Road vulnarability damage level using visual model: analysis for medium traffic loading in dense area

Muhammad Nanang Prayudyanto; Rulhendri; Muhammad Rizal Firdaus; Annisyia Zarina Putri; Arien Heryansyah

Author(s)

Muhammad Nanang Prayudyanto Department of Civil Engineering, Faculty of Engineering and Science,UIKA Bogor,Indonesia

Rulhendri Department of Civil Engineering, Faculty of Engineering and Science,UIKA Bogor,Indonesia

Muhammad Rizal Firdaus Department of Civil Engineering, Faculty of Engineering and Science,UIKA Bogor,Indonesia

Annisyia Zarina Putri Department of Agriculture Engineering, Faculty of Engineering and Science,UIKA Bogor,Indonesia

Arien Heryansyah Department of Civil Engineering, Faculty of Engineering and Science,UIKA Bogor,Indonesia

Abstract

In highly populated cities, road damage inspection is a critical and pressing issue for economic traffic. Despite the development of several techniques, the visual method remains popular due to its simplicity and speed of inspection. The Pavement Condition Index (PCI) method is a widely used visual inspection technique for evaluating pavement conditions, valued for its speed, simplicity, and ability to provide a standardized numerical rating based on observed surface distress. In contrast, the Bina Marga analytical method-developed and standardized by Indonesia's Directorate General of Highways-adopts a mathematical and structural analysis approach, incorporating parameters such as pavement deflection, material properties, and load repetitions. Both methods analyze the type and level of road damage to be a reference for road maintenance programs. The research location was chosen in a densely populated, suburban area and experienced substantial deterioration due to traffic loads, environmental factors, and inadequate maintenance. Based on the results of field data, the types of damage found on Bogor district roads are 4 types of damage, namely: edge cracks, longitudinal cracks, patches, and holes. By using the PCI method, the total PCI obtained is 546 with an average PCI of 45.50. So that the condition has a value in a moderate condition (Fair). For the Bina Marga method, the priority sequence value obtained is 5, which indicates that periodic maintenance is needed.

Publication Details

Page(s) 1083-1093

DOI DOI not available

Published Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 20, Issue: 14, Year: 2025

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Keywords

dense area, bina marga, PCI, road damage

References

Shahin M. Y. .2005 .Pavement management for airports, roads, and parking lots (2nd ed. , : .

Hardiyatmo H. C. .2007 .Pemeliharaan jalan raya: Perkerasan, drainase, longsoran (Cetakan 1). , : .

Park K.,Thomas N. E.,Lee K. W. .2007 .Applicability of the International Roughness Index as a predictor of asphalt pavement condition. Journal of Transportation Engineering, 133(706) : 12-947X.

Putri V. A.,Diana I. W.,Putra S. .2016 .Identifikasi jenis kerusakan pada perkerasan lentur (studi kasus Jalan Soekarno-Hatta Bandar Lampung). Jurnal Rekayasa Sipil dan Desain, 4(2) : 366-204.

Karim D. F. M. ,Rubasi D. K. A. H ,Saleh D. A. A. .2016 .The Road Pavement Condition Index (PCI) evaluation and maintenance: A case study of Yemen. -0008, 8(1) : 1446-1455.

Tho 'atin U.,Setyawan A.,Suprapto M. .2016 .Penggunaan Metode International Roughness Index (IRI), Surface Distress Index (SDI) dan Pavement Condition Index (PCI) untuk Penilaian Kondisi Jalan di Kabupaten Wonogiri. Prosiding Semnastek, 0(0) : 1-9.

Firmansyah S. J.,Sigit A. A. .2019 .Analisis potensi kerusakan jalan menggunakan aplikasi sistem informasi geografis di Kecamatan Pulung, Kabupaten Ponorogo (Doctoral dissertation, Universitas Muhammadiyah Surakarta). Universitas Muhammadiyah Surakarta, : .

Oladele A. S. .2013 .Gravel road performance modelling for optimal maintenance interventions of Botswana district transportation network (Doctoral dissertation. Retrieved from the Research Gate database., : .

Gao L.,Liu X.,Liu Y.,Wang P.,Deng M.,Zhu Q.,Li H. .1811 .Measuring Road Network Topology Vulnerability by Ricci Curvature. , : .

Zhao R.,Huang Y.,Luo H.,Huang X.,Zheng Y. .2023 .A framework for using UAVs to detect pavement damage based on optimal path planning and image splicing. Sustainability, 15(3) : .

Leng J.-q.,Yang L J.-q.,Zhao L. .2017 .Measuring Road Network Vulnerability with Sensitivity Analysis. PLoS ONE, 12(1) : .

Pais J. C.,Amorim S. I. R.,Minhoto M. J. C. .2013 .Impact of Traffic Overload on Road Pavement Performance. Journal of Transportation Engineering, : .

Zaghloul S. M.,White T. D. .1994 .Guidelines for permitting overloads. Part I: Effect of overloaded vehicles on the Indiana highway network (Publication FHWA. , : .

Pusat Statistik Kabupaten Bogor Badan .2024 .Kota Cibinong: BPS Kabupaten Bogor. , 28 : .

McKenna J. ,Collection Data .2024 .Physical Vulnerability Database for Critical Infrastructure Hazard Risk Assessments - A Systematic Review. Natural Hazards and Earth System Sciences, 24 : 4341-4365.

Díaz J. A. P.,Riveros O. C. V.,Muñoz M. R. .2022 .Unpaved Road Distress Evaluation Using URDE. ARPN Journal of Engineering and Applied Sciences, 17(10) : 8944-1113.

.2022 .An Integrated Framework for the Quantification of Road Network Seismic Vulnerability. , 14(19) : 12474.

Piryonesi S. M.,El-Diraby T. E.,Tautan HTTPS .2020 .Examining the relationship between two road performance indicators: Pavement condition index and international roughness index. Transportation Geotechnics, 28 : 100501.

Angreni I. A. A.,Adisasmita S. A.,Ramli M. I.,Hamid S. .2018 .Evaluating the road damage of flexible pavement using a digital image. International Journal of Integrated Engineering, 10(2) : 24-27.

Huang Y. H. .1993 .Pavement Analysis and Design. ISBN 0-13- 655275-7, : .