in terms of temperature and comfort, while light concrete blocks and grass pavement provided cooler solutions.
Article
Chemistry, Analytical
Salvatore Bruno, Lorenzo Vita, Giuseppe Loprencipe
Summary: This study proposes a novel method for monitoring the road surface conditions of stone pavements in a quick and easy way. Field tests were carried out in an Italian historic center using accelerometer sensors mounted on both a car and a bicycle. The results showed that the proposed method can be reliably used to assess the stone pavement conditions on the whole urban road network, as compared to existing pavement indicators.
Article
Chemistry, Analytical
Salvatore Bruno, Stefania Colonnese, Gaetano Scarano, Giulia Del Serrone, Giuseppe Loprencipe
Summary: A new signal on graph (SoG) model of road pavement distresses is proposed in this paper, and a novel nonlinear Bayesian estimator is used to recover distress metrics, improving automatic pavement distress detection systems. The methodology is evaluated on a large dataset of pavement distress values collected in field tests, and it can be used to schedule road section maintenance more effectively.
Article
Chemistry, Physical
Lingxiang Kong, Ling Xu, Yinfei Du, Jiao Jin, Giuseppe Loprencipe, Laura Moretti
Summary: This study proposed a new method to cool asphalt pavements by incorporating a hybrid mineral filler (HMF) with high emissivity into a reference asphalt mixture. The results showed that HMF increased the emissivity and rutting resistance of the asphalt mastic, and enhanced the thermal conductivity of the asphalt mixture. The combined effect of high emissivity and thermal conductivity led to a lower surface temperature in the tests.
Article
Green & Sustainable Science & Technology
Giuseppe Loprencipe, Salvatore Bruno, Giuseppe Cantisani, Antonio D'Andrea, Paola Di Mascio, Laura Moretti
Summary: Stone pavements are significant historical, architectural, and cultural heritage in Italy and many other cities worldwide. Road managers need to consider global conditions in order to decide suitable strategies and maintenance for different types of pavements. Evaluating the performance of stone pavements has no standard criteria or monitoring methods, and their uneven surfaces can be accepted based on the type of vehicles and travel conditions. Therefore, it is important to establish roughness assessment criteria considering the comfort of users in various vehicles.
Article
Green & Sustainable Science & Technology
Ling Xu, Yinfei Du, Giuseppe Loprencipe, Laura Moretti
Summary: The feasibility of recycling and reusing municipal solid waste incineration (MSWI) residue as an alternative to limestone filler (LF) in transport infrastructure was evaluated in this study. The rheological characteristics and fatigue performance of asphalt mastics and mixtures containing MSWI residue were investigated. The results showed that MSWI residue has certain advantages over LF in terms of high-temperature rheology and fatigue performance.
Article
Green & Sustainable Science & Technology
Giuseppe Cantisani, Salvatore Bruno, Antonio D'Andrea, Giuseppe Loprencipe, Paola Di Mascio, Laura Moretti
Summary: This paper presents a comprehensive methodology for assessing the irregularity of urban stone pavements. Four different methods have been investigated to describe pavement unevenness and comfort conditions, taking into account the comfort experienced by road users and different urban vehicles. This research provides a useful framework for road managers to make decisions in implementing an effective pavement management system.
Article
Chemistry, Analytical
Salvatore Bruno, Giuseppe Loprencipe, Paola Di Mascio, Giuseppe Cantisani, Nicola Fiore, Carlo Polidori, Antonio D'Andrea, Laura Moretti
Summary: This study presents a low-cost, high-performance pothole monitoring system using photogrammetry techniques to predict the pothole's shape and volume. The system utilizes a Raspberry Pi camera module connected to a Raspberry Pi 4 to create a 3D model of the pothole. The Raspberry-based configuration is mounted on a robot to reduce workers' exposure to live traffic and automate the process.
Article
Engineering, Multidisciplinary
Federico Foria, Mario Calicchio, Laura Moretti, Giuseppe Loprencipe
Summary: This paper presents an innovative methodology for surveying and inspecting existing railway tunnels using multidimensional mobile mapping systems. The proposed approach allows for collecting information necessary for the diagnostics of a structure with non-destructive tests, providing a new method for managing and identifying risks in existing tunnels.
