Upper Great Plains Transportation Institute

UGPTI Transportation Data Intelligence Lab

Mission

Support data and information needs of transportation agencies for planning, design, construction, maintenance, operations, safety, and research in support of the safe and efficient movement of people and goods.

Objectives

  • Develop and enhance a classroom Transportation Management and Traffic Operations Center Emulation Lab with interconnected transportation data feeds from all available State, County, City, and Tribal sensors.
  • Provide workforce development to State and Local agencies by giving students hands-on experience with monitoring and analyzing real-time traffic, weather, and operations data along with the skills necessary to interpret and provide decision support to improve safety and operational efficiency.
  • Develop advanced artificial intelligence models and technologies to collect and interpret real-time data feeds and provide decision support to transportation management center operators.
  • With all data sources develop artificial intelligence models to support the ability to predict the future performance of assets, measure the cost-benefit and performance of maintenance and operations practices, communicate timely information to managers, operators, and the public, and support research to achieve safe and efficient highways.

Tools

Emerging technology and techniques will be used to collect, transmit, process, and analyze data for managing transportation systems and conducting research.

  • Artificial intelligence / machine learning / deep learning will improve accuracy.
  • Edge computing components will collect data, run algorithms, perform results, and communicate data at low cost.
  • Internet of things components communicate data packets to online data server.
  • Power components provide long-term power at low cost.
  • Sensors include video, image Infrared, radar/lidar, ultrasonic, vibration, and soil moisture and temperature sensors.
  • Connected vehicles are equipped with vehicle-to-everything technologies and can capture geo-referenced data such as speed, trajectory information, acceleration and other data.