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Transportation Engineering

Faculty Contacts

Mecit Cetin

Sherif Ishak PhD, PE

  • NORFOLK, VA 23529
  • 757-683-5572
  • sishak@odu.edu

Kun Xie

  • NORFOLK, VA 23529
  • 757-683-4304
  • kxie@odu.edu

Research Highlights

An Automated System for Large-scale Intersection Marking Data Collection and Condition Assessment

Dr. Kun Xie

Website: http://www.kxmatrix.com/

Dr. Kun Xie, joined with Dr. Hong Yang from ODU CMSE and Dr. Hongkai Yu from Cleveland State University, we were recently funded a research project ($ 135K) by the NCHRP IDEA program of National Academy of Sciences, titled "An Automated System for Large-scale Intersection Marking Data Collection and Condition Assessment". VDOT will provide $ 50K matching to support the implementation of the system in Virginia. This project will develop an artificial intelligence-powered system to automatically detect and characterize roadway markings (e.g., lane-use arrows and crosswalks) and to assess their degradation conditions using roadway GIS data and aerial images. Current intersection data collection practices are estimated to cost $2,000,000 and 16,000 person-hours for every 100,000 intersections. The proposed system can automate large-scale data collection in a timely manner, with a great potential to reduce the cost to zero. By economically providing large-scale intersection marking data, this system will enable state DOTs to empower analytic methods for data-driven safety management. The proposed system can also assess the degradation condition of identified markings, and thus timely assist maintenance prioritization for reinforcing intersection safety.

Transportation Research Institute

Mecit Cetin, Director

Website: http://www.tri-odu.org/

The Transportation Research Institute (TRI) in the Civil and Environmental Engineering (CEE) Department at Old Dominion University is focused on developing innovative solutions to address congestion, safety, and environmental impacts of surface transportation systems. The research activities of the Institute include the following areas:

  • Transportation operations
  • Intelligent Transportation Systems (ITS)
  • Connected and Automated Vehicles (CAVs)
  • Transportation safety
  • Modeling freight systems
  • Environment, energy, and sustainable transport
  • Applications of AI and machine learning in transportation

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