Suggested Citation:
Harvey, John T., Jeremy D. Lea, Changmo Kim, Erdem Coleri, Imen Zaabar, Arghavan Louhghalam, Karim Chatti, Jeffrey Buscheck, Ali A. Butt (2016) Simulation of Cumulative Annual Impact of Pavement Structural Response on Vehicle Fuel Economy for California Test Sections . Institute of Transportation Studies, University of California, Davis, Research Report UCD-ITS-RR-16-04

This report presents the preliminary results of a study of the effects of pavement structural response on excess fuel consumption (EFCS), which is defined as the additional fuel required to propel a vehicle on an “imperfect” pavement compared to the amount required on an “ideal” pavement. The study compared EFCS for a set of asphalt-surfaced test sections with a pavement with no structural response as well as with the effects of roughness and macrotexture on EFC. EFCS was calculated using three different models for a factorial that included seventeen asphalt-surfaced pavement field sections on the California state highway network with different structure types that were characterized by their viscoelastic properties. The results of the modeling were used to simulate annual EFCS for a factorial of vehicles, traffic flows, speed distributions, and climate regions typical of California. The sensitivity of EFCS to the variables in the factorial was analyzed, and the effects of structural response on EFC were compared with those of roughness and macrotexture to determine whether structural response is sufficiently important to warrant a second phase of the project to validate and calibrate the models using field test sections and instrumented vehicles.

It is recommended to complete models for concrete pavements in addition to asphalt-surfaced pavements, to consider multiple layers in the asphalt, particularly near the surface to better evaluate the effects of rubberized asphalt surface materials, and to check the effects of full dynamic pavement modeling (inertial effects in the pavement) on more than the one section analyzed. It is also recommended to begin field validation and calibration of the models and rerun the simulations with the improved and calibrated models for all pavement surface types.