MATS UTC is pleased to announce its 2017 competitive collaborative research awards. Selected from among 28 submissions, these eight projects demonstrate the consortium’s commitment to supporting research that accelerates adoption of sustainable practices in the provision of transportation services.
Celest Chavis (Morgan) and Philip Barnes (UDel)
Bikeshares and bike infrastructure are being implemented in cities across the United States. Bicycling is a low-cost, emission-free form of transportation that has grown in popularity across the United States as jurisdictions look for environmentally friendly transportation options that promote healthy living. Bikeshares serve many purposes; they are used for short, neighborhood trips, tourism, and as a last-mile connection. Bikeshares may induce new trips or result in modal shifts. Moreover, bikeshares can introduce new riders to bicycling.
Wael Zatar (MU), Hai Nguyen (Marshall) and Osman Ozbulut (UVA)
The primary goal of this project is to develop, maintain and implement accurate and manageable processes to evaluate, maintain and repair corrosion-deteriorated adjacent precast box beams in PC bridge infrastructure in the MATS States. Non-destructive techniques and equipment will be used to evaluate existing bridge structures.
Mecit Cetin (ODU), Khan Iftekharuddin (ODU) and Jon Goodall (UVA)
This research proposes to develop a set of tools and analytical capabilities to estimate water inundations due to recurrent flooding from image data, primarily from video surveillance cameras.
Andrew Nichols (Marshall) and Mecit Cetin (ODU)
Each unique commodity (e.g., livestock, fuel, machinery, etc.) is hauled in a specific type of trailer. Narrowing the trailer type can narrow the possible commodity types. The goal of this research project is to determine whether the trailer type can be automatically identified using existing technologies, which is a necessary component of estimating the type of commodity being hauled.
Navid Tahvildari (ODU), Mecit Cetin (ODU), Jon Goodall (UVA) and Pamela Murray-Tuite (VT)
Addressing recurrent flooding of transportation infrastructure is the top priority for the city of Norfolk and many other communities in the region. Recurrent flooding disrupts access to Sentara Norfolk General Hospital which houses the only level 1 trauma center in the region. The research team proposes to develop a framework to use the state-of-the-art hydrodynamic and hydrologic modeling to forecast flooding of the transportation network in real-time.
Ralph Buehler (VT), Steve Hankey (VT) and Andrew Mondschein (UVA)
Over the last two decades walking and cycling have increased in the United States—in particular in large cities. Efforts to further increase walking and cycling occur during a time of increasingly automated and connected vehicles (AVs). Almost nothing is known about impacts of an increasingly automated vehicle fleet on pedestrians and cyclists. This research seeks to develop planning guidelines for walking and cycling during the transition towards an automated and connected vehicle (AV) fleet.
Paul Imhoff (UDel), Pei Chiu (UDel) and Teresa Culver (UVA)
Stormwater from roadways, wastewater facilities, and agricultural operations is a major contributor to deteriorating water quality in many watersheds in the U.S., particularly the Chesapeake Bay in the Mid-Atlantic region. Municipalities and state departments of transportation must find ways to control their discharge to comply with increasingly stringent regulations. Nutrients, such as nitrogen, are the leading cause of impaired water quality in the U.S. and worldwide. Current stormwater treatment technologies, such as bioretention ponds, do not always treat nutrients sufficiently and may require sizable real estate to achieve the necessary removal – unless new technologies are developed. Successful completion of this proposed study will lay the foundation for use of a sustainable, effective methodology for nutrient management in the field.
Donna Chen (UVA) and Rajesh Paleti (ODU)
The research proposed focuses on utilizing a combination of existing RP data and to-be-collected SP survey data to examine the effects of household demographic, vehicle, and transportation infrastructure characteristics on EV ownership.
For more information about these projects, visit our research page at http://www.matsutc.org/research/.