scholarly journals Measurement of International Roughness Index by UsingZ-Axis Accelerometers and GPS

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Yuchuan Du ◽  
Chenglong Liu ◽  
Difei Wu ◽  
Shengchuan Jiang
Keyword(s):  
Measurement System ◽  
Low Cost ◽  
Pavement Management ◽  
Small Scale ◽  
International Roughness Index ◽  
The Road ◽  
Quarter Car Model ◽  
Pavement Management Systems ◽  
Roughness Index ◽  
Wheel Model

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.

Full-Car Roughness Index as Summary Roughness Statistic

2005 ◽  
Vol 1905 (1) ◽  
pp. 148-156 ◽  
Author(s):  
Renato A. C. Capuruço ◽  
Tarek Hegazy ◽  
Susan L. Tighe ◽  
Sameh Zaghloul
Keyword(s):  
Mechanical Response ◽  
Pavement Management ◽  
Ride Quality ◽  
Management Decision ◽  
International Roughness Index ◽  
Front Suspension ◽  
Car Model ◽  
Roughness Index ◽  
Wheel Model ◽  
Management Decision Making

The international roughness index (IRI) and the half-car roughness index (HRI) are the two commonly used roughness indices for pavement management, decision making, prioritization, budgeting, and planning. This work presents a new statistic, termed the full-car roughness index (FRI), for calculation of roughness from longitudinal pavement profiles. FRI is calculated from a single, equivalent profile that is a composite of four corner profiles based on both civil and mechanical engineering principles. More specifically, the full-car (four-wheel) model combines the rear and front suspension systems through an interdependent relation of motion with the longitudinal axle. To validate this model, the FRI values for different pavement sections are determined for sampling roughness measurements from several states and provinces. Then, the behavior of FRI is compared with that of IRI and HRI. The methodology of assessment uses a Monte Carlo simulation for calibration and validation of the index. Correlations derived from this sensitivity analysis on the basis of regression analysis arrive at a conversion chart to propose conversion values from these indices to FRIs. Overall, this paper suggests that the mechanical response of the proposed full-car model is more representative of the characteristics of a real vehicle than the response of a quarter- or half-car model. The results also indicate that FRI is less sensitive to the governing factors that account for the quarter-car simulation and thus provides an index that is unique, insightful, and more effective in the characterization of ride quality.

Evaluation of low-cost consumer-level mobile phone technology for measuring international roughness index (IRI) values

2014 ◽  
Vol 41 (9) ◽  
pp. 819-827 ◽  
Author(s):  
Trevor Hanson ◽  
Coady Cameron ◽  
Eric Hildebrand
Keyword(s):  
Low Cost ◽  
Pavement Management ◽  
Vehicle Speed ◽  
Accelerometer Data ◽  
International Roughness Index ◽  
Mobile Phone Technology ◽  
Vehicle Type ◽  
Roughness Index ◽  
Class 1 ◽  
Test Scenarios

International roughness index (IRI) values were calculated from multi-step processing of accelerometer data collected using three smartphone devices in three consumer vehicles under 11 test scenarios on a 1000 m stretch of secondary highway in New Brunswick. These data were compared to IRI data from a Class 1 inertial profiler averaged over 1000 m (2.60 m/km, std. dev. = 0.029). The combinations of factors producing average IRI values closest to Class 1 inertial profiler were the compact car, Galaxy SIII, windshield mount, at 80 km/h (2.58 m/km, std. dev. = 0.075) and the SUV, iPhone 5, windshield mount, at 50 km/h (2.63 m/km, std. dev. = 0.054). Changes in device type, vehicle type, and mounting arrangement significantly impacted IRI variance, while vehicle speed (50 km/h and 80 km/h) did not. The development of correction factors and analysis automation could make these devices a low-cost option for real-time network-level pavement management.

scholarly journals Study of Pavement Condition Index (PCI) relationship with International Roughness Index (IRI) on Flexible Pavement.

2019 ◽  
Vol 258 ◽  
pp. 03019 ◽  
Author(s):  
Rijal Psalmen Hasibuan ◽  
Medis Sejahtera Surbakti
Keyword(s):  
Condition Index ◽  
International Roughness Index ◽  
Pavement Condition ◽  
The Road ◽  
Roughness Index ◽  
Pavement Condition Index ◽  
Local Roads ◽  
Actual Field ◽  
Two Parameters

Road is an infrastructure that built to support the movement of the vehicle from one place to another for different purposes. Today, it is often found damage to road infrastructure, both local roads, and arterial roads. Therefore, to keep the pavement condition to remain reliable, in Indonesia has a periodic program by conducting an objective functional inspection of roads regulated by Bina Marga using the International Roughness Index (IRI). However, the IRI examination is not sufficient to represent the actual field condition; it is necessary to perform subjective functional examination by appraising the road one of them is Pavement Condition Index (PCI, ASTM D 6433). This method has been widely applied in some countries because it has many advantages. However, to do this inspection requires considerable cost, then there needs to be a model to get the relationship between these two parameters of the road. The selected case study was arterial road segment in Medan City, that is in Medan inner ring road. Based on the results of the analysis, there is a difference between the functional conditions of PCI and IRI. The equation derived from these two parameters is by exponential regression equation, with equation IRI = 16.07exp-0.26PCI. with R2 of 59% with correlation coefficient value (r) of -0.768. The value of R2 indicates that PCI gives a strong influence on IRI value.

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.

scholarly journals Assessment of the road based on PCI and IRI roadroid measurement

2018 ◽  
Vol 195 ◽  
pp. 04006 ◽  
Author(s):  
Donny A. Putra ◽  
Mamok Suprapto
Keyword(s):  
Good Condition ◽  
Visual Assessment ◽  
Condition Index ◽  
Assessment Method ◽  
Visual Methods ◽  
International Roughness Index ◽  
Pavement Condition ◽  
The Road ◽  
Roughness Index ◽  
Pavement Condition Index

There are two methods of road assessment, ie, visually and using tools. Visual assessment makes use of the PCI (Pavement Condition Index), while assessment with the Roadroid app can be used to obtain the value of IRI (International Roughness Index) with less cost. Functional assessment of roads in the field more use of visual methods. This method is influenced by the subjectivity of surveyors. Therefore, the assessment using the visual method should be correlated with the assessment method using tools, in order to reduce the subjectivity of road assessment. The research location used is Magetan District Road consisting of 5 road segments. The result shows that the r road assessment using the PCI method has a very good condition, and using IRI Roadroid has a Medium condition. There is a negative (r) correlation between PCI and IRI Roadroid, valued at -0.23. The negative correlation shows that both judgments reversed. Comparison of PCI assessment with IRI Roadroid has a low correlation value and with ttest, yields no comparison of correlation. This result is because the PCI and IRI equally assess the pavement, using different methods.

scholarly journals TINJAUAN KONDISI PERKERASAN JALAN DENGAN KOMBINASI NILAI INTERNATIONAL ROUGHNESS INDEX (IRI) DAN SURFACE DISTRESS INDEX (SDI) PADA JALAN TAKENGON – BLANGKEJEREN

2018 ◽  
Vol 1 (3) ◽  
pp. 543-552
Author(s):  
Baihaqi Baihaqi ◽  
Sofyan M. Saleh ◽  
Renni Anggraini
Keyword(s):  
Road Surface ◽  
Road Segment ◽  
International Roughness Index ◽  
Damage Level ◽  
The Road ◽  
Road Pavement ◽  
Roughness Index ◽  
Surface Distress ◽  
Observation Method ◽  
Pavement Damage

Abstract: Takengon - Blangkejeren road is one of the cross national roads connecting Central Aceh Regency with Gayo Lues Regency. This road is in the mountainous terrain and often passed by heavy loaded vehicles so that often damaged. To overcome the frequent damage to this road segment, it is necessary to conduct a research on road pavement damage. The purpose of this research is to know the condition of road damage based on the combination of International Roughness Index (IRI) and Surface Distress Index (SDI). This study uses direct observation method in the field by conducting a visual survey of road pavement conditions. The result of the research shows that the total damage level of road surface is 30,54% while the road surface is not damaged by 69,46% from total of road that become research object, that is 12,63 Km divided into 6 road segment. For the overall condition of roads reviewed 45.02% good, 45.81% medium, 6.87% lightly damaged, 2.29% heavily damaged.Abstrak: Ruas jalan Takengon – Blangkejeren merupakan salah satu ruas jalan nasional lintas tengah yang menghubungkan Kabupaten Aceh Tengah dengan Kabupaten Gayo Lues. Jalan ini berada pada medan pegunungan dan sering dilalui kendaraan dengan beban yang berat sehingga sering mengalami kerusakan. Untuk mengatasi kerusakan yang sering terjadi pada ruas jalan ini perlu diadakan suatu penelitian mengenai jenis kerusakan perkerasan jalan. Tujuan dari penelitian ini adalah untuk mengetahui kondisi kerusakan jalan berdasarkan kombinasi nilai International Roughness Index (IRI) dan Surface Distress Index (SDI). Penelitian ini menggunakan metode pengamatan langsung dilapangan dengan melakukan survey secara visual terhadap kondisi perkerasan jalan. Dari hasil penelitian diperoleh tingkat kerusakan keseluruhan permukaan jalan adalah sebesar 30,54% sedangkan permukaan jalan yang tidak mengalami kerusakan sebesar 69,46 % dari total panjang jalan yang menjadi objek penelitian, yaitu 12,63 Km yang dibagi menjadi 6 buah segmen jalan. Untuk kondisi keseluruhan jalan yang ditinjau 45,02 % baik, 45,81 % sedang, 6,87 % rusak ringan, 2,29 % rusak berat.

scholarly journals Analysis of Vehicle Vibrations – New Approach to Rating Pavement Condition of Urban Roads

2012 ◽  
Vol 23 (6) ◽  
pp. 485-494 ◽  
Author(s):  
Stjepan Lakušić ◽  
Davor Brčić ◽  
Višnja Tkalčević Lakušić
Keyword(s):  
Surface Roughness ◽  
Ride Comfort ◽  
Road Traffic ◽  
Heavy Traffic ◽  
Pavement Management ◽  
International Roughness Index ◽  
New Approach ◽  
Pavement Condition ◽  
Roughness Index ◽  
Road Surface Roughness

Urban road infrastructure is daily burdened by heavy traffic volume. Pavement structure roughness observations are significantly more difficult in urban agglomerations than on roads in unpopulated areas. Roughness, expressed by IRI (International Roughness Index), directly affects the quality and safety of road traffic. Within the framework of the pavement management in relation to safety and the achievement of the best possible ride comfort, it is very important to foresee when a road should be reconstructed. The method for quality evaluations of safety and ride comfort on urban roads presented in this paper is based on vehicle vibrations measurements. In the article, measuring of vehicle vibrations was performed on the main urban roads in Zagreb (Croatia). Measurements covered roads with different pavement surface roughness. This method can be simply and very easily used in pavement management aimed at achieving road safety and better ride comfort. The results of measurements according to this method could be used by traffic and civil engineering experts as an indication for the roads that require reconstruction or maintenance. KEY WORDS: urban roads, traffic flow, safety, vehicle vibrations, road surface roughness (IRI)

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.

Optimization of data collection needs for manual and automated network-level pavement condition ratings based on transverse variability and neural networks

2007 ◽  
Vol 34 (2) ◽  
pp. 139-146 ◽  
Author(s):  
Ahmed Shalaby ◽  
Alan Reggin
Keyword(s):  
Back Propagation ◽  
Predictive Ability ◽  
Kappa Coefficient ◽  
Pavement Management ◽  
Back Propagation Algorithm ◽  
International Roughness Index ◽  
Pavement Condition ◽  
Roughness Index ◽  
Transverse Variability ◽  
Data Elements

The paper deals with two approaches to optimizing pavement condition surveys for the urban pavement network of the City of Winnipeg, Manitoba. First, a nonparametric statistical test was applied to assess the transverse variability of the data. The test compared the ratings for one lane with those of all lanes of each segment. The test concluded that the medians of the two groups are equal at a 92% confidence interval and that there are observed biases in the data. The bias can be eliminated if the surveyed lane is selected randomly. The second approach was to predict visual survey scores from automated (laser-based) measurement of rut depth and international roughness index (IRI). A resilient back-propagation algorithm was selected, and the Kappa coefficient was used to examine the strength of the agreement. The results showed that only moderate agreement was achieved and that additional data elements are required to improve the predictive ability of the model.Key words: international roughness index (IRI), rutting, cracking, spalling, pavement management system (PMS), Kappa coefficient, distress surveys.

International Roughness Index Prediction Model for Thin Hot Mix Asphalt Overlay Treatment of Flexible Pavements

2018 ◽  
Vol 2672 (40) ◽  
pp. 7-13 ◽  
Author(s):  
Jinsong Qian ◽  
Chen Jin ◽  
Jiake Zhang ◽  
Jianming Ling ◽  
Chao Sun
Keyword(s):  
Low Temperature ◽  
Prediction Model ◽  
Temperature Region ◽  
Hot Mix Asphalt ◽  
Pavement Management ◽  
Pavement Performance ◽  
International Roughness Index ◽  
Medium Temperature ◽  
Asphalt Overlay ◽  
Roughness Index

Pavement performance prediction after maintenance and rehabilitation is important to pavement management. A two-parameter exponential international roughness index (IRI) regression model for thin hot mix asphalt overlay was developed based on information from the U.S. Long Term Pavement Performance (LTPP) database. The model influence parameters α and β, which represent the initial IRI as the thin overlay completion and shape factor of IRI deterioration curve, were statistically analyzed. The results suggested that the IRI deterioration trends in high-temperature and low-temperature regions are different. This is because β was mainly affected by the structural strength and equivalent single axle loads in the high and medium temperature region and mainly affected by the average annual precipitation in low temperature region. In-situ data from LTPP database was used to verify the IRI prediction model, and it was found that the predicted IRI and measured IRI exhibited similar trends.

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