The objective of this project is to validate a remote-sensing and GIS-enabled Asset Management System (RS-GAMS) integrating emerging 3D line laser imaging, signal/image processing, and GPS/GIS technologies to bring the new capabilities to roadway asset inventory, condition assessment, and management with a special focus on network-level pavement surface/pavement marking condition assessment, and efficient inventory of cross slopes, roadway curvatures, and pavement width. Project development steps are to (1) refine and calibrate the integrated sensing system, (2) test and validate the sensing system using the real-world data, (3) quantify the research benefits. The validated technologies and systemtargets asphalt and concrete highways, parking lots, and civilian and military airfield taxiways and runways. The US DOT, the Georgia Institute of Technology, GDOT, FDOT, NCDOT, SCDOT, and Chatham county – Savannah Metropolitan Commissionhave participated in this project by providing direct and in-kind support. 

The technology to be developed in this project is an extension of the outcomes from RS-GAMS Phase 1 that is sponsored by the US DOT RITA CRS&SI program.  The following figure shows the architecture of RS-GAMS. It includes the components of the sensing system, data processing and collection, data integration and management, and decision support.  New capabilities and functions for data collection, condition assessment, and decision support can then be developed under this system framework.  RS-GAMS Phase 1 has established the preliminary framework and also uses two assets (sign and asphalt pavement) to demonstrate its capability. 

RS-GAMS Phase 2 uses the framework developed in Phase 1, but extends to additional roadway assets, including concrete pavements, pavement markings,cross slopes, curvatures, and pavement widththat are important for transportation agencies’engineering practice.  RS-GAMS Phase 2 focuseson the following applications and their validations:

(1) Asphalt pavement distress classification.

(2) Concrete pavement distress detection.

(3) Roadway characteristics data collection.