Journal articles: 'Road condition monitoring'

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Radopoulou, Stefania C., and Ioannis Brilakis. "Improving Road Asset Condition Monitoring." Transportation Research Procedia 14 (2016): 3004–12. http://dx.doi.org/10.1016/j.trpro.2016.05.436.

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Linton, Michael A., and Liping Fu. "Winter Road Surface Condition Monitoring." Transportation Research Record: Journal of the Transportation Research Board 2482, no. 1 (January 2015): 46–56. http://dx.doi.org/10.3141/2482-07.

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Oladele, Adewole S. "Evaluation and Analysis of Botswana Gravel Road Condition for District Transportation Networks Monitoring." Applied Mechanics and Materials 505-506 (January 2014): 740–44. http://dx.doi.org/10.4028/www.scientific.net/amm.505-506.740.

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Gravel roads are majorly affected by deterioration which manifests as loss of gravel materials due to traffic and environmental conditions. District Road Maintenance Managers are faced with competing investment demands to maintain gravel road networks in the best condition due to inadequate intelligent techniques of evaluating the roadway performance. The aim of evaluating the road network performance is to reduce the rate of deterioration so that maintenance interventions could be extended. Road condition data is a precursor for road monitoring and is collected on a periodic basis by road authorities to assist in transportation planning. The primary objective of this paper was to evaluate and analysis the trend of Botswana gravel road condition which best captures the effects of gravel road condition influencing factors. This was achieved by carrying out exploratory statistical analysis. Gravel road condition data were collected through the Botswana Roads Department covering 2002, 2005 and 2008 for Botswana district gravel road networks. The variables required for the analysis were clustered and pre-processed to determine their suitability. The analysis results gave a broad overview of the extent to which gravel road condition trends lend credence to their usefulness in district transportation networks monitoring in Botswana.

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Marciniuk, Karolina, Maciej Blaszke, and Bożena Kostek. "Acoustic Road Monitoring." MATEC Web of Conferences 231 (2018): 05002. http://dx.doi.org/10.1051/matecconf/201823105002.

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The subject of this research is showing the performance of an automatic acoustic road monitoring system proposed by the authors. The main goal of the study is describing road traffic by means of an acoustic representation and testing effectiveness of traffic flow sensors. Evaluation metrics of the road conditions such as velocity of the traffic flow, its structure and weather condition are presented along with acoustic descriptors derived from the audio signal analysis. Accuracy of emergency vehicles pass by detection based on acoustic monitoring is also briefly described.

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Åstrand, Max, Erik Jakobsson, Martin Lindfors, and John Svensson. "A system for underground road condition monitoring." International Journal of Mining Science and Technology 30, no. 3 (May 2020): 405–11. http://dx.doi.org/10.1016/j.ijmst.2020.04.006.

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Roberts, Ronald, Gaspare Giancontieri, Laura Inzerillo, and Gaetano Di Mino. "Towards Low-Cost Pavement Condition Health Monitoring and Analysis Using Deep Learning." Applied Sciences 10, no. 1 (January 1, 2020): 319. http://dx.doi.org/10.3390/app10010319.

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Governments are faced with countless challenges to maintain conditions of road networks. This is due to financial and physical resource deficiencies of road authorities. Therefore, low-cost automated systems are sought after to alleviate these issues and deliver adequate road conditions for citizens. There have been several attempts at creating such systems and integrating them within Pavement management systems. This paper utilizes replicable deep learning techniques to carry out hotspot analyses on urban road networks highlighting important pavement distress types and associated severities. Following this, analyses were performed illustrating how the hotspot analysis can be carried out to continuously monitor the structural health of the pavement network. The methodology is applied to a road network in Sicily, Italy where there are numerous roads in need of rehabilitation and repair. Damage detection models were created which accurately highlight the location and a severity assessment. Harmonized distress categories, based on industry standards, are utilized to create practical workflows. This creates a pipeline for future applications of automated pavement distress classification and a platform for an integrated approach towards optimizing urban pavement management systems.

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Kunz, Bethany K., Nicholas S. Green, Janice L. Albers, Mark L. Wildhaber, and Edward E. Little. "Use of Real-Time Dust Monitoring and Surface Condition to Evaluate Success of Unpaved Road Treatments." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 52 (October 9, 2018): 195–204. http://dx.doi.org/10.1177/0361198118799167.

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Fugitive dust from unpaved roads creates human health hazards, degrades road surfaces, and increases the cost of road maintenance. As a result, many different chemical treatments are applied to unpaved roads in an attempt to control dust and stabilize the wearing course. However, investigations of the effectiveness of these treatments have often been poorly planned or executed. The objective of this study was to use a combination of real-time dust monitoring and objective road condition evaluations to assess the success of two chemical treatments for a period of 19 months post-application, to provide quantitative information in support of road management decisions. Dust production from road sections treated with calcium chloride-based durablend-C™ or the synthetic fluid EnviroKleen® was monitored on five dates using a vehicle-mounted particulate matter meter. Both products reduced dust by up to 99% relative to an untreated control section during the monitoring period, and quantitative data from the meter were consistent with qualitative observations of dust conditions. Linear models of dust production indicated that road treatment and humidity explained 69% of the variation in dust over time. Road sections treated with either product developed less rutting and fewer potholes than the untreated control. Overall, the combination of real-time dust monitoring and surface condition evaluation was an effective approach for generating quantitative data on endpoints of interest to road managers.

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Dong, Dapeng, and Zili Li. "Smartphone Sensing of Road Surface Condition and Defect Detection." Sensors 21, no. 16 (August 12, 2021): 5433. http://dx.doi.org/10.3390/s21165433.

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Road surface condition is vitally important for road safety and transportation efficiency. Conventionally, road surface monitoring relies on specialised vehicles equipped with professional devices, but such dedicated large-scale road surveying is usually costly, time-consuming, and prohibitively difficult for frequent pavement condition monitoring—for example, on an hourly or daily basis. Current advances in technologies such as smartphones, machine learning, big data, and cloud analytics have enabled the collection and analysis of a great amount of field data from numerous users (e.g., drivers) whilst driving on roads. In this regard, we envisage that a smartphone equipped with an accelerometer and GPS sensors could be used to collect road surface condition information much more frequently than specialised equipment. In this study, accelerometer data were collected at low rate from a smartphone via an Android-based application over multiple test-runs on a local road in Ireland. These data were successfully processed using power spectral density analysis, and defects were later identified using a k-means unsupervised machine learning algorithm, resulting in an average accuracy of 84%. Results demonstrated the potential of collecting crowdsourced data from a large population of road users for road surface defect detection on a quasi-real-time basis. This frequent reporting on a daily/hourly basis can be used to inform the relevant stakeholders for timely road maintenance, aiming to ensure the road’s serviceability at a lower inspection and maintenance cost.

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Boucetta, Zakaria, Abdelaziz Fazziki, and Mohamed Adnani. "A Deep-Learning-Based Road Deterioration Notification and Road Condition Monitoring Framework." International Journal of Intelligent Engineering and Systems 14, no. 3 (June 30, 2021): 503–15. http://dx.doi.org/10.22266/ijies2021.0630.42.

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Ardian, Muhammad, Sahala Ruben A., and Reza Ardhianto. "HAUL ROAD CONDITION MONITORING USING SENSORS AND GNSS DATA." Prosiding Temu Profesi Tahunan PERHAPI 1, no. 1 (March 29, 2020): 293–304. http://dx.doi.org/10.36986/ptptp.v1i1.73.

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ABSTRAK Salah satu faktor agar mendapatkan performa alat angkut yang baik adalah dengan kondisi jalan angkut yang baik. Oleh karena itu, perlu diantisipasi dengan cara melakukan rekayasa engineering terhadap hal yang berpotensi menimbulkan kondisi jalan yang tidak baik. Dalam pembuatan prototype aplikasi ini digunakan data sensor strut pressure & data GNSS (Global Navigation Satellite System) sebagai teknologi untuk melakukan pengawasan terhadap kondisi jalan. Penggunaan sistem pengawasan jalan tambang menggunakan data sensor strut pressure dan data GNSS diharapkan dapat membantu meningkatkan produktivitas & efektivitas dalam pengambilan keputusan terkait dengan kegiatan pengawasan dan pemeliharaan kondisi jalan angkut di area tambang Pit Batu Hijau. Kata Kunci : Jalan Angkut, Fleet Management System, Sensor Strut Pressure, Global Navigation Satellite System, Analisa Data Geospasial ABSTRACT One of factor to get the good performed of hauling equipment is good condition of hauling road. Because of this, need to be prevent with engineering method about the things that potential can impact the poor haul road condition. The simulation was performed with using sensor and GNSS (Global Navigation Satellite System) Data as a technology about monitoring haul road condition. Utilizing haul road monitoring system using data sensor and GNSS expect can help to improve the productivity & effectivity for interpretation the good decision about monitoring activity and maintain Haul road condition at Pit Batu Hijau.Key Words : Haul Road, Fleet Management System, Sensor Strut Pressure, Global Navigation Satellite System, Geospatial Data Analyst

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Roberts, Ronald, Laura Inzerillo, and Gaetano Di Mino. "Using UAV Based 3D Modelling to Provide Smart Monitoring of Road Pavement Conditions." Information 11, no. 12 (December 4, 2020): 568. http://dx.doi.org/10.3390/info11120568.

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Road pavements need adequate maintenance to ensure that their conditions are kept in a good state throughout their lifespans. For this to be possible, authorities need efficient and effective databases in place, which have up to date and relevant road condition information. However, obtaining this information can be very difficult and costly and for smart city applications, it is vital. Currently, many authorities make maintenance decisions by assuming road conditions, which leads to poor maintenance plans and strategies. This study explores a pathway to obtain key information on a roadway utilizing drone imagery to replicate the roadway as a 3D model. The study validates this by using structure-from-motion techniques to replicate roads using drone imagery on a real road section. Using 3D models, flexible segmentation strategies are exploited to understand the road conditions and make assessments on the level of degradation of the road. The study presents a practical pipeline to do this, which can be implemented by different authorities, and one, which will provide the authorities with the key information they need. With this information, authorities can make more effective road maintenance decisions without the need for expensive workflows and exploiting smart monitoring of the road structures.

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Et al., Rashidbek M. Xudoyqulov. "Monitoring of Road Conditions Based on Geographic Information Systems: A Case Study of Yangiyul District of Tashkent Region, Uzbekistan." Psychology and Education Journal 58, no. 2 (February 1, 2021): 1500–1504. http://dx.doi.org/10.17762/pae.v58i2.2301.

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Modern requirements for road management require the use of new technologies and methods in solving the problems of construction, reconstruction and maintenance of roads. Currently, road organizations have begun work on the creation of a geographic information system for roads; digital maps with the location and layer of roads are being assembled. Information about roads, is very important data for many social-economic sectors of the Republic of Uzbekistan. In this paper, creating geospatial digital and informative map of roads of Bukhara district of Tashkent region is revealed. The map covers all types and categories of roads. All availability conditions of roads inserted to attribute table of ArcGIS 10.2 and analyzed geospatial operations. On maps, created by not road organizations, information about roads is presented in a standard form, which leads to the lack of modern information on the condition of roads.

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Lei, Tian, Abduallah A. Mohamed, and Christian Claudel. "An IMU-based traffic and road condition monitoring system." HardwareX 4 (October 2018): e00045. http://dx.doi.org/10.1016/j.ohx.2018.e00045.

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Linton, Michael A., and Liping Fu. "Connected Vehicle Solution for Winter Road Surface Condition Monitoring." Transportation Research Record: Journal of the Transportation Research Board 2551, no. 1 (January 2016): 62–72. http://dx.doi.org/10.3141/2551-08.

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Laubis, Kevin, Marcel Konstantinov, Viliam Simko, Alexander Gröschel, and Christof Weinhardt. "Enabling crowdsensing-based road condition monitoring service by intermediary." Electronic Markets 29, no. 1 (March 29, 2018): 125–40. http://dx.doi.org/10.1007/s12525-018-0292-7.

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Knyaz, V. A., and A. G. Chibunichev. "PHOTOGRAMMETRIC TECHNIQUES FOR ROAD SURFACE ANALYSIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 15, 2016): 515–20. http://dx.doi.org/10.5194/isprsarchives-xli-b5-515-2016.

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The quality and condition of a road surface is of great importance for convenience and safety of driving. So the investigations of the behaviour of road materials in laboratory conditions and monitoring of existing roads are widely fulfilled for controlling a geometric parameters and detecting defects in the road surface. Photogrammetry as accurate non-contact measuring method provides powerful means for solving different tasks in road surface reconstruction and analysis. The range of dimensions concerned in road surface analysis can have great variation from tenths of millimetre to hundreds meters and more. So a set of techniques is needed to meet all requirements of road parameters estimation. Two photogrammetric techniques for road surface analysis are presented: for accurate measuring of road pavement and for road surface reconstruction based on imagery obtained from unmanned aerial vehicle. The first technique uses photogrammetric system based on structured light for fast and accurate surface 3D reconstruction and it allows analysing the characteristics of road texture and monitoring the pavement behaviour. The second technique provides dense 3D model road suitable for road macro parameters estimation.

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Knyaz, V. A., and A. G. Chibunichev. "PHOTOGRAMMETRIC TECHNIQUES FOR ROAD SURFACE ANALYSIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 15, 2016): 515–20. http://dx.doi.org/10.5194/isprs-archives-xli-b5-515-2016.

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The quality and condition of a road surface is of great importance for convenience and safety of driving. So the investigations of the behaviour of road materials in laboratory conditions and monitoring of existing roads are widely fulfilled for controlling a geometric parameters and detecting defects in the road surface. Photogrammetry as accurate non-contact measuring method provides powerful means for solving different tasks in road surface reconstruction and analysis. The range of dimensions concerned in road surface analysis can have great variation from tenths of millimetre to hundreds meters and more. So a set of techniques is needed to meet all requirements of road parameters estimation. Two photogrammetric techniques for road surface analysis are presented: for accurate measuring of road pavement and for road surface reconstruction based on imagery obtained from unmanned aerial vehicle. The first technique uses photogrammetric system based on structured light for fast and accurate surface 3D reconstruction and it allows analysing the characteristics of road texture and monitoring the pavement behaviour. The second technique provides dense 3D model road suitable for road macro parameters estimation.

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Botshekan, Meshkat, Erfan Asaadi, Jake Roxon, Franz-Josef Ulm, Mazdak Tootkaboni, and Arghavan Louhghalam. "Smartphone-enabled road condition monitoring: from accelerations to road roughness and excess energy dissipation." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 477, no. 2246 (February 2021): 20200701. http://dx.doi.org/10.1098/rspa.2020.0701.

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We develop a framework to address the shortcomings of current smartphone-based approaches for road roughness sensing and monitoring through combining vehicle dynamics, random vibration theory and a two-layer inverse analysis. The proposed approach uses in-cabin recordings of the vehicle’s vertical acceleration measured by a smartphone positioned inside the car for the estimation of road roughness. The mechanistic road roughness–vehicle interaction model at the core of the proposed framework links the frequency spectrum of the vehicle’s vertical acceleration to the road roughness power spectral density and lends itself to the quantitative characterization of roughness-induced energy dissipation. We demonstrate that the measure of roughness provided by the stochastic model of car dynamics interacting with a rough road is fully compatible, in a statistical sense, with the spatial but deterministic definition of road roughness, and validate the identification strategy that originates from it against laser measurements of road roughness. The critical crowdsourcing features of the proposed framework, such as the marginal impact of phone position and transferability, are examined and its utility to meld with big data analytics to identify the class of vehicles travelling on a roadway network is demonstrated.

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BELLO-SALAU, H., A. M. AIBINU, A. J. ONUMANYI, S. AHUNSI, E. N. ONWUKA, and J. J. DUKIYA. "DEVELOPMENT OF A ROAD SURFACE CONDITION MONITORING AND DATABASE SYSTEM." i-manager's Journal on Computer Science 6, no. 4 (2019): 25. http://dx.doi.org/10.26634/jcom.6.4.15723.

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Baruah, Barnana, and Subhasish Dhal. "A secure road condition monitoring scheme in cloud based VANET." Computer Communications 174 (June 2021): 131–42. http://dx.doi.org/10.1016/j.comcom.2021.04.027.

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Radkevich, Maria, and Abdulkhakim Salokhiddinov. "Monitoring of pavement state as a basis for economic regulation of greenhouse gases emissions." Annals of Warsaw University of Life Sciences, Land Reclamation 46, no. 2 (December 1, 2014): 93–100. http://dx.doi.org/10.2478/sggw-2014-0008.

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Abstract Monitoring of pavement state as a basis for economic regulation of greenhouse gases emissions. Road complex which includes a road network with traffic, road services, car repair businesses, and enterprises for the production of fuels and materials for the repair of roads, is an important source of environmental pollution, and the degree of contamination depends on the quality of the road pavement. The present research is aimed to find the interaction between the amount of emissions into the environment from whole road complex and condition of road cover, on creation of a simplified method of determining economic damage from environmental pollution at the road operation and to develop basic mechanism of the economic impact on road services at excess emissions. According to the results of computer experiments mathematical relations of complex road emissions from the evenness of road pavement were obtained. Worked out method of greenhouse (and other) emission inventory permits to determine the total amount of emissions and to identify excess emissions relative to some acceptable level. Definition of economic damage of environmental pollution during road operation can be the basis for determining the amount of ban impositions on road service

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Li, Qingwu, Haisu Cheng, Yan Zhou, and Guanying Huo. "Road Vehicle Monitoring System Based on Intelligent Visual Internet of Things." Journal of Sensors 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/720308.

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In recent years, with the rapid development of video surveillance infrastructure, more and more intelligent surveillance systems have employed computer vision and pattern recognition techniques. In this paper, we present a novel intelligent surveillance system used for the management of road vehicles based on Intelligent Visual Internet of Things (IVIoT). The system has the ability to extract the vehicle visual tags on the urban roads; in other words, it can label any vehicle by means of computer vision and therefore can easily recognize vehicles with visual tags. The nodes designed in the system can be installed not only on the urban roads for providing basic information but also on the mobile sensing vehicles for providing mobility support and improving sensing coverage. Visual tags mentioned in this paper consist of license plate number, vehicle color, and vehicle type and have several additional properties, such as passing spot and passing moment. Moreover, we present a fast and efficient image haze removal method to deal with haze weather condition. The experiment results show that the designed road vehicle monitoring system achieves an average real-time tracking accuracy of 85.80% under different conditions.

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Sattar, Shahram, Songnian Li, and Michael Chapman. "Road Surface Monitoring Using Smartphone Sensors: A Review." Sensors 18, no. 11 (November 9, 2018): 3845. http://dx.doi.org/10.3390/s18113845.

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Road surface monitoring is a key factor to providing smooth and safe road infrastructure to road users. The key to road surface condition monitoring is to detect road surface anomalies, such as potholes, cracks, and bumps, which affect driving comfort and on-road safety. Road surface anomaly detection is a widely studied problem. Recently, smartphone-based sensing has become increasingly popular with the increased amount of available embedded smartphone sensors. Using smartphones to detect road surface anomalies could change the way government agencies monitor and plan for road maintenance. However, current smartphone sensors operate at a low frequency, and undersampled sensor signals cause low detection accuracy. In this study, current approaches for using smartphones for road surface anomaly detection are reviewed and compared. In addition, further opportunities for research using smartphones in road surface anomaly detection are highlighted.

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Nakatsuji, Takashi, Takashi Fujiwara, Toru Hagawara, and Yuki Onodera. "Snow and Ice Control System Based on Slipperiness Data Transmitted by Drivers: Usefulness of Subjective Slipperiness Data." Transportation Research Record: Journal of the Transportation Research Board 1533, no. 1 (January 1996): 44–49. http://dx.doi.org/10.1177/0361198196153300107.

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In Japan, the regulation of studded tires requires the establishment of new countermeasures for effective ice control on slippery roads in winter. The most important information for snow and ice control systems is determining the slipperiness of road surfaces. To detect the slipperiness simply and precisely, a monitoring system was examined in which drivers judged the slipperiness. To evaluate the suitability of such slipperiness data, three investigations were carried out: (a) the relationship between the road condition classification and the slipperiness index, (b) the effectiveness of the subdivision of road classification, and (c) the comparison of slipperiness indexes with the actual friction coefficients. To address the first problem, the road conditions were investigated for 1 month with the cooperation of 10 taxi companies. It was found that the subjective slipperiness index was more sensitive to changes in weather conditions than the road classifications, and that icy roads do not always correspond to slippery roads. That is, there was a limitation on expressing road conditions by road classification. For the second problem, a similar investigation was performed by subdividing the road conditions into more classes. It was concluded that the subdivision of road classification is not so effective in precisely representing the slipperiness of roads. For the third problem, it was clarified that the subjective slipperiness indexes more or less agree with the actual friction coefficients. As for the results, the slipperiness index showed potential for use in snow and ice control systems.

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Miśkiewicz, Mikołaj, Błażej Meronk, Tadeusz Brzozowski, and Krzysztof Wilde. "MONITORING SYSTEM OF THE ROAD EMBANKMENT." Baltic Journal of Road and Bridge Engineering 12, no. 4 (December 13, 2017): 218–24. http://dx.doi.org/10.3846/bjrbe.2017.27.

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The paper presents the analysis of the monitoring system of the embankment supported on concrete columns and overlaid by a load transfer platform with the embedded steel grid. This field investigation was to study the complex interaction between the columns, the load transfer platform layer, and steel grid via in situ measurements during erection and live loading of the embankment. The study was focused on the behaviour of steel grid and the behaviour of the outer rows of columns since there are limited reference data available for this problem. The system was designed to inform the engineers about the condition of the embankment at every stage of construction and during standard operation of the road. The measurements brought the information on strain variations of steel grid, concrete columns, and structural settlement and provided necessary evidence for the embankment numerical model validation.

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Brodnikova, Sofia D., and Nikolai A. Maslov. "APPLICATION OF SYSTEM FOR DIAGNOSTICS OF QUARRIES’S LAND SURFACE." Interexpo GEO-Siberia 2 (July 8, 2020): 15–23. http://dx.doi.org/10.33764/2618-981x-2020-2-15-23.

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Practical experience of diagnosing the open-pit earthwork based on the assessment of its condition using the functioning parameters of pit dump truck obtained from the system of remote monitoring of its technical state in changing road conditions is reviewed. The relationship between functioning parameters of the truck and road condition determining the stability of its design parameters in operation is found.

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Jonsson, Patrik, and Mats Riehm. "Infrared Thermometry in Winter Road Maintenance." Journal of Atmospheric and Oceanic Technology 29, no. 6 (June 1, 2012): 846–56. http://dx.doi.org/10.1175/jtech-d-11-00071.1.

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Abstract There is significant interest among road authorities in measuring pavement conditions to perform appropriate winter road maintenance. The most common monitoring methods are based on pavement-mounted sensors. This study’s hypothesis is that the temperature distribution in a pavement can be measured by means of a nonintrusive method to retrieve the topmost pavement temperature values. By utilizing the latest infrared (IR) technology, it is possible to retrieve additional information concerning both road temperatures and road conditions. The authors discovered that surface temperature readings from IR sensors are more reliable than data retrieved from traditional surface-mounted sensors during wet, snowy, or icy road conditions. It was also possible to detect changes in the road condition by examining how the temperatures in wheel tracks and in between the wheel tracks differ from a reference dry road condition. The conclusion was that nonintrusive measurement of the road temperature is able to provide an increase in relation to the knowledge about both the road temperature and the road condition. Another conclusion was that the surface temperature should not be considered as being equal to the ground temperatures retrieved from traditional surface-mounted sensors except under conditions of dry, stable roadways.

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Bopoto, Charles, Robert Geddes, and Michael Pinard. "Framework for Monitoring of Road Agency Performance in Rural Road Asset Management." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 12 (September 15, 2019): 843–54. http://dx.doi.org/10.1177/0361198119854088.

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The Research for Community Access Partnership (ReCAP) is providing technical assistance and capacity building initiatives to foster sustainable improvements in asset management performance in selected rural road agencies in Sub-Saharan Africa. Central to the research methodology is the development of a specification to enable road agencies to assess their performance in asset management as a basis for self-improvement. The specification is based on the development of an objectively determinable “road sector sustainability index” which measures the extent to which six building blocks considered essential for achieving effective road asset preservation are satisfied in practice. Periodic measurements of the condition of the project road networks, coupled with the collection of socioeconomic data, are being used to monitor the trend in road asset value, and to assess the effectiveness of, and improvements in, asset management as well as the impact of road condition on the wellbeing of rural communities. This paper outlines methodologies and tools that have been developed and piloted in four Sub-Saharan African countries to assess and monitor performance in rural road asset management and to achieve improvements over time. It summarizes progress achieved in the first 3 years since the project’s inception. The initial findings of the research indicate that severe institutional, funding, and technical shortcomings exist in the participating countries that preclude sustainable road asset preservation. However, following implementation of the methods summarized here, there is now an increased awareness of the importance of adopting a holistic approach to road asset management using simple and sustainable methods.

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B.A, Nafras Ameer, Pradeep Kumar J, Kumaran V, and Dinesh P. "Automated Sensing System for Monitoring Road Surface Condition Using Fog Computing." International Journal of Advanced Engineering, Management and Science 4, no. 3 (2018): 215–18. http://dx.doi.org/10.22161/ijaems.4.3.12.

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Aishwarya, R., R. Yogitha, and V. Kiruthiga. "Smart Road Surface Monitoring with Privacy Preserved Scheme for Vehicle Crowd Sensing." Journal of Computational and Theoretical Nanoscience 16, no. 8 (August 1, 2019): 3204–10. http://dx.doi.org/10.1166/jctn.2019.8162.

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In the Modern years many varieties of solutions has been framed for transport infrastructure such as street view application, traffic scrutiny, shortest road path navigation and route discovery. The current requirements and most significant of transport infrastructure has been lead towards the monitoring of road surface condition. Many varieties of solutions have been generated with sensor technology in existing system. Because of this, most of the systems using sensors are getting trouble in existing method for analyzing the condition of road surface and also no awareness or warning for the people who travel for the first time. So that initially visual observe of every surface of the road for the particular areas has been analyzed for a superior solution. Observation can be done by taking site survey, street view applications and also getting suggestion from the highway engineers. Later every detail about the surface of the observed road will be updated with the help of crowd sensing and Global Positioning System (GPS) Vehicle based sensing technology frequently which provides the user-friendly transport services to the customer. In our work the intermediate server called Fog Node is proposed to update the genuine data about the surface of the road condition to the cloud server by applying the Light Weight Signcryption method. The best road condition path for the sensor based cars is to be notified when the car is nearer to the Road Side Unit (RSU) with the help of Global System for Mobile communication (GSM) and also the details will be provided for the client on demand. The implementation can be proved with our proposed method to reach the best path recover, less storage, power consumption and finding proper route discovery. Also, it will dispense on demand data for the road based customers through mobile application with privacy preserved technology.

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Cabral, Frederico Soares, Hidekazu Fukai, and Satoshi Tamura. "Feature Extraction Methods Proposed for Speech Recognition Are Effective on Road Condition Monitoring Using Smartphone Inertial Sensors." Sensors 19, no. 16 (August 9, 2019): 3481. http://dx.doi.org/10.3390/s19163481.

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The objective of our project is to develop an automatic survey system for road condition monitoring using smartphone devices. One of the main tasks of our project is the classification of paved and unpaved roads. Assuming recordings will be archived by using various types of vehicle suspension system and speeds in practice, hence, we use the multiple sensors found in smartphones and state-of-the-art machine learning techniques for signal processing. Despite usually not being paid much attention, the results of the classification are dependent on the feature extraction step. Therefore, we have to carefully choose not only the classification method but also the feature extraction method and their parameters. Simple statistics-based features are most commonly used to extract road surface information from acceleration data. In this study, we evaluated the mel-frequency cepstral coefficient (MFCC) and perceptual linear prediction coefficients (PLP) as a feature extraction step to improve the accuracy for paved and unpaved road classification. Although both MFCC and PLP have been developed in the human speech recognition field, we found that modified MFCC and PLP can be used to improve the commonly used statistical method.

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Meocci, Monica, Valentina Branzi, and Andrea Sangiovanni. "An innovative approach for high-performance road pavement monitoring using black box." Journal of Civil Structural Health Monitoring 11, no. 2 (January 13, 2021): 485–506. http://dx.doi.org/10.1007/s13349-020-00463-8.

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AbstractOne of the criteria adopted by the Word Bank with the aim of defining the economic level of a country is represented by the condition of the road pavements. To ensure adequate road pavement quality, road authorities should be continuously monitoring and repair the detected anomalies. To fast solve problems associated with poor quality of road surface such as comfort or safety, the presence of distress must be detected quickly. The high-performance pavement distress detection, such as those base on the image processing or on the laser scanning, is very expensive and does not allow to the road administration to conduct the appropriate monitoring campaigns. To solve these problems, the paper describes the pave box methodology, an innovative and immediately operational distress detection approach based on the exploitation of data collected by the black boxes located inside the vehicles that routinely pass on the road network. Data processing and the algorithms used in the post-processing evaluation of the vertical acceleration were compared with existing visual surveys procedures such as PCI. Two different indices have been proposed to detect and classify both the local damages and the global condition of the entire road. Pave box provides a robust evaluation of the pavement condition that allows to detect all the severe distress and not less than 70% of the minor damages on the pavement surface. The proposal is characterized by low time and cost consumption and it represents an effective tool for road authorities.

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Kravcovas, Igoris, Audrius Vaitkus, and Rita Kleizienė. "Comparison of Pavement Performance Models for Urban Road Management System." Baltic Journal of Road and Bridge Engineering 15, no. 3 (August 14, 2020): 111–29. http://dx.doi.org/10.7250/bjrbe.2020-15.487.

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The key factors for effective pavement management system (PMS) are timely preservation and rehabilitation activities, which provide benefit in terms of drivers’ safety, comfort, budget and impact on the environment. In order to reasonably plan the preservation and rehabilitation activities, the pavement performance models are used. The pavement performance models are usually based on damage and distress observations of rural roads, and can be applied to forecast the performance of urban roads. However, the adjustment of the parameters related to traffic volume, speed and load, climate conditions, and maintenance has to be made before adding them to PMS for urban roads. The main objective of this study is to identify the performance indicators and to suggest pavement condition establishment methodology of urban roads in Vilnius. To achieve the objective, the distresses (rut depth and cracks), bearing capacity, and international roughness index (IRI) were measured for fifteen urban roads in service within a two-year period. The distresses, rut depth and IRI were collected with the Road Surface Tester (RST) and bearing capacity of pavement structures were measured with a Falling Weight Deflectometer (FWD). The measured distresses were compared to the threshold values identified in the research. According to the measured data, the combined pavement condition indices using two methodologies were determined, as well as a global condition index for each road. The analysed roads were prioritized for maintenance and rehabilitation in respect to these criteria. Based on the research findings, the recommendations for further pavement condition monitoring and pavement performance model implementation to PMS were highlighted.

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Shi, Wenbo, Ming Li, Jingxuan Guo, and Kaixuan Zhai. "Evaluation of Road Service Performance Based on Human Perception of Vibration While Driving Vehicle." Journal of Advanced Transportation 2020 (December 22, 2020): 1–8. http://dx.doi.org/10.1155/2020/8825355.

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Road surface monitoring is a significant issue in providing smooth road infrastructure for vehicles, and the key to road condition monitoring is to detect road potholes that affect driving comfort and transportation safety. This paper presents a simple, efficient, and accurate way to evaluate road service performance based on the acquisition of road vibration data by vibration sensors installed in vehicles. Inspired by the discrete fast Fourier transform, the vibration acceleration is processed, and the RMS value of vibration acceleration at 1/2 octave is calculated, after which the road vibration level is calculated. The vibration level is optimized according to the human body’s sensitivity to different frequencies of vibration, resulting in road service performance indicators that can reflect the human body’s real feelings. According to the road service performance index values on the road grading, combined with GPS data on the electronic map color block labeling, the results obtained for the road condition warning, road maintenance, driver route selection have an important significance.

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Loprencipe, Giuseppe, Flavio Guilherme Vaz de Almeida Filho, Rafael Henrique de Oliveira, and Salvatore Bruno. "Validation of a Low-Cost Pavement Monitoring Inertial-Based System for Urban Road Networks." Sensors 21, no. 9 (April 30, 2021): 3127. http://dx.doi.org/10.3390/s21093127.

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Road networks are monitored to evaluate their decay level and the performances regarding ride comfort, vehicle rolling noise, fuel consumption, etc. In this study, a novel inertial sensor-based system is proposed using a low-cost inertial measurement unit (IMU) and a global positioning system (GPS) module, which are connected to a Raspberry Pi Zero W board and embedded inside a vehicle to indirectly monitor the road condition. To assess the level of pavement decay, the comfort index awz defined by the ISO 2631 standard was used. Considering 21 km of roads with different levels of pavement decay, validation measurements were performed using the novel sensor, a high performance inertial based navigation sensor, and a road surface profiler. Therefore, comparisons between awz determined with accelerations measured on the two different inertial sensors are made; in addition, also correlations between awz, and typical pavement indicators such as international roughness index, and ride number were also performed. The results showed very good correlations between the awz values calculated with the two inertial devices (R2 = 0.98). In addition, the correlations between awz values and the typical pavement indices showed promising results (R2 = 0.83–0.90). The proposed sensor may be assumed as a reliable and easy-to-install method to assess the pavement conditions in urban road networks, since the use of traditional systems is difficult and/or expensive.

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Takahashi, Junji, Yusuke Kobana, Naoya Isoyama, Yoshito Tobe, and Guillaume Lopez. "YKOB: Participatory Sensing based Road Condition Monitoring using Smartphones worn by Cyclist." IEEJ Transactions on Electronics, Information and Systems 137, no. 4 (2017): 658–66. http://dx.doi.org/10.1541/ieejeiss.137.658.

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Wang, Yujue, Yong Ding, Qianhong Wu, Yongzhuang Wei, Bo Qin, and Huiyong Wang. "Privacy-Preserving Cloud-Based Road Condition Monitoring With Source Authentication in VANETs." IEEE Transactions on Information Forensics and Security 14, no. 7 (July 2019): 1779–90. http://dx.doi.org/10.1109/tifs.2018.2885277.

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Lenzo, B., G. Ottomano, S. Strano, M. Terzo, and C. Tordela. "A Physical-Based Observer for Vehicle State Estimation and Road Condition Monitoring." IOP Conference Series: Materials Science and Engineering 922 (October 29, 2020): 012005. http://dx.doi.org/10.1088/1757-899x/922/1/012005.

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TAKAHASHI, JUNJI, YUSUKE KOBANA, NAOYA ISOYAMA, YOSHITO TOBE, and GUILLAUME LOPEZ. "YKOB: Participatory Sensing-Based Road Condition Monitoring Using Smartphones Worn by Cyclist." Electronics and Communications in Japan 101, no. 4 (February 12, 2018): 3–14. http://dx.doi.org/10.1002/ecj.12027.

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Tan, Yumin, and Yunxin Li. "UAV Photogrammetry-Based 3D Road Distress Detection." ISPRS International Journal of Geo-Information 8, no. 9 (September 12, 2019): 409. http://dx.doi.org/10.3390/ijgi8090409.

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The timely and proper rehabilitation of damaged roads is essential for road maintenance, and an effective method to detect road surface distress with high efficiency and low cost is urgently needed. Meanwhile, unmanned aerial vehicles (UAVs), with the advantages of high flexibility, low cost, and easy maneuverability, are a new fascinating choice for road condition monitoring. In this paper, road images from UAV oblique photogrammetry are used to reconstruct road three-dimensional (3D) models, from which road pavement distress is automatically detected and the corresponding dimensions are extracted using the developed algorithm. Compared with a field survey, the detection result presents a high precision with an error of around 1 cm in the height dimension for most cases, demonstrating the potential of the proposed method for future engineering practice.

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Silva, Luís Augusto, Héctor Sanchez San Blas, David Peral García, André Sales Mendes, and Gabriel Villarubia González. "An Architectural Multi-Agent System for a Pavement Monitoring System with Pothole Recognition in UAV Images." Sensors 20, no. 21 (October 30, 2020): 6205. http://dx.doi.org/10.3390/s20216205.

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In recent years, maintenance work on public transport routes has drastically decreased in many countries due to difficult economic situations. The various studies that have been conducted by groups of drivers and groups related to road safety concluded that accidents are increasing due to the poor conditions of road surfaces, even affecting the condition of vehicles through costly breakdowns. Currently, the processes of detecting any type of damage to a road are carried out manually or are based on the use of a road vehicle, which incurs a high labor cost. To solve this problem, many research centers are investigating image processing techniques to identify poor-condition road areas using deep learning algorithms. The main objective of this work is to design of a distributed platform that allows the detection of damage to transport routes using drones and to provide the results of the most important classifiers. A case study is presented using a multi-agent system based on PANGEA that coordinates the different parts of the architecture using techniques based on ubiquitous computing. The results obtained by means of the customization of the You Only Look Once (YOLO) v4 classifier are promising, reaching an accuracy of more than 95%. The images used have been published in a dataset for use by the scientific community.

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Hrůza, Petr, Tomáš Mikita, and Přemysl Janata. "Monitoring of Forest Hauling Roads Wearing Course Damage using Unmanned Aerial Systems." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 64, no. 5 (2016): 1537–46. http://dx.doi.org/10.11118/actaun201664051537.

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Currently, a large part of the forest roads that were built using the bituminous surface technology in the second half of the last century have been worn out. This means that forest owners and forest managers urgently need to determine the amount and extent of this damage and establish a suitable repair plan, which demands both time and staff. The aim of the study is to verify whether it is possible, and with what precision, to detect the damage of the wearing course by means of unmanned aerial systems, which would facilitate and accelerate this process and possibly make it cheaper. A 3D model of a forest road was created using photos of the current state of a damaged part of a forest road. The aerial photographs were taken by an unmanned aircraft. To verify the accuracy of the model, cross sections of the road surface were surveyed tachymetrically and compared with the cross sections created in the 3D model in ArcMap, from photogrammetric pointcloud using aerial photographs from the unmanned aircraft. The RMSE of the values of the control points in the 3D model cross sections compared to the values of the points in the tachymetric measurement of the cross sections reached to within 0.0198 m. The results of the tested road section showed that the unmanned aerial systems can be used to detect the forest road surface damage with the difference in accuracy being up to 2 cm compared with the accuracy of the current tachymetric methods. Based on the results we can conclude that the used method is appropriate for detailed monitoring of the condition of the asphalt wearing course of forest roads and allows for a precise and objective localization and quantification of damage.

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Khahro, Shabir Hussain, Yasir Javed, and Zubair Ahmed Memon. "Low Cost Road Health Monitoring System: A Case of Flexible Pavements." Sustainability 13, no. 18 (September 14, 2021): 10272. http://dx.doi.org/10.3390/su131810272.

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A healthy road network plays a significant role in the socio-economic development of any country. Road management authorities struggle with pavement repair approaches and the finances to keep the existing road network to its best functionality. It has been observed that real-time road condition monitoring can drastically reduce road and vehicle maintenance expenses. There are various methods to analyze road health, but most are either expensive, costly, time-consuming, labor-intensive, or imprecise. This study aims to design a low-cost smart road health monitoring system to identify the road section for maintenance. An automized sensor-based system is developed to assist the road sections for repair and rehabilitation. The proposed system is mounted in a vehicle and the data have been collected for a more than 1000 km road network. The data have been processed using SPSS, and it shows that the proposed system is adequate for detecting the road quality. It is concluded that the proposed system can identify the vulnerable sections to add to the pavement maintenance plan. In the future, the created application can be launched as a smart citizen app where each car driver can install this application and can monitor the road quality automatically.

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Bi, Song, Zhong Cheng Zhao, Guan Wang, Lin Kong, Qi Diao, Cun Wu Han, and De Hui Sun. "Research on Travel Time Prediction under the Condition of Urban Rainstorm in Overpass Area." Advanced Materials Research 989-994 (July 2014): 5565–70. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.5565.

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Overpass is an important hub for urban road network facility, its traffic capacity severely restricts that of the entire road network. Since overpass area is easy to gather water in urban road network, rain water under the overpass is an important incentive for traffic jams. In this paper, a reliable and easily maintainable method is discussed to detect the depth of the road surface water, which designs and implements a monitoring system of urban road network ponding depth. Based on this, technique of predicting travel time has been researched about overpass area under water-logging condition. Through a real example, the technique discussed in this paper has been proved to be highly effective and veracious, and can be used to provide basic data for traffic guidance to plan out sound routes.

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Li, K., J. A. Misener, and K. Hedrick. "On-board road condition monitoring system using slip-based tyre-road friction estimation and wheel speed signal analysis." Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics 221, no. 1 (March 2007): 129–46. http://dx.doi.org/10.1243/1464419jmbd60.

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Pekša, Jānis. "ADAPTIVE KALMAN FILTER FORECASTING FOR ROAD MAINTAINERS." ENVIRONMENT. TECHNOLOGIES. RESOURCES. Proceedings of the International Scientific and Practical Conference 2 (June 20, 2019): 109. http://dx.doi.org/10.17770/etr2019vol2.4134.

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The article considers the road monitoring weather-stations which collects raw observations that are processed to be able to make the necessary forecasting for future decisions. For the road maintainers those predictions are crucial to make decisions daily. When it comes to the winter season when road safety is very important; however, the road condition is also affected by the snow and icing. In order to improve safety on the road network the road maintainers are trying to use every possible way to be able to provide it. A number of methods have been studied and compared to clarify the parameter required by Kalman filter, which can be improved by making forecasting more accurate. Several road monitoring weather-stations are merged into one region because they are relatively close to each other and it is assumed that there are common conditions in one region that may indicate changes in road conditions. The corresponding algorithms are applied for each region and then compared to each other. Adaptive Kalman filter is generalized in the relevant article in order to have a general understanding of how to correctly apply the approach. The main result of this article is a comparison with the different methods, which are finally compiled in a single table.

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D’Aranno, P., A. Di Benedetto, M. Fiani, and M. Marsella. "REMOTE SENSING TECHNOLOGIES FOR LINEAR INFRASTRUCTURE MONITORING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W11 (May 4, 2019): 461–68. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w11-461-2019.

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<p><strong>Abstract.</strong> The need for a continuous evaluation of the state of preservation of civil infrastructures during their lifetime is increasingly requiring advanced monitoring technologies. The improvement of spatial and temporal resolution of the measurements is now one of the most significant achievement, especially for large infrastructures. Monitoring actions are necessary to maintain safety conditions by controlling the evolution of deformation patterns or detecting significant instabilities. Remote sensing technique such as Differential Interferometry by Synthetic Aperture Radar (DInSAR) allows identifying environmental vulnerability and potential damages on large road infrastructures thus contributing to plan and optimize maintenance actions. DInSAR data allow to highlight instability processes and to quantify mean deformation velocities and displacement time series. This information can be analysed considering geotechnical and structural characteristics and adopted to evaluate possible safety condition improvement and damage mitigation. Using proximal remote sensing techniques, such as Light Detection And Ranging (LiDAR), it is possible to analyse the pavement conditions on 3D models derived from a dense point cloud acquired by Mobile Laser Scanner (MLS). By combining the DInSAR and LiDAR datasets a great improvement is expected in the capability to promptly identifying critical situations and understanding potential risks affecting extended road infrastructures. The principal aim of this paper is to provide a general overview of the most innovative remote sensing techniques for infrastructure safety condition assessments. Furthermore, a methodological approach to define a reliable procedure for data processing and integration is applied on a test area located in the municipality of Rome.</p>

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AlOrabi, Wael AlRahal, Sawsan Abdul Rahman, May El Barachi, and Azzam Mourad. "Towards on Demand Road Condition Monitoring Using Mobile Phone Sensing as a Service." Procedia Computer Science 83 (2016): 345–52. http://dx.doi.org/10.1016/j.procs.2016.04.135.

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Cui, Mingming, Dezhi Han, and Jun Wang. "An Efficient and Safe Road Condition Monitoring Authentication Scheme Based on Fog Computing." IEEE Internet of Things Journal 6, no. 5 (October 2019): 9076–84. http://dx.doi.org/10.1109/jiot.2019.2927497.

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Yan, Jing Ming. "Research on Driving Simulator in early Warning System of Vehicle Rear-End Collisions." Applied Mechanics and Materials 380-384 (August 2013): 581–85. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.581.

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Road safety has drawn wide attention from the whole society in recent years. The system of collision warning and anti-collision as an emerging vehicle safety technology can effectively help drivers avoid rear-end accident. This paper uses driver assistance system to analogously simulate true condition of driving and road. By real-time monitoring safe distance between two vehicles under the condition of following, this paper optimizes and adjusts the existing simulator. Drivers can avoid some untimely happening or unnecessary warning through improved and optimized simulator, which provides crucial technical conditions for producing more controlled and real-time interactive simulator.

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Journal articles on the topic 'Road condition monitoring'

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