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Academic literature on the topic 'International Roughness Index (IRI)'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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Journal articles on the topic "International Roughness Index (IRI)"

1

Hajek, Jerry J., Thomas J. Kazmierowski, and Graham Musgrove. "Switching to International Roughness Index." Transportation Research Record: Journal of the Transportation Research Board 1643, no. 1 (January 1998): 116–24. http://dx.doi.org/10.3141/1643-15.

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The International Roughness Index (IRI) has become a well-recognized standard for measurement of pavement roughness. The main objectives of the study were to evaluate the consequences of switching to IRI roughness measurements, and to develop a procedure for switching from measuring roughness with a response-type device, used for more than 10 years, to an IRI device. The study consisted of two parts. In the first part, the repeatability and consistency of roughness measurements obtained by three different IRI-measuring systems using a 10-section calibration circuit was evaluated. In the second part, transfer functions relating IRI with a subjectively measured ride condition rating for a large pavement network consisting of asphaltic concrete, rigid, and surface-treated pavements were developed. Based on the results of the calibration circuit, the three IRI-measuring systems were proved equally capable of providing repeatable and reliable roughness measurements for network-level monitoring purposes, and their individual results correlated very well. However, because of systematic differences between the results, the IRI-measuring systems cannot be used interchangeably and without proper calibration. Based on the results obtained for the network, different transfer functions were required and developed for the four pavement types (asphaltic concrete, composite, jointed portland cement concrete, and surface-treated). IRI roughness measurements provided better prediction of the ride condition rating than the response-type roughness measurements. These results support the switch to IRI roughness measurements.

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Dahlstedt, Sven. "Smooth Enough?: Estimated Roughness on Roads with Low International Roughness Index Values." Transportation Research Record: Journal of the Transportation Research Board 1860, no. 1 (January 2003): 144–51. http://dx.doi.org/10.3141/1860-16.

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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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Setiawan, Arief, Novita Pradani, and Ferra Claudia Masoso. "PEMANFAATAN APLIKASI SMARTPHONE UNTUK MENGUKUR KEMANTAPAN PERMUKAAN JALAN BERDASARKAN INTERNATIONAL ROUGHNESS INDEX." Jurnal Transportasi 19, no. 3 (January 6, 2020): 205–14. http://dx.doi.org/10.26593/jt.v19i3.3673.205-214.

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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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Tian, Yu, Shifu Liu, Le Liu, and Peng Xiang. "Optimization of International Roughness Index Model Parameters for Sustainable Runway." Sustainability 13, no. 4 (February 18, 2021): 2184. http://dx.doi.org/10.3390/su13042184.

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Pavement roughness is a critical airport pavement characteristic that has been linked to impacts such as safety and service life. A properly defined roughness evaluation method would reduce airport operational risk, prolong the life of aircraft landing gear, and optimize the decision-making process for pavement preservation, which together positively contribute to overall airport sustainability. In this study, we optimized the parameters of the International Roughness Index (IRI) model to resolve the current poor correlation between the IRI and aircraft vibration responses in order to adapt and extend the IRI’s use for airport runway roughness evaluation. We developed and validated a virtual prototype model based on ADAMS/Aircraft software for the Boeing 737–800 and then employed the model to predict the aircraft’s dynamic responses to runway pavement roughness. By developing a frequency response function for the standard 1/4 vehicle model, we obtained frequency response distribution curves for the IRI. Based on runway roughness data, we used fast Fourier transform to implement the frequency response distribution of the aircraft. We then utilized Particle Swarm Optimization to determine more appropriate IRI model parameters rather than modifying the model itself. Our case study results indicate that the correlation coefficient for the optimized IRI model and aircraft vibration response shows a qualitative leap from that of the original IRI model.

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Cumbaa, Steven L. "Using the International Roughness Index for Profilograph Trace Reduction." Transportation Research Record: Journal of the Transportation Research Board 1536, no. 1 (January 1996): 90–93. http://dx.doi.org/10.1177/0361198196153600113.

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Current Louisiana acceptance specifications for 100 percent payment require Profile Indexes (PIs) completed pavement surface to as low as 3.0 in./mi for flexible pavements and 6.0 in./mi for rigid pavements. These acceptance specifications are currently among the most stringent in the United States. Requiring an acceptance PI value of less than 7.0 in./mi when using the California-style profilograph and the 0.2 in. blanking band is unacceptable unless the blanking band is eliminated from the procedure. Louisiana's efforts to replace the blanking-band evaluation procedure with a procedure that inputs the profile trace into the quarter-car-based International Roughness Index (IRI) model are presented. The key step in this process is the scanning and digitization of the profilo-gram before determining the IRI based on the filtered profile trace. A much better correlation exists between the rideability of the finished surface and the profilograph IRI than that of the profilograph PI. New profilograph IRI specifications are recommended to replace the existing PI specifications.

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Pawar, Prashant R., Arun Tom Mathew, and M. R. Saraf. "IRI (International Roughness Index): An Indicator Of Vehicle Response." Materials Today: Proceedings 5, no. 5 (2018): 11738–50. http://dx.doi.org/10.1016/j.matpr.2018.02.143.

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Pembuain, Ardilson, Sigit Priyanto, and Latif Budi Suparma. "Evaluasi Kemantapan Permukaan Jalan Berdasarkan International Roughness Index Pada 14 Ruas Jalan di Kota Yogyakarta." TEKNIK 39, no. 2 (March 14, 2019): 132. http://dx.doi.org/10.14710/teknik.v39i2.21459.

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Jalan yang memiliki kekasaran (roughness) permukaan yang buruk dapat menyebabkan ketidaknyamanan bagi pengguna jalan, kecelakaan lalu lintas, peningkatan beban dinamis pada permukaan jalan sehingga mempercepat proses kerusakan jalan, serta kerusakan kendaraan. Penelitian ini bertujuan untuk mengevaluasi kemantapan kondisi jalan berdasar nilai international roughness index (IRI). Evaluasi kondisi kemantapan jalan dilakukan pada 14 ruas jalan di Kota Yogyakarta, dengan perincian 4 ruas jalan arteri sekunder dan 10 ruas jalan kolektor sekunder. Data nilai kekasaran permukaan jalan (IRI) diperoleh dengan menggunakan alat NAASRA roughness meter yang mengacu pada SNI 03-3426-1994. Evaluasi kemantapan kondisi jalan dilakukan dengan membandingkan nilai IRI hasil survei dan batasan nilai IRI yang ditetapkan oleh Direktorat Jenderal Bina Marga. Hasil penelitian menunjukkan 14 ruas jalan yang dievauasi 64% dalam kondisi sedang dan 36% dalam kondisi baik. Dari ke-14 ruas jalan tersebut, ruas jalan Sisingamangaraja, Lowanu, dan Sugeng Jeroni memiliki nilai IRI tertinggi secara bururutan sehingga ketiga ruas jalan tersebut lebih diprioritaskan untuk mendapatkan penanganan

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Abed, Muataz Safaa. "Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index." Journal of Engineering 26, no. 12 (December 1, 2020): 81–94. http://dx.doi.org/10.31026/j.eng.2020.12.05.

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Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of each observed distress, the pavement condition surveys were conducted by actually walking through all the sections. Using these data, PCI was calculated utilizing Micro PAVER software. Dynatest Road Surface Profiler (RSP) was used to collect IRI data of all the sections. Using the SPSS software, linear and nonlinear regressions have been used for developing two models between PCI and IRI based on the collected data. These models have the coefficients of determination (R2) equal to 0.715 and 0.722 for linear and quadratic models. Finally, the results indicate the linear and quadratic models are acceptable to predict PCI from IRI directly.

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Du, Yuchuan, Chenglong Liu, Difei Wu, and Shengchuan Jiang. "Measurement of International Roughness Index by UsingZ-Axis Accelerometers and GPS." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/928980.

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The International Roughness Index (IRI) is a well-recognized standard in the field of pavement management. Many different types of devices can be used to measure the IRI, but these devices are mainly mounted on a full-size automobile and are complicated to operate. In addition, these devices are expensive. The development of methods for IRI measurement is a prerequisite for pavement management systems and other parts of the road management industry. Based on the quarter-car model and the vehicle vibration caused by road roughness, there is a strong correlation between the in-carZ-axis acceleration and the IRI. The variation of speed of the car during the measurement process has a large influence on IRI estimation. A measurement system equipped withZ-axis accelerometers and a GPS device was developed. Using the self-designing measurement system based on the methodology proposed in this study, we performed a small-scale field test. We used a one-wheel linear model and two-wheel model to fit the variation of theZ-axis acceleration. The test results demonstrated that the low-cost measurement system has good accuracy and could enhance the efficiency of IRI measurement.

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Abd El-Hakim, Ragaa, and Sherif El-Badawy. "International Roughness Index Prediction for Rigid Pavements: An Artificial Neural Network Application." Advanced Materials Research 723 (August 2013): 854–60. http://dx.doi.org/10.4028/www.scientific.net/amr.723.854.

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nternational Roughness Index (IRI) is an important parameter that indicates the ride quality and pavement condition. In this study, an Artificial Neural Network (ANN) model was developed to predict the IRI for Jointed Plain Concrete Pavement (JPCP) sections. The inputs for this model are: initial IRI value, pavement age, transverse cracking, percent joints spalled, flexible and rigid patching areas, total joint faulting, freezing index, and percent subgrade passing No. 200 U.S. sieve. This data was obtained from the Long Term Pavement Performance (LTPP) Program. It is the same data and inputs used for the development of the Mechanistic-Empirical pavement Design Guide (MEPDG) IRI model for JPCP. The data includes a total of 184 IRI measurements. The results of this study shows that using the same input variables, the ANN model yielded a higher prediction accuracy (coeficint of determination: R2= 0.828, and ratio of standard error of estimate (predicted) to standard deviation of the measured IRI values: Se/Sy=0.414) compared to the MEPDG model (R2= 0.584, Se/Sy=0.643). In addition, the bias in the predicted IRI values using the ANN model was significantly lower compared to the MEPDG regression model.

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Dissertations / Theses on the topic "International Roughness Index (IRI)"

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Huang, Wen Stroup-Gardiner Mary. "Transferring Alabama's smoothness specificaitons from PI-based to IRI-based." Auburn, Ala., 2006. http://hdl.handle.net/10415/1319.

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Zamora, Alvarez Eric Jose. "A Discrete Roughness Index for Longitudinal Road Profiles." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/64452.

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Engineers of off-road equipment, on-road vehicles, pavement, and tires must assess the roughness of a terrain surface for the design of their products. The International Roughness Index (IRI), a standardized means of assessing longitudinal road roughness, quantifies roughness based on the average suspension travel for a particular vehicle at a prescribed speed. The Discrete Roughness Index (DRI) developed in this work address fundamental limitations of the IRI. Specifically, the DRI is calculated for each discretely measured location along a terrain surface and is applicable to vehicles traveling at varying speeds and using parameters other than the Golden Quarter-Car on which the IRI is based. The development of the DRI begins with a consistent discretization of the terrain surface, vehicle response, and the IRI. Next the Fractional Response Coefficient is developed, the properties of which are critical in the development of the DRI. The DRI is developed and its properties are discussed through theory and simulation of the ASTM E1926-08 profile. One important property of the average DRI is that it converges to the IRI as the distance between sampled points becomes smaller, for the particular case when the Golden Quarter-Car model is simulated at 80 kph. The DRI is not an alternative to the standard IRI, therefore, but a widely applicable roughness measure of which the standard IRI is a single specialized application.
Master of Science

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Altmann, Craig Tyler. "Identification and Characterization of Damaging Road Events." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/98844.

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In the field of vehicle durability, many individuals are focusing on methods for better replicating the durability a user will experience throughout the typical design lifespan of a vehicle (e.g., 100,000 miles). To estimate user durability a means of understand the types of damaging events and driving styles of uses must be understood. The difficulty with accurately estimating customer usage is, firstly, there is a large pool of possible roads for a user to drive along, for example, there are over 4 million miles of public roads in the United States, alone [1]. In addition, while measurements of these surfaces could be collected it would be impractical for two reasons, the first is the financial and extreme time burden this would take. Second, when collecting measurements of a road surface only the current state of a road surface can be measured, thus as a road deteriorates or is repaved the measurements collected would no longer be an accurate representation of the road. It should be mentioned that even, if all of the road surfaces were measured performing simulation and analysis of all of these road surfaces would be computationally intensive. Instead, it would be beneficial if select events that account for a significant portion of the damage a vehicle experiences can be identified. These damaging events could then be used in more complex vehicle simulation models and as input and validation of proving ground and laboratory durability testing. The objective of this research is to provide a means for improved estimation of vehicle durability, specifically a means for identifying, characterizing, and grouping unique separable damaging events from a road profile measurement. In order to achieve this objective a measure that can be used to identify separate damaging events from a road profile is developed. This measure is defined as Localized Pseudo Damage (LPD), which identifies the amount of damage each individual road excitation makes to the total accumulated damage for a single load path in a vehicle system. LPD is defined as a damage density to minimize the effect of measurement spacing on the resulting metric. The developed LPD measure is causal in that the value of LPD at a location is not affected by any future locations. In addition, for a singular event (e.g., impulse or step) in the absences of other excitations, the LPD value at the singular event location is equivalent to the total pseudo damage divided by the step size at the location. Once a measure of pseudo damage density is known at multiple locations along a road profile for multiple load paths of interest, then separable damaging events can be identified. To identify separable damaging events the activity of the vehicle system must be considered because separate damaging events can only occur when a region of inactivity is present across all load paths. Subsequently, an optimization problem is formed to determine the optimal active regions to maintain. The cost function associated with the optimization problem is defined to minimize the cost (number of locations maintained in damaging events) and maximize the benefit (the amount of pseudo damage maintained). Lastly, a statistical test is developed to assess if separate damaging events can be considered to be from the same general class of events based on their damage characteristics. The developed assessment methods establish the similarity between two more separable damaging events based on application specific user defined inputs. In the development, two example similarity metrics are defined. The first similarity metric is in terms of distance and the second is in terms of likelihood (probability). The developed statistical analysis uses the current state-of-the-art in clustering algorithms to allow for multiple damaging events to be identified and grouped together.
Doctor of Philosophy
In the automotive field determining the level of damage a typical production vehicle experiences over its lifetime has always been a desirable criterion to identify. This criterion is commonly referred to as customer usage. By understanding the typical customer usage of a vehicle over the lifetime of a vehicle, automotive engineers are able to improve the design of vehicle components. The issue with defining customer usage is that there are millions of miles of roads that a customer can travel on and millions of customers that all have unique driving characteristics. While it is possible to collect measurements of these road surfaces to use in further vehicle simulations, it is not feasible both from a financial and time perspective. In addition, the simulation and analysis of all road surfaces would be computationally intensive. However, if select damaging events (regions of the road surface that excessively contribute to accumulated damage) are identified, then they can be used in more complex vehicle durability analyses with lower computational efforts. In conventional damage analysis a total amount of accumulated damage is established for a known road surface. The issue with defining damage this way is that unique events which likely contributed a large amount of the accumulated damage cannot be identified. The first objective of this research is to define damage as a function of the vehicle's location along a road surface. Then, unique and separable damaging events can be identified and separated from sections of the road that do not significantly contribute to the accumulated damage. After defining this measure, an optimization problem is developed to identify damaging events based on maximizing the benefit (amount of damage accounted for in damaging events) and minimizing the cost (amount of road surface retained). Unique and separable damaging events are identified by solving this optimization problem. While the optimization problem identifies unique, separable damaging events, it is likely that some damaging events contain similar characteristics to each other. When performing additional durability analysis, it would be beneficial to form connections between similar damaging events to allow for analysis to be performed based on groups of events. To identify damaging events with similar characteristics, a statistical analysis is developed as the last contribution of this work. By combining this analysis with current state-of-the-art clustering algorithms and user provided definitions based on applications, similar damaging events are able to be grouped together.

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Fuentes, Luis G. "Investigation of the Factors Influencing Skid Resistance and the International Friction Index." Scholar Commons, 2009. http://scholarcommons.usf.edu/etd/3920.

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This dissertation is compiled of the findings of several phases of a detailed research study that was aimed at investigating the Skid Resistance phenomenon. In the first phase of the dissertation research a study was performed to evaluate the different factors that influence frictional measurements obtained using the Dynamic Friction Tester (DFT). A temperature calibration factor that would account for temperature effects on DFT readings and IFI computations was developed. In addition, other variables that also affect the friction measurements obtained using the DFT are identified. In the next phase of the dissertation research the effect of pavement roughness on the Skid Resistance was investigated. The variation of the normal load and its nonlinear relation to SN was used to explain lower SN values measured on relatively rougher surfaces. The feasibility of using the International Roughness Index (IRI) and the Dynamic Load Coefficient (DLC) as predictors of the reduction in SN due to pavement roughness was also investigated. In the final phase of the dissertation research an in-depth investigation was carried out to better understand the principles underlying the concept of the International Friction Index (IFI), and specifically the role played by the Speed Constant ( Sp) parameter in the IFI computations. The parameter Sp dictates the speed variation of the wet friction measurements taken on a given pavement surface. The results of the current investigation suggest the revision of the procedure for computation of the Sp parameter to incorporate device specific properties. Furthermore, the incorporation of vehicle characteristics in the Sp parameter computations would help address a well known deficiency of the IFI, which is the inconsistent FR60 (predicted friction at 60 km/h) obtained from the friction values measured at two different slip speeds on the same surface. This study also showed that the modification of the Sp parameter reduces significantly the slip speed dependency of the device calibration parameters A and B. Finally, a modified IFI procedure that incorporates device specific slip conditions is presented. The modified IFI procedure showed consistently better predictive capability than the conventional ASTM procedure on all the different devices considered in this study.

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Cummings, Patrick. "Modeling the Locked-Wheel Skid Tester to Determine the Effect of Pavement Roughness on the International Friction Index." Scholar Commons, 2010. https://scholarcommons.usf.edu/etd/1604.

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Pavement roughness has been found to have an effect on the coefficient of friction measured with the Locked-Wheel Skid Tester (LWT) with measured friction decreasing as the long wave roughness of the pavement increases. However, the current pavement friction standardization model adopted by the American Society for Testing and Materials (ASTM), to compute the International Friction Index (IFI), does not account for this effect. In other words, it had been previously assumed that the IFI's speed constant (SP), which defines the gradient of the pavement friction versus speed relationship, is an invariant for any pavement with a given mean profile depth (MPD), regardless of its roughness. This study was conducted to quantify the effect of pavement roughness on the IFI's speed constant. The first phase of this study consisted of theoretical modeling of the LWT using a two-degree of freedom vibration system. The model parameters were calibrated to match the measured natural frequencies of the LWT. The calibrated model was able to predict the normal load variation during actual LWT tests to a reasonable accuracy. Furthermore, by assuming a previously developed skid number (SN) versus normal load relationship, even the friction profile of the LWT during an actual test was predicted reasonably accurately. Because the skid number (SN) versus normal load relationship had been developed previously using rigorous protocol, a new method that is more practical and convenient was prescribed in this work. This study concluded that higher pavement long-wave roughness decreases the value of the SP compared to a pavement with identical MPD but lower roughness. Finally, the magnitude of the loss of friction was found to be governed by the non-linear skid number versus normal load characteristics of a pavement.

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Ďuriš, Samuel. "Měření nerovností povrchů vozovek." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2020. http://www.nusl.cz/ntk/nusl-414305.

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The subject of the master thesis is to verify the possibility of application of geodetic methods to determine longitudinal and transverse pavement surface roughnesses. Geodetic techniques are compared to techniques specified in ČSN 73 6175. Subject of testing is absolute and relative accuracy of altitude measurement and accuracy of roughness parameter determination. As a result, the graphic interpretation of these parameters and deviations from reference values are presented in the current document. Practical use of the surveying methods is evaluated based on the application of the above mentioned techniques and the results of accuracy analysis.

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Ng, Vincent Laphang. "A Study of Deterioration in Ride Quality on Ohio's Highways." University of Toledo / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1430322756.

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Calkins, Reed. "PERFORMANCE OF THE CRACK, SEAT, AND OVERLAY REHABILITATION TECHNIQUE FOR CONCRETE PAVEMENTS IN CALIFORNIA." DigitalCommons@CalPoly, 2011. https://digitalcommons.calpoly.edu/theses/528.

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Research was performed to analyze the performance of the crack, seat, and overlay (CS&O) roadway rehabilitation technique in the Central Coast and Northern regions of California. This technique was evaluated through literature review to determine the state of practice and their conclusions. California highway sections rehabilitated using CS&O were selected for evaluation based on age and location. Pavement distresses and traffic data for these sections were collected and analyzed. Prior to beginning analysis this data was checked for errors, outliers, and omissions. The analysis consisted of checking the data for correlations among distresses and regions. The focus of this research is to develop performance prediction models for pavement distresses in CS&O sections. Using data collected from Caltrans’ Pavement Condition Reporting Software, performance models were developed based on dependent (distress) variables: alligator cracking, transverse cracking, longitudinal cracking, and International Roughness Index (IRI). And independent (explanatory) variables: age, traffic in the form of equivalent single axle load (ESAL), thickness of hot mix asphalt (HMA), thickness of Portland Cement Concrete (PCC), and cumulative traffic in the form of cumulative ESAL. Prediction models were then analyzed for preciseness and sensitivity to the variables included in each model.

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Pontes, Carlos Andre Melo. "AnÃlise da EvoluÃÃo de Defeitos de SuperfÃcie em Trechos da Malha RodoviÃria do Estado do CearÃ." Universidade Federal do CearÃ, 2012. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7704.

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Devido Ã grande predominÃncia do modal de transporte rodoviÃrio no Brasil, se faz cada vez mais necessÃrio um controle sobre as aÃÃes de manutenÃÃo e de conservaÃÃo das rodovias. Para isso, muitos ÃrgÃos rodoviÃrios adotam modernos sistemas informatizados, que Ã o caso do DER/CE, que utiliza o SIGMA (Sistema Integrado de GestÃo da ManutenÃÃo). O sistema, atravÃs do subsistema SGP (Sistema de GerÃncia de Pavimentos), possui um vasto banco de dados relativos Ã condiÃÃo das rodovias, que Ã alimentado com dados provenientes de levantamentos de campo, que trazem, periodicamente, informaÃÃes atualizadas da condiÃÃo das rodovias estaduais. Estes dados sÃo adquiridos utilizando metodologias definidas pela equipe tÃcnica do DER/CE, baseadas em procedimentos normalizados, sendo os principais: o levantamento de irregularidade longitudinal (IRI) e o Levantamento Visual ContÃnuo (LVC). O primeiro avalia o conforto ao rolamento e o segundo registra os defeitos de superfÃcie das rodovias. Esta pesquisa apresenta uma anÃlise comparativa entre dados de LVC e de IRI, avaliando a evoluÃÃo das quantidades de defeitos e do IRI e as metodologias e os equipamentos envolvidos nos levantamentos. Apresenta, ainda, uma tentativa de compreensÃo da evoluÃÃo dos parÃmetros medidos pelo LVC ao longo de oito anos. Espera-se que, com a contribuiÃÃo desta pesquisa, as metodologias e os dados relativos Ã condiÃÃo das rodovias sejam analisados considerando as limitaÃÃes encontradas e que sejam sempre adotados o equipamento e o procedimento mais apropriados.
Due to the large predominance of the transportation by highways in Brazil, it is necessary to control the actions related to maintenance and conservation of the roads. With this purpose, institutions make use of modern computational systems, such as the DER/CE, which uses the ISMA (Integrated System of Maintenance Administration). The referred system, using the subsystem PMS (Pavement Management System), has a large database related to the roads condition, filled with data provided by surveys that bring periodically up to date information of the state roads. These data are acquired by using methodologies defined by the technical staff of the DER/CE, based on the following normalized procedures: Visual Continuous Survey (LVC) and International Roughness Index Survey (IRI). The first one evaluates the comfort of the traffic rolling and the second registers the surface distresses of the roads. This research presents a comparative analysis between LVC and IRI data, evaluating the evolution of the distresses and the methodologies and equipments involved in the procedures. It is expected that, with the contribution of this research, the methodologies and road related data be analyzed considering the limitations of the equipments and procedures.

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Mohagheghi, Ali. "Effect of Pavement Condition on Traffic Crash Frequency and Severity in Virginia." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/100129.

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Previous studies show that pavement condition properties are significant factors to enhance road safety and riding experience, and pavements with low quality might have inadequate performance in terms of safety and riding experience. Pavement Management System (PMS) databases include pavement properties for each segment of the road collected by the agencies. Understanding the impact of road characteristics on crash frequency is a key step to prevent crashes. Whereas other studies analyzed the effect of different characteristics such as International Roughness Index (IRI), Rutting Depth (RD), Annual Average Daily Traffic (AADT), this thesis analyzed the effect of Critical Condition Index (CCI) on crash frequency, in addition to the other factors identified in previous studies. Other characteristics such as Percentage of Heavy Vehicles, Road Surface Condition, Road Lighting Condition, and Driver Conditions are taken into the consideration. The scope of the study is the interstate highway system in Fairfax County, Virginia. Negative Binomial, Least Square and Nominal Logistic Models were developed, showing that the CCI value is a significant factor to predict the number of crashes, and that it has different effect for different values of AADT. The result of this study is a substantial step towards developing an integrated transportation control and infrastructure management framework.
Master of Science
Many factors cause crashes in the roads. Although there is a common sense that road characteristics such as asphalt quality are important in terms of road safety, there are few studies that scientifically prove that statement. In addition, asphalt maintenance decisions making process is mainly based on cost benefit optimization, and traffic safety is not considered at the process. The purpose of this study is to analyze crashes and road characteristics related to each crash to understand the effect of those characteristics on crash frequency, and eventually, to build a model to predict the number of crashes at each part of the road. The model can help transportation agencies to have a better understanding in terms of safety consequences of their infrastructure management plans. The scope of this study is the highway interstate system in Northern Virginia. Results suggest that pavement condition has a significant impact on crash frequency.

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Books on the topic "International Roughness Index (IRI)"

1

Perera, Rohan W. Inertial Profiler Certification for Evaluation of International Roughness Index. Washington, D.C.: Transportation Research Board, 2018. http://dx.doi.org/10.17226/25207.

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Harris, Dwayne. Development of Methods and Specifications for the Use of Inertial Profilers and the International Roughness Index for Newly Constructed Pavement. Joint Transportation Research Program, 2013.

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Book chapters on the topic "International Roughness Index (IRI)"

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Surbakti, Medis, Saleh Samsuri, Ridwan Anas, and Ahmad Perwira Tarigan. "Evaluation of Road Maintenance Program Based on International Roughness Index (IRI) and Surface Distress Index (SDI)." In Lecture Notes in Civil Engineering, 764–71. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6311-3_87.

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Rahim, Ab Mughni Bin Ab, Muhammad Akram Bin Adnan, Norliana Binti Sulaiman, and Tuan Badrol Hisyam Bin Tuan Besar. "Modeling Operating Speed with Regard to Pavement Roughness Index (IRI) at Two-Lane Highway." In InCIEC 2015, 971–82. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0155-0_81.

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Chen, Chien-Ta, Ching-Tsung Hung, Chien-Cheng Chou, Ziping Chiang, and Jyh-Dong Lin. "The Predicted Model of International Roughness Index for Drainage Asphalt Pavement." In Lecture Notes in Computer Science, 937–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-87442-3_115.

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4

Eriksson, O., and T. Lundberg. "Prediction models for international roughness index and rut depth." In Pavement and Asset Management, 225–30. CRC Press, 2019. http://dx.doi.org/10.1201/9780429264702-27.

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Conference papers on the topic "International Roughness Index (IRI)"

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Zhang, Wenjin, and Ming Wang. "International Roughness Index (IRI) measurement using Hilbert-Huang transform." In Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII, edited by Peter J. Shull. SPIE, 2018. http://dx.doi.org/10.1117/12.2297211.

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Chang, Jia-Ruey, Yung-Shuen Su, Tsun-Cheng Huang, Shih-Chung Kang, and Shang-Hsien Hsieh. "Measurement of the International Roughness Index (IRI) Using an Autonomous Robot (P3-AT)." In 26th International Symposium on Automation and Robotics in Construction. International Association for Automation and Robotics in Construction (IAARC), 2009. http://dx.doi.org/10.22260/isarc2009/0052.

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3

Altmann, Craig T., and John B. Ferris. "Customer Usage Based on Pseudo Damage." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5270.

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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.

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4

Zhao, Zhizhong, and Zhongyin Guo. "Prediction of Asphalt Pavement International Roughness Index (IRI) by Combined Approach of Empirical Regression and Markov." In Fourth International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2013. http://dx.doi.org/10.1061/9780784413159.307.

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Pérez Acebo, Heriberto, and Hernán Gonzalo-Orden. "IRI performance models for recently constructed low and medium-traffic two lane roads of the province of Biscay." In CIT2016. Congreso de Ingeniería del Transporte. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.4108.

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Reliable pavement prediction models are needed for pavement management systems (PMS), as they are a key component to forecast future conditions of the pavement and to prioritize maintenance, rehabilitation and reconstruction strategies. The International Roughness Index (IRI) is the most used parameter worldwide for calibrating pavement roughness and measures reasonably the ride comfort perceived by occupants of passenger cars. The Regional Government of Biscay also collects this value on the road network under its control These surveys are carried out regularly in the XXI century. Several IRI performance models have been proposed by different authors and administrations, varying greatly in their comprehensiveness, the ability to predict performance with accurancy and input data requirements. The aim of this paper is to develop a roughness performance model for Biscay's roads, based on availablbe IRI data, taking into account heavy traffic volume and the age of pavement. Local characteristics as climate conditions and average rainfall are not considered. IRI performance models have been suggested for regional two lane highways with low and medium heavy traffic constructed in the last 20 years in the province of Biscay, with no treatments during their life. They can be applied for flexible pavements, but no logical coherent results have been concluded for semi-rigid pavements.DOI: http://dx.doi.org/10.4995/CIT2016.2016.4108

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"IRI 2020 Index." In 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI). IEEE, 2020. http://dx.doi.org/10.1109/iri49571.2020.00077.

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"IEEE IRI 2014 author index." In 2014 IEEE International Conference on Information Reuse and Integration (IRI). IEEE, 2014. http://dx.doi.org/10.1109/iri.2014.7051862.

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Rathour, Vidhiwar, Kashu Yamakazi, and T. Le. "Roughness Index and Roughness Distance for Benchmarking Medical Segmentation." In 8th International Conference on Bioimaging. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010335500820093.

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"Author index." In 2006 IEEE International Conference on Information Reuse & Integration. IEEE, 2006. http://dx.doi.org/10.1109/iri.2006.252485.

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"Author Index." In 2007 IEEE International Conference on Information Reuse and Integration. IEEE, 2007. http://dx.doi.org/10.1109/iri.2007.4296586.

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Reports on the topic "International Roughness Index (IRI)"

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Lee, Hyung, William Vavrik, and Hesham Abdualla. Development of IDOT’s Proposed Smoothness Specification Based on the International Roughness Index. Illinois Center for Transportation, September 2020. http://dx.doi.org/10.36501/0197-9191/20-015.

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Harris, Dwayne. Development of Methods and Specifications for the Use of Inertial Profilers and the International Roughness Index for Newly Constructed Pavement. Purdue University, October 2013. http://dx.doi.org/10.5703/1288284315211.

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