The researchers plan to use artificial intelligence to reduce commercial accidents

Dr. Judith McClung of South Carolina State University and Dr. Saidi Siohey are among a team of researchers who were recently awarded a $1.3 million federal grant to study commercial vehicle crashes.

Funded by the Federal Carrier Safety Administration, the project aims to use artificial intelligence to reduce CMV incidents in highway work areas via alerts through wireless technology.

“This project will play a key role in expanding SC State’s transportation research capabilities by applying artificial intelligence in addressing commercial vehicle safety in work areas,” said Mwakalonge, Professor of Transportation Engineering and principal investigator on the project. “Transportation students involved in this will be uniquely empowered by existing technologies to solve transportation problems.

“We look forward to collaborating with Benedict and Clemson on this work in due course,” she said.

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Siuhi, assistant professor of civil engineering, serves as co-principal investigator for the project. Dr.. Gurkan Kumart of Benedict College and Mashroor Chowdhury of Clemson University are also on the team.

“It is exciting to be a part of the South Carolina State University team on the FMCSA scholarship that will improve safety on American roads through AI-based real-time work area safety assessment,” Chaudhry said.







SCState Commercial Vehicle Safety

SC State researchers and officials join Clemson University and Benedict Fellows in launching a commercial vehicle safety project with the Federal Motor Carrier Safety Administration.


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“It has always been rewarding for us to collaborate with Dr. Judith McClung and her team at South Carolina State University on new frontiers of transportation research. We are fortunate to expand our collaboration through this FMCSA grant,” Chaudhry said. “We can’t wait to start this new collaboration with South Carolina State University and Benedict College on this project.”

While the study will initially use data from the South Carolina Department of Public Safety and Department of Transportation and work will take place along South Carolina highways, officials expect the effort to result in a prototype for use nationally.

Most commercial vehicles are oversized, which leads to challenges associated with operations that contribute to crashes, injuries, and deaths on US highways. The National Highway Traffic Safety Administration’s (NHTSA) Fatality Analysis Reporting System (FARS) data shows that commercial vehicle participation in fatal work area accident incidents is increasing:

  • In the United States, a work site death occurs every 15 hours, while work site accident injuries occur every 16 minutes.
  • In 2019, out of 115,000 work area-related accidents, 22,000 were involved in CMVs, of which 4,000 were injury accidents, 247 were fatal accidents, with 288 fatalities.

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By gathering information from traffic cameras and roadside units, the grant team will develop a safety application for commercial vehicles:

  • A vision-based deep learning model will detect vehicles under different weather and lighting conditions.
  • The team’s algorithm will generate safety alerts during the risk of an accident.
  • The team will use video data from multiple traffic cameras at security-significant road sections/intersections to detect CMVs, generate safety messages, and provide CMV-related safety alerts to approaching vehicles.
  • On a part of the way, vehicles wirelessly connected to other vehicles, people and infrastructure can receive wireless alerts through an in-vehicle display or a mobile phone.

Offline vehicles will receive the alert via dynamic message signs or mobile phones.

As defined by US federal motor vehicle carrier safety regulations, a CMV is any vehicle used on a public highway to carry passengers or cargo when the vehicle meets any of the following criteria:

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  • The gross vehicle weight is 4,536 kg (1,001 lb) or more.
  • It is designed or used to carry more than 8 passengers (including the driver) for compensation.
  • It is designed or used to carry more than 15 passengers including the driver, and is not used to carry passengers for compensation.
  • It is used to transport materials that the Minister of Transport found to be dangerous.

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