Evaluation of Relationship Between Profilograph and Profile-Based Roughness Indexes

The relationship between the profilograph profile index (PI) and the international roughness index (IRI) is evaluated. To accomplish this evaluation, profile data taken on 48 overlaid test sections were used in profilograph simulations to predict the profilograph response to the measured profiles. The PIs determined were then correlated with IRIs computed from the profile data to evaluate relationships between these roughness statistics. The results show that the PI based on the null blanking band is more strongly related to the IRI than the corresponding index determined using the 5-mm blanking band. In view of the general acceptance of the IRI as a statistic for establishing surface smoothness based on profiles, the results suggest that a profilograph specification based on the null blanking band is preferable to a similar specification based on the 5-mm blanking band, which may mask certain components of roughness that are otherwise picked up if no blanking band is used.

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PEMANFAATAN APLIKASI SMARTPHONE UNTUK MENGUKUR KEMANTAPAN PERMUKAAN JALAN BERDASARKAN INTERNATIONAL ROUGHNESS INDEX

Jurnal Transportasi ◽

10.26593/jt.v19i3.3673.205-214 ◽

2020 ◽

Vol 19 (3) ◽

pp. 205-214

Author(s):

Arief Setiawan ◽

Novita Pradani ◽

Ferra Claudia Masoso

Keyword(s):

Segment Length ◽

Android Application ◽

Smartphone Applications ◽

International Roughness Index ◽

Surface Conditions ◽

Software Applications ◽

Measurement Results ◽

Roughness Index ◽

Technological Developments ◽

The Relationship

Abstract An assessment of road surface conditions is needed to determine an appropriate road evaluation program. One of the parameters used is the International Roughness Index or IRI. Currently, technological developments encourage the use of smartphone applications as a tool to determine the value of IRI. Comparisons between IRIs obtained using tools, such as roughometers, and IRIs obtained from software applications have not been made. The purpose of this study was to analyze the relationship between the results of the measurement of the roughometer and the results of the Android application Roadbump Pro. This research was carried out on the Sam Ratulangi Road in Palu City, with a segment length of 600 meters and analyzed per 100 meters. The results of this study indicate that smartphone applications provide good IRI measurement results, so they can be used in road stability assessments. In addition, the type of survey vehicle did not have a significant effect on IRI measurements. Keywords: smartphone, International Roughness Index, roughometer, Roadbump, road stability Abstrak Penilaian kondisi permukaan jalan diperlukan untuk menentukan program evaluasi jalan yang tepat. Salah satu parameter yang digunakan adalah International Roughness Index atau IRI. Saat ini, perkembangan teknologi mendorong penggunaan aplikasi smartphone sebagai alat bantu untuk menentukan nilai IRI. Perbandingan antara IRI yang diperoleh dengan menggunakan alat bantu, seperti roughometer, dan IRI yang diperoleh dari aplikasi perangkat lunak belum dilakukan. Tujuan penelitian ini adalah menganalisis hubungan antara hasil pengukuran alat roughometer dan hasil aplikasi android Roadbump Pro. Penelitian ini dilakukan di ruas Jalan Sam Ratulangi di Kota Palu, dengan panjang segmen 600 meter dan dianalisis per 100 meter. Hasil penelitian ini menunjukkan bahwa aplikasi smartphone memberikan hasil pengukuran IRI yang baik, sehingga dapat digunakan dalam penilaian kemantapan jalan. Selain itu, jenis kendaraan survei tidak memberikan pengaruh yang signifikan terhadap pengukuran IRI. Kata-kata kunci: smartphone, International Roughness Index, roughometer, Roadbump, kemantapan jalan

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Assessment of the relationship between the international roughness index and dynamic loading of heavy vehicles

International Journal of Pavement Engineering ◽

10.1080/10298436.2015.1121780 ◽

2015 ◽

Vol 18 (8) ◽

pp. 693-701 ◽

Cited By ~ 13

Author(s):

Jean-Pascal Bilodeau ◽

Louis Gagnon ◽

Guy Doré

Keyword(s):

Dynamic Loading ◽

Heavy Vehicles ◽

International Roughness Index ◽

Roughness Index ◽

The Relationship

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Roughness prediction models using pavement surface distresses in different Canadian climatic regions

Canadian Journal of Civil Engineering ◽

10.1139/cjce-2018-0697 ◽

2019 ◽

Vol 46 (10) ◽

pp. 934-940 ◽

Cited By ~ 1

Author(s):

Graeme Patrick ◽

Haithem Soliman

Keyword(s):

Prediction Models ◽

Climatic Conditions ◽

International Roughness Index ◽

Climatic Regions ◽

Pavement Surface ◽

Roughness Index ◽

Roughness Prediction ◽

Surface Distress ◽

The Relationship

The correlation between the international roughness index (IRI) and distress is inherent, as roughness is a function of both the changes in elevation of the distress-free pavement surface and the changes in elevation due to existing surface distress. In this way, a relationship between existing surface distress and IRI may be developed. However, the susceptibility of pavement to various types of surface distress is affected by many factors, including climatic conditions. A model that relates pavement surface distress to IRI for Canada needs to account for climatic conditions in different locations. This paper investigates the relationship between pavement surface distresses and IRI for different climatic conditions in Canada using historical data collected at numerous pavement test section locations sourced from the Long-Term Pavement Performance program database. Developed models were calibrated then validated and found to be statistically significant.

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Effects of the International Roughness Index and Rut Depth on Crash Rates

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198118781137 ◽

2018 ◽

Vol 2672 (40) ◽

pp. 418-429 ◽

Cited By ~ 3

Author(s):

Michael Mamlouk ◽

Mounica Vinayakamurthy ◽

B. Shane Underwood ◽

Kamil E. Kaloush

Keyword(s):

Pavement Management ◽

Ride Quality ◽

International Roughness Index ◽

Accident Rate ◽

Crash Data ◽

Crash Rates ◽

Vehicle Operation ◽

Roughness Index ◽

Pavement Distresses ◽

The Relationship

Pavement distresses directly affect ride quality, and indirectly contribute to driver distraction, vehicle operation, and accidents. In this study, analysis was performed on highways in the states of Arizona, North Carolina, and Maryland to investigate the relationship between accident rate and pavement ride quality (roughness) and rut depth. Two main types of data were collected: crash data from the accident records and International Roughness Index (IRI) and rut depth data from the pavement management system database in each state. Crash rates were calculated using the U.S. Department of Transportation method, which is the number of accidents per 100 million vehicle-miles of travel. Sigmoidal function regression analysis was performed to study the relationship between crash rate and both IRI and rut depth. In all cases, the crash rate did not show substantial increases until an IRI value of 210 inches/mile or a critical rut depth of 0.4 inches. When the IRI or rut depth increased above these values the crash rate increased. This is a key conclusion that provides empirically derived thresholds for IRI and rut depth to reducing the accident rate.

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Methodology for Detection of Defect Locations in Pavement Profile

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198105190500115 ◽

2005 ◽

Vol 1905 (1) ◽

pp. 140-147 ◽

Cited By ~ 1

Author(s):

Shubham Rawool ◽

Emmanuel G. Fernando

Keyword(s):

Fourier Transform ◽

Transfer Function ◽

Gain Function ◽

Profile Data ◽

International Roughness Index ◽

Road Users ◽

Roughness Index ◽

Transportation Agencies ◽

Detection Of Defects

Pavement smoothness has become a standard measure of pavement quality. Transportation agencies strive to build and maintain smoother pavements. Road users generally perceive the quality of a pavement on the basis of how well it rides, which is severely affected by the presence of defects (bumps or dips) in the pavement profile. Defects are corrected according to the smoothness specifications prescribed by respective agencies. The effectiveness of any method used to identify defect locations depends on the decrease in roughness obtained on correction of the defects. Following this line of thought, this paper presents a method for the detection of defects based on a comparison of the original profile with a target or a desired profile. The proposed methodology is based on the international roughness index (IRI) gain function for the identification of defect locations to improve smoothness in pavements. This method uses the discrete Fourier transform to help identify defect locations on the basis of deviations of the original profile from the target or the smoothened profile. Areas with defects have a higher deviation from the smoothened profile than areas without defects. This method also estimates the contribution of each defect to roughness. Roughness statistics, such as the IRI and the present serviceability index, are used in the proposed approach to determine the severity of each defect. In addition, the use of a quarter-truck transfer function instead of the IRI gain function is demonstrated to illustrate consideration of dynamic load criteria for the detection of defects. The approach is illustrated through the use of profile data collected for in-service pavement sections.

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Examining the relationship between two road performance indicators: Pavement condition index and international roughness index

Transportation Geotechnics ◽

10.1016/j.trgeo.2020.100441 ◽

2021 ◽

Vol 26 ◽

pp. 100441

Author(s):

S. Madeh Piryonesi ◽

Tamer E. El-Diraby

Keyword(s):

Performance Indicators ◽

Condition Index ◽

International Roughness Index ◽

Pavement Condition ◽

Roughness Index ◽

Pavement Condition Index ◽

Road Performance ◽

The Relationship

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Roadway-Vehicle Interaction, Physical Indexes, and Human Judgment of Ride Quality

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1570-07 ◽

1997 ◽

Vol 1570 (1) ◽

pp. 55-59 ◽

Cited By ~ 4

Author(s):

Chiu Liu ◽

Robert Herman

Keyword(s):

Ride Quality ◽

Physical Parameters ◽

Human Judgment ◽

International Roughness Index ◽

Moving Vehicle ◽

Roughness Index ◽

Static Profile ◽

Relationship Of ◽

The Relationship ◽

Analytical Expressions

Present serviceability index (PSI) modeling has been an important subject for decades. Other dynamic indexes characterizing a roadway such as the international roughness index (IRI), averaged rectified slope (ARS), and averaged rectified speed (ARV) have been proposed and studied. However, the roles played by these indexes in the interaction between road, vehicle, and human ratings have not been made clear. A unified physical model linking the static profile of a roadway and the dynamic response of a vehicle to the profile to the serviceability index of the roadway is presented here. Analytical expressions for jerk index, acceleration index, ARV, ARS, and IRI are derived from the developed model in terms of the physical parameters for roadways and the dynamic characteristics of a vehicle. Then a linear relation between the PSI and the logarithm of the jerk index is proposed. Using the jerk index computed from field profile data, the linear functional form for the PSI is verified, and regression R2 values higher than 0.94 are obtained for various types of pavements. The same analysis is performed for other dynamic indexes, and the R2 values are found to be approximately in the range from 0.70 to 0.80. These results indicate that the theoretical model correctly predicts and explains the human rating of ride quality and that the jerk experienced by raters in a moving vehicle dictates the ratings. Moreover, the relationship of the static parameters of roadway profiles with human ratings is discussed using the conventional approach.

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