Civil and Environmental Engineering

CEE Team 22

Assessing Maryland Infrastructure Using Object Recognition Software

CEE Team 22 - MD 1-1 project image

Project Description:

As the automotive and technology industry are quickly working to integrate advanced driver assistance systems (ADAS), the quality of roadway conditions and safety features must be assessed. ADAS relies on its ability to quickly identify lane markings, signage, and pavement conditions in order to operate safely and efficiently. With this understanding, this project aims to evaluate the current state of Maryland’s road infrastructure, identify any shortcomings, and provide recommendations for improvement. Roadway infrastructure evaluation will be conducted with AI analysis tools that mimic the ADAS technology within self-driving vehicles. After the collection and analysis of data from various types and conditions of roadways, such as interstate highways and major collectors, Maryland roadways will be graded on their preparedness.

Advisor/Instructor:

Dr. Deb Niemeier

Sponsor:

Dr. Xianfeng Yang

Team Members:

Oluwatobi Ajiboye Civil and Environmental Engineering
Madison Devane Civil and Environmental Engineering
Robert Mayo Civil and Environmental Engineering
Kevin Rosa Civil and Environmental Engineering

Table #:

Y22
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