Estimation of lane distribution of truck traffic for pavement design

Abstract

For structural analysis of pavement design and pavement evaluation, there is often a need to compute critical-lane traffic loading from directional traffic-volume input. The accurate estimation of the lane distribution of truck traffic is an important element in this process. This paper presents a project conducted in Singapore to study the lane-distribution characteristics of truck traffic in five different road classes. The effects on the lane distribution of trucks by the following four factors are presented: the functional class of the road, the number of traffic lanes, the total directional traffic volume, and the volume of truck traffic. Statistical regression models for estimating truck volume in the critical lane were established for hourly traffic-volume input and daily traffic-volume input, respectively. A comparison with three widely used procedures indicated that the proposed regression approach produced the best results. It is proposed that highway agencies adopt the approach and develop their own regression models to provide accurate lane traffic-loading input for pavement design, pavement monitoring, and pavement evaluation.