Hubungan Lalu Lintas Harian Rata-Rata (LHR) dan Proporsi Kendaraan Berat Terhadap Surface Distress Index (SDI)

Rany Agustina, Kurniati Lestari, Ratna Sari, Susilowati Susilowati

Abstract


The Betung – Palembang City Boundary Road segment is part of the primary arterial corridor of the East Trans-Sumatra route, which plays an important role in supporting regional logistics connectivity. The high intensity of freight transportation along this corridor increases the frequency of heavy vehicle movements and generates repeated loading on flexible pavements, which may accelerate pavement surface deterioration. Based on Average Daily Traffic (ADT) data from the South Sumatra National Road Implementation Agency (BBPJN) in 2024, the traffic volume on this segment reaches approximately 52,073 vehicles per day with a heavy vehicle proportion of about 37%. Meanwhile, the traffic survey conducted in this study recorded an average of approximately 25,000 vehicles per day with a heavy vehicle proportion of about 12%. This study aims to analyze the characteristics of ADT and heavy vehicle proportions, evaluate the level of pavement surface distress using the Surface Distress Index (SDI) method, and examine the relationship between traffic variables and pavement surface deterioration. The research method involved field surveys consisting of traffic counts and visual pavement inspections per segment. SDI values were calculated based on the type, extent, and severity of pavement distress. The relationship between variables was analyzed using multiple linear regression. The results show that segments with higher traffic volumes and greater proportions of heavy vehicles tend to have higher SDI values, indicating moderate to poor pavement conditions. The regression model produced a coefficient of determination (R²) of 0.8383, indicating that approximately 83.83% of the variation in SDI values can be explained by traffic volume and vehicle composition variables. Partially, large buses (p = 0.0438) and heavy trucks (p = 0.0417) were found to significantly influence the increase in SDI values. Therefore, traffic volume and heavy vehicle composition data can be recommended as key indicators for determining condition-based road maintenance priorities to improve the effectiveness of national road management.

Keywords


Average Daily Traffic; Heavy Vehicles; Surface Distress Index; Pavement Surface Distress; Regression Analysis.

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References


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DOI: http://dx.doi.org/10.33087/talentasipil.v9i2.1340

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Jurnal Talenta Sipil, Faculty of Engineering, Batanghari University
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