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

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.

A Study on the Roads Flatness Using International Roughness Index in New Taipei City

The quality of roads is an indicator of urban progress. The development of tourism and economy contributes to the increasing demands for transportation and, thus, aggravated burdens and vulnerability to damage of these roads, and the result is compromised transportation quality and safety. The Road Leveling Project is aimed to road updates and improvement of pavement quality. New Taipei City was selected as the subject for this study. International roughness index (IRI) was selected for field survey and statistical comparison. The outcome indicated that the IRI spread between 3.5 and 6.5 m/km before road leveling with an average of 4.71 m/km; the index fell between 2.5 and 4.5 m/km after road leveling with an average of 3.12m/km, suggesting that the IRI of the tested road sections showed a declining trend. For multi-lane road sections tested, the improvement was greater on the outer lanes than on the inner lanes. This proves that the implementation of the Road Leveling Project has made significant improvement in terms of pavement flatness. Suggestions are proposed in this study for the subsequent management and improvement polices of the Road Leveling Project, hoping that the pavement quality improvement continues to contribute to the extension of road service life and ride comfort.

Determining the influence of concrete drying shrinkage in the International Roughness Index of newly constructed rigid pavements in Bolivian Altiplano

In the last decade, the design and the construction of concrete pavements in Bolivia focused on prevention of fatigue damage of concrete by the design and construction of locally named "semi-short slabs" concrete pavements, a solution with slab size between traditional JPCP and short slab concrete pavements. Although the structural performance of these new pavements is adequate so far, it was observed that the length of the slab, which commonly is between 2.4 to 3.0 m, affects functional performance. Because of the slabs are affected by differential drying shrinkage, they develop permanent curling with wavelengths that have more influence on IRI with respect to other lengths due to the sensitivity of the Quarter-Car model. This article describes the studies conducted to determine the slab curling influence on IRI of concrete pavements built with semi-short slabs in the last years in the Bolivian Altiplano. Longitudinal profile data was collected by means of a laser profilometer in highway sections located in western Bolivia, in regions with high altitudes and arid climate. Based on profile information, mechanistic analyses were done in order to estimate the theoretical deflections along the slabs that correspond to the observed curling. Deflections calculated were then used to estimate a Pseudo Strain Gradient that represent the effects of curling along the evaluated sections. IRI related to slabs curling was calculated and compared to IRI calculated from artificially generated profiles for various slab lengths. Results indicate that slab curling of these pavements has an important influence on IRI of evaluated sections. Recommendations for specifications of new construction projects are presented.

International Roughness Index Modeling For Jointed Plain Concrete Pavement Using Artificial Neural Network

Climate attributes such as precipitation, extreme temperature, and freeze-thaw cycles along with traffic loads cause pavement distresses. The maintenance need for pavements is decided based on the pavement condition rating such as International Roughness Index (IRI). Generally, an IRI rating less than 2.68 m/km is acceptable, and a rating greater than 2.68 m/km is considered unacceptable and classified as “very poor” condition of the pavement. It is imperative to be able to accurately predict pavement conditions to prepare proper Maintenance and Rehabilitation (M&R) programs for the pavements. This study aims to develop IRI models that can successfully estimate the IRI values for Jointed Plain Concrete Pavement (JPCP) considering the M&R history of the pavements using Artificial Neural Networks (ANNs) approach. The study was carried out with the database collected from Long Term Pavement Performance (LTPP) program. The variables used for the ANN model development are initial IRI, pavement age, concrete pavement thickness, equivalent single axle load (ESAL), climatic region (wet-freeze, wet non-freeze, dry-freeze, dry non-freeze), construction number (CN), and several climatological data. After utilizing various ANN model structures, the best performing ANN model resulted in promising statistical measures (i.e. R2 = 0.87). The IRI prediction model can successfully estimate the increase of IRI values with the increase of ESAL value over time. The IRI prediction model can also estimate the decrease of IRI value after maintenance and rehabilitation. The predicted IRI values with good accuracy will help the local and state agencies to prepare for M&R programs for JPCP pavements and allocate a projected budget accordingly.

On the Applicability of Laser Scanning for Evaluation of the Pavement Serviceability Parameters

Pavement performance is influenced by man factors such as climate and environmental conditions, traffic and operational conditions and type of pavement. These factors cause a pavement deterioration what leads to the restriction of the pavement serviceability or pavement efficiency. The pavement serviceability is the ability of the pavement to fulfil the service function represented by the actual values of variable parameters such as pavement surface roughness, surface evenness, pavement surface condition. The state of the pavement is assessed using different performance indicators when International Roughness Index (IRI) is most used. This approach allows to classify the state of the pavement in the pavement management system as a most used indexing, generalizes the pavement surface to the response of the testing car tire and the pavement. Laser scanning presented in this paper is able to bring the knowledge about the real pavement surface considering the accuracy of the method and equipment. Realized laser scanning proved the applicability of this method for the measurement of the pavement surface. Because of the complex knowledge of the pavement surface morphology, we can evaluate the pavement serviceability in terms of roughness, surface evenness or even pavement surface condition (rutting or cracks).