Old Dominion University
A to Z Index  |  Directories


Frank Batten College of Engineering and Technology


Center for Innovative Transportation Solutions


About Us

Activities/Outreach


TranLIVE UTC


Trans Res Institute


Trans Applications Program


Trans Mod & Sim Prog


Dr. Mecit Cetin Dr. Mecit Cetin
Associate Professor
Civil & Environmental Engineering Department
135 Kaufman Hall, Old Dominion University
Norfolk , VA 23529-0241

Telephone: (757) 683-6700
E-mail: mcetin@odu.edu

Dr. Mecit Cetin's CV

 

Dr. Mecit Cetin earned his M.S. degree in Civil Engineering and Ph.D. degree in Transportation Engineering from Rensselaer Polytechnic Institute (RPI), Troy, NY, in 1999 and 2002, respectively. Dr. Cetin has joined the Civil and Environmental Engineering Department at Old Dominion University (ODU) as an assistant professor in August 2008. Prior to that, he had worked as an assistant professor for four years in the Department of Civil and Environmental Engineering at the University of South Carolina (USC), Columbia, SC. Dr. Cetin has published more than 20 peer reviewed journal papers and conference proceedings. Dr. Cetin has been conducting research in various areas including modeling and simulation of traffic operations, congestion pricing, freight transportation, advanced traveler information systems, traffic signal control, probe vehicle technologies, and system state estimation in transportation networks. Currently, Dr. Cetin is developing new methods to estimate the system state in transportation networks (e.g., travel times, flow rate, and queue lengths) from the real-time data collected by various types of sensors such as inductive loops and probe vehicles equipped with wireless communications and tracking technologies. System state estimation is a critical component in optimizing the efficiency of transportation operations, traffic signal optimization, emergency evacuation & response, and effective management of transportation networks. Dr. Cetin is also conducting research that pertains to modeling the movement of freight over the highway networks. He is developing new vehicle re-identification algorithms to estimate flow patterns of truck traffic to obtain a better understanding of origin-destination flows, empty truck movements, and reliability of travel times.