scholarly journals Development of a Relationship between Pavement Condition Index and International Roughness Index in Rural Road Network

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Sasan Adeli ◽  
Vahid Najafi moghaddam Gilani ◽  
Mohammad Kashani Novin ◽  
Ehsan Motesharei ◽  
Reza Salehfard
Keyword(s):  
Road Network ◽  
Condition Index ◽  
Road Surface ◽  
International Roughness Index ◽  
Pavement Condition ◽  
Exponential Regression ◽  
Rural Road ◽  
Proposed Model ◽  
Pavement Condition Index ◽  
Road Surface Roughness

The main objective of this paper was to investigate the relationship between PCI and IRI values of the rural road network. To this end, 6000 pavement sections of the rural road network in Iran were selected. Road surface images and roughness linear profiles were collected using an automated car to calculate PCI and IRI, respectively. Three exponential regression models were developed and validated in three different IRI intervals. Analysis of the results indicated that exponential regression was the best model to relate IRI and PCI. In these models, R2 values were found to be acceptable, equal to 0.75, 0.76, and 0.59 for roads with good, fair, and very poor qualities, respectively, indicating a good relationship between IRI and PCI. Moreover, validation results showed that the model had a high accuracy. Also, the relation between IRI and PCI became weaker as a result of increasing the level of road surface roughness, which can be caused by the increase in the number and severity of failures. Furthermore, two failures of rail R.C. and rutting were rarely observed in the studied roads. Therefore, the proposed model is more applicable for roads without the mentioned failures and asphalt-pavement rural road network.

scholarly journals STUDI KERUSAKAN JALAN DITINJAU DARI FAKTOR SETEMPAT (STUDI KASUS RUAS JALAN BLANGKEJEREN – LAWE AUNAN)

2018 ◽  
Vol 1 (3) ◽  
pp. 667-678
Author(s):  
Mulyadi Mulyadi ◽  
Muhammad Isya ◽  
Sofyan M. Saleh
Keyword(s):  
Traffic Safety ◽  
Condition Index ◽  
Road Surface ◽  
Primary Data ◽  
Soil Conditions ◽  
Pavement Condition ◽  
Local Factors ◽  
The Road ◽  
Pavement Condition Index ◽  
On The Road

Abstract: Blangkejeren - Lawe Aunan road conditions overall is on the slopes of the mountains which is strongly influenced by local environmental factors such as drainage, topography, soil conditions, material conditions and vehicle load conditions across the road. It should be noted in order to avoid a decrease in the road quality due to road surface damage that can affect the traffic safety, comfort and smoothness.. Therefore, it is necessary to study the evaluation of the condition of the damaged road surface and the local factors that affect the damage in order to avoid a decrease in the roads quality. This study took place on Blangkejeren - Lawe Aunan roads started from Sta. 529 + 700 - Sta. 535 + 206. Generally, the condition of roads in this segment were found damage that disturb the comfort, smoothness and safety of the roads users. In this study, the primary data obtained by actual surveys in the form of data field length, width, area, and depth of each type of damage as well as local factors that lead to such damage. Actual field surveys conducted along the 5.506 km, with the distance interval of each segment is 100 m. The secondary data obtained from the relevant institutions and other materials related to this research. This study analyzed the PCI method (Pavement Condition Index) to obtain the level of damage in order to know how to handle, while for the identification of the damage done by observation factors descriptively appropriate observation in the field such as the number of damage points. The results of this study found that the type of damage caused to roads is damage to the cover layer, a hole, and curly. This type of damage that commonly occurs on the road Blangkejeren - Lawe Aunan is damage to the edges with a percentage of 87.30%. The local factors that greatly affect drainage on the percentage of damage is 62.00%. PCI average value is 13.47 which indicates a very bad condition (very poor) and requires maintenance or improvement of reconstruction.Abstrak: Kondisi jalan Blangkejeren – Lawe Aunan secara keseluruhan berada di lereng pegunungan sangat dipengaruhi oleh faktor lingkungan setempat seperti drainase, topografi, kondisi tanah, kondisi material dan kondisi beban kendaraan yang melintasi jalan tersebut. Hal ini perlu diperhatikan agar tidak terjadi penurunan kualitas jalan akibat kerusakan permukaan jalan sehingga dapat mempengaruhi keamanan, kenyamanan, dan kelancaran dalam berlalu lintas. Oleh karena itu, perlu dilakukan penelitian evaluasi terhadap kondisi permukaan jalan yang mengalami kerusakan serta faktor setempat yang mempengaruhi kerusakan tersebut agar tidak terjadi penurunan kualitas jalan. Penelitian ini mengambil lokasi di ruas jalan Blangkejeren – Lawe Aunan yang dimulai dari Sta. 529+700 - Sta. 535+206. Umumnya kondisi ruas jalan pada segmen ini banyak ditemukan kerusakan-kerusakan yang dapat mengganggu kenyamanan, kelancaran, dan keamanan pengguna jalan. Dalam penelitian ini data primer diperoleh dengan melakukan survei aktual lapangan yaitu berupa data panjang, lebar, luasan, dan kedalaman tiap jenis kerusakan serta faktor setempat yang mengakibatkan kerusakan tersebut. Survei aktual lapangan dilakukan sepanjang 5,506 km, dengan jarak interval setiap segmen adalah 100 m. Adapun data sekunder diperoleh dari lembaga terkait dan bahan lainnya yang berhubungan dengan penelitian ini. Penelitian ini dianalisis dengan metode PCI (Pavement Condition Index) untuk mendapatkan tingkat kerusakan agar diketahui cara penanganannya, sedangkan untuk identifikasi faktor kerusakannya dilakukan dengan pengamatan secara diskriptif sesuai hasil pengamatan di lapangan berupa jumlah titik kerusakan. Hasil penelitian ini didapatkan bahwa jenis kerusakan yang terjadi pada ruas jalan adalah kerusakan lapisan penutup, lubang, dan keriting. Jenis kerusakan yang umum terjadi pada ruas jalan Blangkejeren – Lawe Aunan adalah kerusakan tepi dengan persentase 87,30 %. Faktor setempat yang sangat mempengaruhi kerusakan adalah drainase dengan persentase 62,00%. Nilai PCI rata-rata yaitu 13,47 yang menunjukkan kondisi sangat buruk (very poor) dan memerlukan pemeliharaan peningkatan atau rekonstruksi.

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.

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 ANALISIS TINGKAT KERUSAKAN JALAN DAN PENGARUNYA TERHADAP KECEPATAN KENDARAAN (STUDI KASUS: JALAN BLANG BINTANG LAMA DAN JALAN TEUNGKU HASAN DIBAKOI)

2018 ◽  
Vol 1 (3) ◽  
pp. 617-626
Author(s):  
Intan Wirnanda ◽  
Renni Anggraini ◽  
Muhammad Isya
Keyword(s):  
Regression Analysis ◽  
Condition Index ◽  
Road Surface ◽  
Road Segment ◽  
Primary Data ◽  
Vehicle Speed ◽  
Pavement Condition ◽  
The Road ◽  
Road Condition ◽  
Pavement Condition Index

Abstract: Abstract:Damage that occurs on some road segment causing huge lossed, especially for road users such as a long travel time, traffic jam, incident, and etc. In general there variety factor that caused of road damage such as age of the road that has been passed, puddle onthe road surface that cannot flow due to the poor drainage, trafic load excessively repetitive (overloaded). Which can cause life time is shorter than planning. Improper planning, poor monitoring and the implementation is not accordance with the existing plan, in addition to the lack of maintenance costs, delays in budget spending and priorities of improper handling also be the cause. It should be noted in order to avoid decreased in the quality of roads due to damage on road surface. The purpose of this study is to determined damage of the road extent/level using PCI method (Pavement Condition Index), determined the effect of road damage to the speed of vehicle using Regression Analysis method. This research take location in the road segment of Blang Bintang Lama road, and Teungku hasan Dibakoi each road is divided into 7 that being reviewed according to the level of damage. Primary data collected by field actual survey in the form of geometric data, extensive damage to the road, and vehicle speed. The results showed that damage of the road is very affected on the vehicle speed as seen on Blang Bintang Lama in V segment the value of PCI is 10 with failed condition and vehicle speed just reached 5.31 Km/h, while in VII segment PCI value is 87 with perfect road condition (excellent) vehicle speed reached to 58.34 Km/h, so that the equation obtained by regression analysis of Y = (3,571)(0,032) ͯ, while for segment in Teungku Hasan Dibakoi road as seen in III Segment PCI value is 4 with failed condition with vehicle speed just 4.95 Km/h, while in the VII segment PCI value is 88 with perfect road condition (excellent) vehicle speed reached to 68.64 Km/h, so the equation obtained by regression analysis of Y is Y= (3,822)(0,035) ͯ. This suggests that higher levels of road damage will affected to slower speed of vehicle, otherwise the lower level of damage road, will make the higher speed of vehicle.Abstrak: Kerusakan jalan yang terjadi di beberapa ruas jalan menimbulkan kerugian yang sangat besar terutama bagi pengguna jalan seperti waktu tempuh yang lama, kemacetan, kecelakaan, dan lain-lain. Secara umum penyebab kerusakan jalan ada berbagai sebab yaitu umur rencana jalan yang telah dilewati, genangan air pada permukaan jalan yang tidak dapat mengalir akibat drainase yang kurang baik, beban lalu lintas berulang yang berlebihan (overloaded) yang menyebabkan umur pakai jalan lebih pendek dari perencanaan. Perencanaan yang tidak tepat, pengawasan yang kurang baik dan pelaksanaan yang tidak sesuai dengan rencana yang ada, selain itu minimnya biaya pemeliharaan, keterlambatan pengeluaran anggaran serta prioritas penanganan yang kurang tepat juga menjadi penyebabnya. Hal ini perlu diperhatikan agar tidak terjadi penurunan kualitas jalan akibat kerusakan permukaan jalan. Tujuan penelitian ini adalah untuk menentukan tingkat dan jenis kerusakan jalan dengan menggunakan metode PCI (Pavement Condition Index), mengetahui pengaruh kerusakan jalan terhadap kecepatan kendaraan dengan menggunakan metode Analisis Regresi. Penelitian ini mengambil lokasi pada ruas Jalan Blang Bintang Lama dan ruas Jalan Teungku Hasan Dibakoi yang masing-masing jalan terbagi atas 7 segmen yang ditinjau menurut tingkat kerusakannya. Pengumpulan data primer dilakukan dengan survey aktual lapangan yaitu berupa data geometrik jalan, luas kerusakan jalan, dan kecepatan kendaraan. Hasil penelitian menunjukkan bahwa kerusakan sangat berpengaruh terhadap kecepatan kendaraan seperti yang terlihat pada ruas jalan Blang Bintang Lama pada segmen V dengan nilai PCI 10 kondisi jalan gagal (failed) dengan kecepatan kendaraan mencapai 5,37 Km/Jam, sedangkan pada segmen VII nilai PCI sebesar 87 dengan kondisi jalan sempurna (excellent) kecepatan kendaraan mencapai 58,34 Km/Jam, sehingga didapat persamaan dengan metode analisis regresi Y= (3,571)(0,032) ͯ, sedangkan untuk ruas Jalan Teungku Hasan Dibakoi terlihat pada segmen III nilai PCI 4 kondisi jalan gagal (failed) dengan kecepatan mencapai 4,95 Km/Jam, sedangkan pada segmen VII nilai PCI sebesar 88 dengan kondisi jalan sempurna (excellent) kecepatan kendaraan mencapai 68,64 Km/Jam, sehingga didapat persamaan dengan metode analisis regresi Y= (3,822)(0,035) ͯ. Hal ini menunjukkan bahwa semakin tinggi tingkat kerusakan jalan maka semakin rendah kecepatan kendaraan, sebaliknya semakin rendah tingkat kerusakan maka semakin tinggi kecepatan kendaraan.

scholarly journals Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index

2020 ◽  
Vol 26 (12) ◽  
pp. 81-94
Author(s):  
Muataz Safaa Abed
Keyword(s):  
Regression Models ◽  
Essential Element ◽  
Condition Index ◽  
Flexible Pavement ◽  
Transportation Infrastructure ◽  
International Roughness Index ◽  
Pavement Condition ◽  
Roughness Index ◽  
Pavement Condition Index ◽  
Quadratic Models

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.

scholarly journals PERBANDINGAN METODE INTERNATIONAL ROUGHNESS INDEX DENGAN PAVEMENT CONDITION INDEX UNTUK PENENTUAN KONDISI JALAN NASIONAL DI KOTA WAMENA (STUDI KASUS : RUAS JALAN WAMENA – HABEMA)

2022 ◽  
Vol 5 (1) ◽  
pp. 1-7
Author(s):  
Muhamad Agung Rahman ◽  
Herdianto Arifin ◽  
Bertho Orbain Sowolino
Keyword(s):  
Condition Index ◽  
International Roughness Index ◽  
Pavement Condition ◽  
Roughness Index ◽  
Pavement Condition Index

Pembangunan infrastruktur jalan merupakan suatu kebutuhan mutlak bagi pengembangan suatu wilayah agar tercapai kesinambungan dan pemerataan pembangunan pada setiap daerah serta membentuk struktur ruang dalam rangka mewujudkan sarana pembangunan nasional. Untuk membuka isolasi dan akses masyarakat terhadap perkembangan perekonomian di Kota Wamena, pemerintah melaksanakan pembangunan dan pemeliharaan jalan. Pemeliharaan jalan bertujuan untuk mempertahankan tingkat pelayanan sesuai dengan standar pelayanan minimum yang ditetapkan.Penelitian ini dilakukan pada ruas Jalan Wamena-Habema sepanjang 35,100 kilometer. Penelitian ini bertujuan untuk membandingkan kondisi jalan hasil pengukuran metode IRI dengan metode PCI. Data yang digunakan berupa data IRI  dan PCI semester 2 tahun 2020 yang diperoleh dari Sistem Pengelolaan Database Jalan Nasional (SiPDJN) Direktorat Jenderal Bina Marga Kementerian Pekerjaan Umum dan Perumahan Rakyat.Hasil penelitian menunjukkan ada perbedaan kondisi jalan Wamena-Habema berdasarkan metode IRI dan metode PCI. Pada metode IRI 61,8% kondisi baik, 32,2% kondisi sedang. Kondisi rusak ringan dan rusak berat 4,0% dan 2,0%. Sedangkan pada metode PCI 49,6% kondisi baik, 9,7% kondisi sedang. Kondisi jelek dan parah 40,5% dan 0,3%. Dengan dilakukan penelitian kondisi jalan menggunakan metode IRI dan PCI pada ruas Jalan Wamena-Habema dapat memberikan deskripsi atau gambaran tentang data kondisi jalan eksisting. Data kondisi jalan dapat digunakan sebagai database untuk perencanaan dan pelaksanaan pemeliharaan jalan.

Relating Pavement Condition Index and Present Serviceability Rating for Asphalt-Surfaced Pavements

2019 ◽  
Vol 2673 (3) ◽  
pp. 308-312 ◽  
Author(s):  
James Bryce ◽  
Richard Boadi ◽  
Jonathan Groeger
Keyword(s):  
Condition Index ◽  
Ride Quality ◽  
Concrete Pavements ◽  
International Roughness Index ◽  
Pavement Condition ◽  
Transportation Funding ◽  
Surface Transportation ◽  
Roughness Index ◽  
Pavement Condition Index ◽  
Using Data

In response to the two latest transportation funding authorization bills, the Moving Ahead for Progress in the 21st Century Act and the Fixing America’s Surface Transportation Act, rules that require the reporting of specific pavement condition measures have been developed and encoded into federal regulation. Pavement performance rules published to the federal register require the reporting of the International Roughness Index (IRI), percent cracking, rutting (for asphalt-surfaced pavements) and faulting (for jointed concrete pavements). Allowing that the measurement of the IRI on pavements with a speed limit below 40 mph is not expected to provide a reliable estimation of ride quality, the rules permit the reporting of the present serviceability rating (PSR) on these routes. However, many agencies do not measure the PSR or collect the slope variance data required to estimate the PSR. In light of not having the data required to directly estimate the PSR, this paper presents a model to estimate the PSR using data collected during a Pavement Condition Index (PCI) survey. Furthermore, this paper explores the reasons why pavements can have a good PCI and poor PSR and vice versa. The model presented in this paper provides a reasonable estimate of the PSR, though it is noted that agencies who wish to report PSR should conduct an updated assessment of rider satisfaction to develop a stronger correlation of PSR and PCI.

Use of Time–Temperature Superposition Principle to Create Pavement Performance Master Curves and Relate Pavement Condition Index and International Roughness Index

2021 ◽  
pp. 036119812110049
Author(s):  
Jose R. Medina ◽  
Ali Zalghout ◽  
Akshay Gundla ◽  
Samuel Castro ◽  
Kamil Kaloush
Keyword(s):  
Superposition Principle ◽  
Condition Index ◽  
Pavement Performance ◽  
International Roughness Index ◽  
Pavement Condition ◽  
Roughness Index ◽  
Temperature Superposition ◽  
Pavement Condition Index ◽  
Pavement Distresses ◽  
Time Temperature Superposition Principle

The international roughness index (IRI) is one of the most popular indices to measure pavement roughness. State agencies and cities with plenty of resources often collect IRI and pavement distresses every year or every other year, but some others with fewer resources will collect this information every 3 to 5 years. Collecting IRI is much more affordable than collecting pavement distresses. With this in mind, the objective of this paper was to establish a relationship between IRI and pavement condition index (PCI) using pavement deterioration models for both PCI and IRI based on the concept of time–deterioration superposition similar to the time–temperature superposition principle, and then combine both models to establish this relationship. Additionally, this study was used to establish threshold limits for IRI measurements that can be used as a general reference for pavement condition. Data from the Long-Term Pavement Performance InfoPave was used to perform the analysis for three network samples from Arizona, California, and Wisconsin. This analysis only included flexible pavements. The results from Arizona, California, and Wisconsin showed a good relationship between IRI and PCI using the proposed approach with a coefficient of determination ranging from 0.71 to 0.85. Furthermore, the analysis showed that the change in IRI over time can be related to the change in PCI over time. The general thresholds developed in this study apply to the sections evaluated but the approach can be used to set limits for other networks.

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