Currently, asphalt mixtures are design using volumetric concepts to determine optimum asphalt content levels with no means of verifying mixture performance prior to field production and placement. A new design methodology called Balanced Mixture Design (BMD) promotes the use of evaluating and design asphalt mixture using rutting and fatigue cracking methods and criteria to achieve an optimum asphalt content that will result in an asphalt mixture performing well in rutting and fatigue cracking scenarios – thereby “balancing” the asphalt mixture performance.

The objective of this project is to develop a comprehensive framework with a set of models to improve multi-modal traffic signal control, by incorporating advanced floating sensor data (e.g. GPS data, etc.) and traditional fixed sensor data (e.g. loop detectors, etc.). Especially, we are interested in addressing the challenges of multi-modal signal control under non-recurrent conditions, such as traffic incidents and planned special events, since non-recurrent congestions usually account for more than 50% of the total congestions.

Even if they are hosted in sophisticated GIS systems, the asset management systems maintained by various utilities are often plagued by information incompleteness and inaccuracy.  The locational information is often based on approximate design data that differ from actual "as-built" drawings that may not be even be held by such utilities owning and maintaining underground lifeline infrastructure systems (water, wastewater, electric/power, gas, stormwater, and communications networks).