Road Safety and Pavement Management: a case study of Tanzania

Amador-Jimenez, Luis; Pooyan Afghari, Amir · 2015 · Crossref

DOI: 10.3846/bjrbe.2015.17

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Summary

This paper addresses the challenge of integrating road safety into pavement management systems (PMS) in contexts where historical accident data is unavailable. Traditional PMS implementations often prioritize infrastructure condition while neglecting safety, or rely on monetized multi-objective frameworks that require extensive data. The authors propose a method to incorporate safety considerations using locally available data on safety hardware and pavement conditions, demonstrated through a case study of Tanzania’s national road network. The study focuses on a subset of approximately 3,000 km of paved roads in Tanzania. Due to the absence of an accident database, the researchers developed a composite safety index based on exposure, severity, and likelihood. Likelihood was derived from six contributing factors: pavement roughness, skid resistance (inferred from raveling and bleeding), guardrail coverage, shoulder adequacy, lane width, and curve intensity. Exposure and severity were estimated using land use as a proxy for traffic volume. This safety index was combined with the International Roughness Index (IRI) to create a multi-objective optimization model. The model utilized linear integer programming to allocate corrective measures—such as micro-surfacing, mill-and-overlay, shoulder widening, and realignment—under annual budget constraints. Treatment effectiveness was defined by extensions in service life or gains in the safety index, with costs estimated using 2007 exchange rates. The results indicate that a balanced approach is necessary to optimize both safety and condition. Through tradeoff analysis, the study determined that assigning 70% relevance to road safety and 30% to pavement condition yielded the most effective outcomes. Under a fixed budget of 5 million EUR, this weighting (Scenario B) allowed for the correction of safety and condition deficiencies within five years. The majority of improvements involved surface treatments, with some geometric corrections. The analysis showed that siloed approaches, where budgets are split rigidly between safety and condition, worsened results by delaying recovery rates for both metrics. Furthermore, the study noted that if larger budgets were available, significant investments in geometric corrections would occur in years two and three. The significance of this work lies in providing a practical framework for developing countries or agencies with limited data to implement safety-conscious pavement management. By using a modified Pareto analysis and a composite safety index, the method allows for strategic planning that balances resources to achieve good surface conditions and low safety risks. The authors conclude that this initial model serves as a valuable first step, which can be refined as more comprehensive accident data becomes available in the future.

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