PAVEMAN: A Data-Driven Customizable PAVEment MANagement System

Successful implementation of a Pavement Management System (PMS) hinges on the accuracy of the information it is based on. Due to the difficulties associated with the current inspection methods, lots of agencies do not have up-to-date information of their road networks. Thus the PMS models need to make lots of assumptions and extrapolations which decrease the reliability of their strategies. This paper introduces PAVEMAN, a data driven customizable PAVEment MANagement system that aims to plan optimum maintenance and repair activities with respect to the priority policies to make practical and defensible decisions. PAVEMAN leverages data from a multi-modal mobile sensor system which can assess road conditions frequently and affordably at both surface and subsurface levels. Stated sensor system consists of acoustic, optical, electromagnetic, and GPS sensors and produces data on a variety of surface and subsurface characteristics of pavements for every meter of a surveyed road. PAVEMAN follows the same logical sequence of the pavement management process. It includes mobile pavement evaluations and data driven maintenance suggestions’ decision trees in addition to priority assessment models. PAVEMAN also projects repair costs and road condition by adopting a data driven deterioration model which considers occurrences of extreme weather events. Each of these components integrates seamlessly with an Oracle database where all the pavement, climate and traffic information reside. PAVEMAN offers a unified solution and an ideal research platform for rapid, intelligent and comprehensive evaluation of tomorrow’s transportation infrastructure performance using heterogeneous sensor systems.