scholarly journals Estimating Pavement Roughness by Fusing Color and Depth Data Obtained from an Inexpensive RGB-D Sensor

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1655 ◽  
Author(s):  
Ahmadreza Mahmoudzadeh ◽  
Amir Golroo ◽  
Mohammad Jahanshahi ◽  
Sayna Firoozi Yeganeh
Keyword(s):  
Surface Defects ◽  
Cost Effective ◽  
Pavement Management ◽  
Outdoor Environment ◽  
Primary Data ◽  
International Roughness Index ◽  
The Road ◽  
Pavement Roughness ◽  
Power Spectral ◽  
Road Roughness

Measuring pavement roughness and detecting pavement surface defects are two of the most important tasks in pavement management. While existing pavement roughness measurement approaches are expensive, the primary aim of this paper is to use a cost-effective and sufficiently accurate RGB-D sensor to estimate the pavement roughness in the outdoor environment. An algorithm is proposed to process the RGB-D data and autonomously quantify the road roughness. To this end, the RGB-D sensor is calibrated and primary data for estimating the pavement roughness are collected. The collected depth frames and RGB images are registered to create the 3D road surfaces. We found that there is a significant correlation between the estimated International Roughness Index (IRI) using the RGB-D sensor and the manual measured IRI using rod and level. By considering the Power Spectral Density (PSD) analysis and the repeatability of measurement, the results show that the proposed solution can accurately estimate the different pavement roughness.

scholarly journals Evaluation of the methodologies used to generate random pavement profiles based on the power spectral density: An approach based on the International Roughness Index

2017 ◽  
Vol 37 (1) ◽  
pp. 49 ◽  
Author(s):  
Boris Jesús Goenaga ◽  
Luis Guillermo Fuentes Pumarejo ◽  
Otto Andrés Mora Lerma
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Pavement Management ◽  
Dynamic Loads ◽  
International Roughness Index ◽  
Vertical Excitation ◽  
Shaping Filter ◽  
Pavement Roughness ◽  
Power Spectral ◽  
Roughness Index

The pavement roughness is the main variable that produces the vertical excitation in vehicles. Pavement profiles are the main determinant of (i) discomfort perception on users and (ii) dynamic loads generated at the tire-pavement interface, hence its evaluation constitutes an essential step on a Pavement Management System. The present document evaluates two specific techniques used to simulate pavement profiles; these are the shaping filter and the sinusoidal approach, both based on the Power Spectral Density. Pavement roughness was evaluated using the International Roughness Index (IRI), which represents the most used index to characterize longitudinal road profiles. Appropriate parameters were defined in the simulation process to obtain pavement profiles with specific ranges of IRI values using both simulation techniques. The results suggest that using a sinusoidal approach one can generate random profiles with IRI values that are representative of different road types, therefore, one could generate a profile for a paved or an unpaved road, representing all the proposed categories defined by ISO 8608 standard. On the other hand, to obtain similar results using the shaping filter approximation a modification in the simulation parameters is necessary. The new proposed values allow one to generate pavement profiles with high levels of roughness, covering a wider range of surface types. Finally, the results of the current investigation could be used to further improve our understanding on the effect of pavement roughness on tire pavement interaction. The evaluated methodologies could be used to generate random profiles with specific levels of roughness to assess its effect on dynamic loads generated at the tire-pavement interface and user’s perception of road condition.

scholarly journals Contactless approach to determine pavement skid resistance for Pavement Management System

2018 ◽  
Vol 222 ◽  
pp. 01003
Author(s):  
Jakub Fengier ◽  
Mieczysław Słowik ◽  
Andrzej Pożarycki
Keyword(s):  
Management System ◽  
Pavement Management ◽  
Coefficient Of Determination ◽  
Specific Power ◽  
Skid Resistance ◽  
Pavement Management System ◽  
Slip Ratio ◽  
Pavement Roughness ◽  
Power Spectral ◽  
Density Values

Standard method to assess the pavement profile is to calculate the MPD (Mean Profile Depth) index based on results obtained usually by usage of laser techniques. In analysis the models of the surface pavements have been used in order to calculate the s1, s2, s3 parameters values corresponding to mega-, macro- and microtexture respectively. The values of the developed parameters s1, s2, s3 are calculated from the specific power spectral density values of surface roughness obtained for the threshold pavement roughness wavelength equal to 0.1, 0.05, 0.005 and 0.0005 m. The skid resistance has been correlated to the s1, s2, s3 parameters using 11 varied cases related to asphalt and concrete pavements. Skid resistance tests have been performed using CSR (Continuous Skid Resistance) device with fixed slip ratio equal to 13%. Three different test speed values 45, 65 and 95 km/h have been used. The obtained results lead to factorial correlation equations between developed parameters and skid resistance indices. Correlation results for uncontaminated pavement surface can be characterized by the coefficient of determination values in range between 0.55 and 0.94. The results can be used for contactless determination of pavement skid resistance in Pavement Management System.

Customer Usage Based on Pseudo Damage

2017 ◽  
Author(s):  
Craig T. Altmann ◽  
John B. Ferris
Keyword(s):  
Performance Monitoring ◽  
International Roughness Index ◽  
The Road ◽  
Road Profile ◽  
Road Roughness ◽  
Federal Highway ◽  
Roughness Index ◽  
Average Annual Daily Traffic ◽  
Road Type ◽  
Early Design Stages

Modeling customer usage in vehicle applications is critical in performing durability simulations and analysis in early design stages. Currently, customer usage is typically based on road roughness (some measure of accumulated suspension travel), but vehicle damage does not vary linearly with the road roughness. Presently, a method for calculating a pseudo damage measure is developed based on the roughness of the road profile, specifically the International Roughness Index (IRI). The IRI and pseudo damage are combined to create a new measure referred to as the road roughness-insensitive pseudo damage. The road roughness-insensitive pseudo damage measure is tested using a weighted distribution of IRI values corresponding to the principal arterial (highways and freeways) road type from the Federal Highway Administration (FHWA) Highway Performance Monitoring System (HPMS) dataset. The weighted IRI distribution is determined using the number of unique IRI occurrences in the functional road type dataset and the Average Annual Daily Traffic (AADT) provided in the FHWA HPMS data.

The Research of Road Profile Estimation Based on Acceleration Measurement

2012 ◽  
Vol 226-228 ◽  
pp. 1614-1617 ◽  
Author(s):  
Ye Chen Qin ◽  
Ji Fu Guan ◽  
Liang Gu
Keyword(s):  
Dynamic Responses ◽  
The Road ◽  
Physical Measurements ◽  
Power Spectral ◽  
Road Profile ◽  
Road Roughness ◽  
Power Spectral Densities ◽  
Profile Estimation ◽  
The Relationship ◽  
Unsprung Mass

To get the certain response of vehicle during the driving process, it’s necessary to measure the road irregularities. Existing method of gauging the roughness is based on physical measurements and the instrument is installed under the vehicle, which is expensive and will affect the vehicle dynamic responses. This paper shows an easier method to estimate the road roughness by measuring and calculating the power spectral density (PSD) of unsprung mass accelerations. This approach is possible due to the relationship between these two via a transfer function. By comparing the power spectral densities of estimated road and the standard classes, we can classify the current road classes easily. Besides, this paper also shows that it’s feasible to estimate the road profile by calculating the PSD of unsprung mass accelerations directly.

scholarly journals METROLOGICAL SUPPORT OF GEODETIC WORKS IN THE ROAD ROUGHNESS MEASURING

2021 ◽  
Vol 6 (166) ◽  
pp. 130-133
Author(s):  
H. Sarkisian ◽  
V. Tymoshevskyi ◽  
S. Urdzik
Keyword(s):  
Metrological Support ◽  
Dynamic Load ◽  
Road Maintenance ◽  
Rigid Pavement ◽  
The Road ◽  
Pavement Roughness ◽  
Road Roughness ◽  
Accuracy Of Measurements ◽  
On The Road

Most of the transport and operational indicators that directly affect the road roughness depend on the roughness of coverage. Therefore, the control and timely monitoring of the road roughness is an extremely important issue that needs the attention of road maintenance services. At monitoring of the road roughness it is most expedient to use a technique of leveling of a covering. The method of leveling the coating provides more detailed information about the coating and allows you to determine the smallest deformations on the road coating, which may be at the first stage of their development, especially at that stage of their development, and show roughness and various parameters. One of the main tasks of measurements in the process of performing geodetic works is not only to obtain the measurement result, but also to assess its reliability. The required quality of instrumental measurement can not be achieved without adhering to the principles of unity and the required accuracy of measurements, so much attention should be paid to the metrological support of geodetic works. The purpose of this article is to analyze the metrological support of geodetic works in determining the pavement roughness and substantiation of the required accuracy of measuring the non-rigid pavement roughness. On the basis of dependences for determining the coefficient of dynamic load on pavement and the correlation between the pavement roughness and the coefficient of dynamic load and on the basis of experimental data, the necessary accuracy of measuring the non-rigid pavement roughness is substantiated. Based on the analysis, it was found that the accuracy of determining the height of the irregularities should not exceed 0.5 mm, for which it is necessary to use optical or electron-optical levels.

scholarly journals Developing An Optimization Model For Pavement Maintenance Planning And Resource Allocation In Hossana Town, Ethiopia

2021 ◽  
Vol 23 (08) ◽  
pp. 824-836
Author(s):  
Tarekegn Shirko Lachore ◽  
◽  
Dagimwork Asele Manuka ◽  
Keyword(s):  
Mathematical Optimization ◽  
Cost Effective ◽  
Optimization Method ◽  
Pavement Management ◽  
Maintenance Strategy ◽  
Pavement Maintenance ◽  
The Road ◽  
Network Maintenance ◽  
Collection Data ◽  
Optimal Maintenance

Pavement Management System is designed to provide objective information and useful data for analysis so that road managers can make more consistent, cost-effective, and defensible decisions related to the preservation of a pavement network. During the process of road network maintenance and rehabilitation, road authorities strive to select an optimum maintenance strategy from a number of alternatives. Mathematical optimization models, supported by suitable data, can assist decision making about allocating funds between alternative maintenance tasks and about the size of the maintenance budget. It can be done through the analysis of costs and benefits by comparing the various maintenance alternatives with the help of an optimization method known as solver. The road segment mainly included in study was road from Hosanna Menhariya to Wachemo University and other important access roads. These roads are divided into different sections in not more than 100m length. The Study involves data collection, data analysis and the selection of optimal maintenance strategy by using a method known as Solver (Add-ins in Microsoft excel). In this study, patching was selected as possible maintenance among the other alternatives. The result of solver analysis for patching indicates that as 74,574 birr allocated for the maintenance of pavement per kilometer in different three segments under the municipality having the constraint budget of 152,018.45 birr/km. The optimized solution shows that about 20962.5 birr would be saved in one year per km with in municipality.

scholarly journals Research on the International Roughness Index Threshold of Road Rehabilitation in Metropolitan Areas: A Case Study in Taipei City

2020 ◽  
Vol 12 (24) ◽  
pp. 10536
Author(s):  
Shong-Loong Chen ◽  
Chih-Hsien Lin ◽  
Chao-Wei Tang ◽  
Liang-Pin Chu ◽  
Chiu-Kuei Cheng
Keyword(s):  
Threshold Value ◽  
City Government ◽  
International Roughness Index ◽  
The Road ◽  
Standard Scale ◽  
Road Roughness ◽  
Roughness Index ◽  
Taipei City ◽  
Road Surface Roughness ◽  
Asphalt Concrete Pavement

The International Roughness Index (IRI) is the standard scale for evaluating road roughness in many countries in the world. The Taipei City government actively promotes a Road Smoothing Project and plans to complete the rehabilitation of the main and minor roads within its jurisdiction. This study aims to detect the road surface roughness in Taipei City and recommend appropriate IRI thresholds for road rehabilitation. A total of 171 asphalt concrete pavement sections in Taipei City with a total length of 803.49 km were analyzed and compared by IRI. The longitudinal profile of the detected road sections was measured using an inertial profiler. The statistical analysis showed that the IRI value prior to road leveling was mainly distributed between 5 and 8 m/km, while the IRI value after road leveling was mainly distributed between 3 and 4.5 m/km. This confirms that the implementation of the Road Smoothing Project has a significant effect on improving road smoothness. Moreover, based on the analysis results, it is recommended that the IRI threshold value for road rehabilitation in Taipei City be set at 4.50 m/km.

Smooth Enough?: Estimated Roughness on Roads with Low International Roughness Index Values

2003 ◽  
Vol 1860 (1) ◽  
pp. 144-151 ◽  
Author(s):  
Sven Dahlstedt
Keyword(s):  
Measurement Errors ◽  
Subjective Experience ◽  
Spectral Composition ◽  
Random Errors ◽  
International Roughness Index ◽  
The Road ◽  
Road Roughness ◽  
Longitudinal Roughness ◽  
Roughness Index ◽  
Subjective Estimates

The reported investigation is one part of a project concerning methods for measurement of the longitudinal roughness of roads and the necessary accuracy. In this study the main focus was on the subjective experience of roughness on roads with low international roughness index (IRI) values, that is, fairly good roads. With the available data it was also studied how much a random error added to the IRI values would influence the correlations with the subjective estimates. The investigation was carried out as a magnitude estimation experiment. Twenty-two observers made their estimates while traveling as passengers first in a car and later in a truck. The roughness estimates were made on 45 sections along a 60-km route. Most of the stretches had an IRI roughness between 0.5 and 3.0 mm/m, with a few of up to IRI = 5.5. The reference section had an even higher roughness, IRI = 6.24, which was given the nominal subjective roughness magnitude of 100. The main results of the study were as follows: subjective roughness seems to be a linear function of roughness according to IRI within the studied roughness range; for some road sections with a nontypical spectral composition of the road roughness, it was found that the correlation between IRI and subjective roughness decreased considerably, and the simulations of random errors added to the IRI values showed that within the studied range and with the fairly large number of observations (45), random measurement errors up to at least ±0.2 IRI unit (mm/m) can be considered insignificant.

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