Effect of pavement condition on vehicle operating costs including fuel consumption, vehicle durability and damage to transported goods

Vehicle Operating Costs (VOC) including fuel consumption, repair and maintenance and damage to goods are an essential part of life cycle cost analysis. They are influenced by vehicle technology, pavement condition, roadway geometrics, environment and speed. Many of these models were developed on the bases of data generated years ago for vehicles that vary substantially from those used currently in the US. Therefore, there is a need to collect new information that could help in refining these models or developing models that would better apply to US conditions.;Regarding fuel consumption, the thesis presents the calibration exercise of the Highway Development and Management model (HDM 4) for US conditions using field data collected as part of this thesis. The results showed that the calibrated HDM 4 model was able to predict very adequately the fuel consumption of five different vehicle classes under different operating, weather and pavement conditions. The better accuracy achieved after calibration has improved the prediction of the effect of roughness. The comparison of sensitivity analyses before and after calibration showed that the effect of roughness on fuel consumption increased by 1.75 for the van, 1.70 for the articulated truck, 1.60 for the medium car, 1.35 for the SUV and 1.15 for the light truck. Also, analysis of covariance was successfully used to extract the effect texture and pavement type from the collected data. The analysis showed that a 67 % decrease in mean texture depth will result in a 1.3 % and 0.9 % decrease in fuel consumption for heavy truck at 56 and 89 km/h, respectively. The analysis also showed that, the mean difference of fuel consumption between asphalt and concrete pavements is statistically significant only at low speed for both heavy and light trucks and for summer conditions.;Regarding repair and maintenance (R&M) costs, two approaches were reported in the thesis. The first approach is to update Zaniewski's repair and maintenance costs (i.e., the latest comprehensive research conducted in the US) using the inflation rate of R&M costs. The second approach is to use the mechanistic-empirical model developed as part of this thesis to conduct fatigue damage analysis using numerical modeling of vehicle response. The comparison between the results from both approaches showed that the results agree up to an IRI of 5 m/km (95 percent of the roads in the US have IRI lower than 5 m/km). These findings show that the mechanistic-empirical approach is promising because it is more flexible than the empirical approach. Also, because of the mechanistic nature of the model, it could be used by state highway agencies (SHA) to correct for the effect of roughness features on vehicle durability at the project level.;Regarding damage to goods, a mechanistic-empirical approach was proposed to conduct product fragility assessment using numerical modeling of vehicle and product vibration response. The model could also be used at the project level.;In summary, this research provided models applicable to the United States. Such models will provide SHA with the tools necessary for considering VOC in evaluating pavement-investment strategies and identifying options that yield economic and other benefits. In addition, this thesis proposes a newly developed tool to detect, localize and identify roughness features.