scholarly journals An innovative approach for high-performance road pavement monitoring using black box

2021 ◽  
Author(s):  
Monica Meocci ◽  
Valentina Branzi ◽  
Andrea Sangiovanni
Keyword(s):  
High Performance ◽  
Laser Scanning ◽  
Poor Quality ◽  
Vertical Acceleration ◽  
Pavement Distress ◽  
The Road ◽  
Road Pavement ◽  
Pavement Monitoring ◽  
Global Condition ◽  
On The Road

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.

Incorporating Vertical Acceleration for Defining Driving Behaviour

2019 ◽  
Vol 9 (2) ◽  
pp. 38-48
Author(s):  
Laura Eboli ◽  
Gabriella Mazzulla ◽  
Giuseppe Pungillo
Keyword(s):  
Road Safety ◽  
Weather Condition ◽  
Relevant Parameter ◽  
Vertical Acceleration ◽  
The Road ◽  
Driving Behaviour ◽  
Road Pavement ◽  
Driving Conditions ◽  
The Difference ◽  
On The Road

Acceleration of a vehicle is composed of three components: longitudinal, lateral, and vertical acceleration. Longitudinal and lateral accelerations have been frequently considered as components for investigating driving behaviour, with the aim of improving road safety. But in particular situations during the motion of the vehicle, also vertical acceleration is relevant. In this paper, the authors want to demonstrate that vertical acceleration is also a relevant parameter to be considered in terms of road safety. The authors focus on the difference registered by considering only lateral and longitudinal acceleration and by considering also vertical acceleration in the analysis of driving behaviour through real tests on the road. All the parameters were registered through a global positioning system (GPS) device and a tri-axial accelerometer, which allow the geo-referenced kinematic parameters of the vehicle to be detected. For this purpose, over 110 tests covering about 600 kilometers were completed. All the experimental surveys were conducted in a good weather condition, under dry road pavement conditions, on weekdays, during day time and out-of-peak hours, in order to have no influence from the traffic flow. Each path was repeatedly run by the driver in order to collect the instantaneous speed and acceleration along the pattern. During the tests, about 40,000 instantaneous values of vehicle position have been registered. The survey interested a segment of the Italian National road n.107 (S.S. 107), in Southern Italy. The authors found that by considering vertical together with longitudinal and lateral accelerations, a higher number of unsafe driving conditions can be identified. More specifically, the proposed methodology allows 20% extra of dangerous driving conditions to be registered. For this reason, the authors retain that also vertical acceleration should be considered in the definition of the safety domain, because it determines the intensity of the exchange forces between the tires and road pavement, and in some cases, it leads to a loss of friction. Definitively, the authors retain that vertical acceleration is not only useful as indicator of comfort on board, but it has an important role also in terms of road safety.

scholarly journals Effects of Vehicular Speed on the Assessment of Pavement Road Roughness

2019 ◽  
Vol 9 (9) ◽  
pp. 1783 ◽  
Author(s):  
Giuseppe Loprencipe ◽  
Pablo Zoccali ◽  
Giuseppe Cantisani
Keyword(s):  
Surface Characteristics ◽  
Ride Quality ◽  
Vertical Acceleration ◽  
The Road ◽  
Road Pavement ◽  
Road Profile ◽  
Vehicular Speed ◽  
On The Road ◽  
Single Number ◽  
Iso 2631

Good ride quality is a fundamental requirement for all road networks in modern countries. For this purpose, it is essential to monitor and evaluate the effect of irregularities on road pavement surfaces. In the last few decades, many roughness indices have been proposed, with the aim to represent shortly the pavement surface characteristics and the relative performances, using a single number and a correspondent scale of values. In this work, a comparison between three different evaluation methods (International Roughness Index, ISO 8608 road profile classification and frequency-weighted vertical acceleration awz according to ISO 2631) was carried out, applying these methods to some real road profiles. The similarities and differences between the obtained results are described, evaluating the effect of the road characteristic speed on the roughness thresholds. In fact, the specific aim of the analyses is to underline the need to use different thresholds depending on the speed at which the vehicular traffic can travel on the road sections. In this way, it will be possible to identify appropriate thresholds for the various types of roads, having for each of them a specific range of design or operating speed.

scholarly journals The Limestone as a Materials Combination of Base Course on the Road Pavement

2021 ◽  
Vol 1125 (1) ◽  
pp. 012019
Author(s):  
Yosef Cahyo Setianto Poernomo ◽  
Sigit Winarto ◽  
Zendy Bima Mahardana ◽  
Dwifi Aprillia Karisma ◽  
Rekso Ajiono
Keyword(s):  
The Road ◽  
Road Pavement ◽  
Base Course ◽  
On The Road

Extraction of road boundary from MLS data using laser scanner ground trajectory

2021 ◽  
Vol 13 (1) ◽  
pp. 690-704
Author(s):  
Lichun Sui ◽  
Jianfeng Zhu ◽  
Mianqing Zhong ◽  
Xue Wang ◽  
Junmei Kang
Keyword(s):  
Laser Scanning ◽  
Laser Scanner ◽  
Boundary Tracking ◽  
The Road ◽  
Navigation Data ◽  
Vehicle Trajectories ◽  
Upward Slope ◽  
Tracking Model ◽  
On The Road ◽  
Boundary Model

Abstract Various means of extracting road boundary from mobile laser scanning data based on vehicle trajectories have been investigated. Independent of positioning and navigation data, this study estimated the scanner ground track from the spatial distribution of the point cloud as an indicator of road location. We defined a typical edge block consisting of multiple continuous upward fluctuating points by abrupt changes in elevation, upward slope, and road horizontal slope. Subsequently, such edge blocks were searched for on both sides of the estimated track. A pseudo-mileage spacing map was constructed to reflect the variation in spacing between the track and edge blocks over distance, within which road boundary points were detected using a simple linear tracking model. Experimental results demonstrate that the ground trajectory of the extracted scanner forms a smooth and continuous string just on the road; this can serve as the basis for defining edge block and road boundary tracking algorithms. The defined edge block has been experimentally verified as highly accurate and strongly noise resistant, while the boundary tracking algorithm is simple, fast, and independent of the road boundary model used. The correct detection rate of the road boundary in two experimental data is more than 99.2%.

scholarly journals Pavement Distress Detection Methods: A Review

2018 ◽  
Vol 3 (4) ◽  
pp. 58 ◽  
Author(s):  
Antonella Ragnoli ◽  
Maria De Blasiis ◽  
Alessandro Di Benedetto
Keyword(s):  
Data Collection ◽  
Operating Cost ◽  
Pavement Management ◽  
Point Of View ◽  
Detection Methods ◽  
Technical Improvement ◽  
Pavement Distress ◽  
The Road ◽  
Road Pavement ◽  
Pavement Distress Detection

The road pavement conditions affect safety and comfort, traffic and travel times, vehicles operating cost, and emission levels. In order to optimize the road pavement management and guarantee satisfactory mobility conditions for all road users, the Pavement Management System (PMS) is an effective tool for the road manager. An effective PMS requires the availability of pavement distress data, the possibility of data maintenance and updating, in order to evaluate the best maintenance program. In the last decade, many researches have been focused on pavement distress detection, using a huge variety of technological solutions for both data collection and information extraction and qualification. This paper presents a literature review of data collection systems and processing approach aimed at the pavement condition evaluation. Both commercial solutions and research approaches have been included. The main goal is to draw a framework of the actual existing solutions, considering them from a different point of view in order to identify the most suitable for further research and technical improvement, while also considering the automated and semi-automated emerging technologies. An important attempt is to evaluate the aptness of the data collection and extraction to the type of distress, considering the distress detection, classification, and quantification phases of the procedure.

scholarly journals Thermal Analysis of Asphalt Concrete Pavements Heated with Amorphous Metal Technology

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Cesare Sangiorgi ◽  
Cecilia Settimi ◽  
Piergiorgio Tataranni ◽  
Claudio Lantieri ◽  
Solomon Adomako
Keyword(s):  
Amorphous Material ◽  
Concrete Pavements ◽  
Road Maintenance ◽  
Warm Up ◽  
Physical Methods ◽  
The Road ◽  
Road Pavement ◽  
Heating Device ◽  
Critical Issues ◽  
On The Road

Undoubtedly, the most commonly used method for road maintenance includes the use of winter service vehicles to clear thoroughfares of snow and the spraying of chemicals to prevent ice formation on the road surface. The application of these traditional methods on road and airport pavements possesses numerous environmental, organizational, and technical challenges. To overcome these critical issues, new nontraditional technologies that act within the pavement, thereby increasing its temperature, have been developed. In relation to the heat source used, these are classified into chemical and physical methods. The purpose of this research is to study the temperature variation under the thermal transient process produced by the action of the physically heating device installed in the road pavement. The heating device is a ribbon, made of amorphous material, which is able to produce heat to warm up the pavement and its surface. Based on its principle of operation, it is classified among the nontraditional physical methods for the treatment of snow and ice. In this work, the performance of the heating ribbons on an experimental site at the G. Marconi International Airport in Bologna (Italy) is presented.

scholarly journals Accurate whole-night sleep monitoring with dry-contact ear-EEG

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kaare B. Mikkelsen ◽  
Yousef R. Tabar ◽  
Simon L. Kappel ◽  
Christian B. Christensen ◽  
Hans O. Toft ◽  
...  
Keyword(s):  
High Performance ◽  
Well Being ◽  
Extensive Study ◽  
Sleep Monitoring ◽  
The Road ◽  
Scalp Eeg ◽  
Dry Contact ◽  
Negative Effect ◽  
On The Road

AbstractSleep is a key phenomenon to both understanding, diagnosing and treatment of many illnesses, as well as for studying health and well being in general. Today, the only widely accepted method for clinically monitoring sleep is the polysomnography (PSG), which is, however, both expensive to perform and influences the sleep. This has led to investigations into light weight electroencephalography (EEG) alternatives. However, there has been a substantial performance gap between proposed alternatives and PSG. Here we show results from an extensive study of 80 full night recordings of healthy participants wearing both PSG equipment and ear-EEG. We obtain automatic sleep scoring with an accuracy close to that achieved by manual scoring of scalp EEG (the current gold standard), using only ear-EEG as input, attaining an average Cohen’s kappa of 0.73. In addition, this high performance is present for all 20 subjects. Finally, 19/20 subjects found that the ear-EEG had little to no negative effect on their sleep, and subjects were generally able to apply the equipment without supervision. This finding marks a turning point on the road to clinical long term sleep monitoring: the question should no longer be whether ear-EEG could ever be used for clinical home sleep monitoring, but rather when it will be.

scholarly journals Automated Pavement Crack Damage Detection Using Deep Multiscale Convolutional Features

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Weidong Song ◽  
Guohui Jia ◽  
Hong Zhu ◽  
Di Jia ◽  
Lin Gao
Keyword(s):  
High Performance ◽  
Crack Detection ◽  
Automated Detection ◽  
Key Factors ◽  
The Road ◽  
Intelligent Maintenance ◽  
Road Pavement ◽  
Maintenance Systems ◽  
High Level ◽  
Pavement Crack Detection

Road pavement cracks automated detection is one of the key factors to evaluate the road distress quality, and it is a difficult issue for the construction of intelligent maintenance systems. However, pavement cracks automated detection has been a challenging task, including strong nonuniformity, complex topology, and strong noise-like problems in the crack images, and so on. To address these challenges, we propose the CrackSeg—an end-to-end trainable deep convolutional neural network for pavement crack detection, which is effective in achieving pixel-level, and automated detection via high-level features. In this work, we introduce a novel multiscale dilated convolutional module that can learn rich deep convolutional features, making the crack features acquired under a complex background more discriminant. Moreover, in the upsampling module process, the high spatial resolution features of the shallow network are fused to obtain more refined pixel-level pavement crack detection results. We train and evaluate the CrackSeg net on our CrackDataset, the experimental results prove that the CrackSeg achieves high performance with a precision of 98.00%, recall of 97.85%, F-score of 97.92%, and a mIoU of 73.53%. Compared with other state-of-the-art methods, the CrackSeg performs more efficiently, and robustly for automated pavement crack detection.

Sign in / Sign up

Export Citation Format

Share Document