Development of a Prediction Model for Paved Road Condition to Enhance Delayed Maintenance: A Case Study of Simiyu Region, Tanzania

Pascal John; Jubily Musagasa

doi:10.37284/eaje.8.2.3994

Pascal John Dar es Salaam Institute of Technology
Jubily Musagasa, PhD Dar es Salaam Institute of Technology

DOI: https://doi.org/10.37284/eaje.8.2.3994

Keywords: Road Maintenance Management, Pavement Condition Prediction, Delayed Maintenance, Tropical Climate, TANROADS, Infrastructure Management

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Abstract

This research developed a forecasting model for paved road conditions in the Simiyu Region, Tanzania, addressing delayed maintenance challenges to mitigate infrastructure decay and escalating rehabilitation costs by TANROADS. A mixed-methods approach included surveys of 99 transportation professionals and field measurements of road segments aged 5-39 years. Relative Importance Index (RII) analysis identified surface distress parameters as most critical: pavement distress density (RII=0.87), potholes (RII=0.87), and surface cracking (RII=0.86). Environmental factors received low ratings (RII=0.39), indicating knowledge gaps regarding climate-pavement interactions. Multiple regression analysis produced a precise model with seven key factors, demonstrating high performance with a correlation coefficient R=0.99 and a coefficient of determination R²=0.98, explaining 98% of road condition variance. The model was statistically significant (F=142.36, p<0.001) and categorises road conditions into five levels from Very Severe (0-20%) to Very Good (80-100%). Validation on road segments confirmed model accuracy, revealing that maintenance delays lead to exponential cost increases of 300-1000% due to deferred preventive treatments. The Ditiwa-Lamadi segment (39 years) scored 20% (Very Severe), while the Bariadi-Kisesa segment (5 years) scored 84% (Very Good). This study introduces the first regionally adjusted deterioration model tailored to Tanzania's tropical environment, enabling a shift from reactive to proactive maintenance planning and supporting sustainable infrastructure management in developing countries.

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