FUNCTIONAL SUITABILITY OF ROAD INFRASTRUCTURE FOR TRAFFIC SAFETY: AN ATTRIBUTE-BASED EXPERIMENTAL STUDY

Abstract

Traffic safety remains a global public health concern, especially in low- and middle-income countries where inadequate infrastructure significantly increases crash risk. This study investigates the functional suitability of road infrastructure and its impact on traffic safety through an attribute-based experimental approach. The research collected primary data from arterial and collector roads in Pekanbaru, Indonesia, focusing on lane width, pavement condition, road markings, traffic signs, and lighting. Statistical analyses included Pearson’s correlation, multiple linear regression, and surrogate safety assessment model (SSAM) simulations. Results indicate that pavement condition (β = 0.42; p < 0.01) and lighting (β = 0.35, p < 0.05) are the strongest predictors of crash frequency, followed by sign clarity and lane width. The findings support the development of data-driven roadworthiness assessment methods in developing countries, highlighting cost-effective interventions such as repainting road markings and upgrading lighting systems.