Assessment of traffic data for road rehabilitation design: A case study of the Korogwe-Mombo road section in Tanzania

Abstract

Traffic loading is one of key inputs for new and rehabilitation designs of pavement. Heavy vehicles cause the most structural damage to pavements; hence, as part of the pavement design process, heavy vehicle volume, and axle load surveys are typically carried out to assist with the accurate estimation of the cumulative traffic loading over a design period. Traffic volumes, axle loads, and the ultimate cumulative traffic loading often fluctuate due to factors such as varying motorist population and economic activities along the length of the road. This paper presents a comparative assessment of traffic loading estimated for the rehabilitation design in 2005, and the actual measured site-specific traffic loading in 2015. The design traffic loading was also compared with the projected future traffic loading for the Korogwe-Mombo road section along the T2 trunk road that connects Tanzania’s business hub of Dar es Salaam with the northern regional cities. The study found, inter alia, that the cumulative traffic loading based on the 2015 measured site-specific traffic data is approximately 2.8 times higher than the design traffic loading based on the 2005 traffic data, which illustrates the importance of using accurate and reliable site-specific traffic data during pavement design. The implications of the findings for rehabilitation design are presented in this paper, along with discussions on the contribution of heavy traffic loading to rutting/permanent deformation that occurred on the surface asphalt layer along the Korogwe-Mombo road section. To improve the accurate determination of traffic loading, traffic studies should ideally be conducted over a long period (typically over one year). However, this is not practical and cost effective when traditional manual methods are used. Hence, it is recommended that road agencies should consider the use of portable automated traffic and Weigh-In-Motion (WIM) monitoring systems.