Eight summer students will learn self-driving car technology at LTU under NSF grant 

SOUTHFIELD—Eight research internship students from across the nation have arrived at Lawrence Technological University to spend eight weeks learning the technologies behind autonomous and connected vehicles under a National Science Foundation grant.

The program, now in its third of three summer sessions, was created by C.J. Chung, professor of computer science at LTU. He applied for and won  $288,112 grant under NSF’s Research Experiences for Undergraduates program. Participants live in LTU’s residence halls and receive a $6,880 stipend.

“Students will design and implement robust algorithms to self-steer real vehicles to drive on a test course with an intersection using traditional and AI methods,” Chung said. “In addition, they will develop V2X—vehicle to everything—communication algorithms that can help improve traffic efficiency and safety. Their designed algorithms and test results will be published in academic papers, and their developed code will be publicly available.”

The student researchers are Jason Chen, a computer and systems engineering major from the University of Southern California; Luis Escamilla, a computer science major from New Mexico State University; Michael Evans, a computer science major from Old Dominion University in Norfolk, Va.; Benat Froemming-Aldonado, a data processing major from the University of Minnesota; Rickey Johnson, a computer science major from North Carolina A&T State University; Marcial Machado, a computer and information sciences major from Ohio State University; Tatiana Rastoskueva, a computer science major from the University of Arizona; and Anna Vadella, a computer science major from Butler University in Indianapolis, Ind. A committee selected the students from a field of 86 applicants.

Collaborating with Chung on the summer program are Joshua Siegel, assistant professor of computer science and engineering at Michigan State University and Mark Wilson, professor of urban and regional planning at MSU, who is an external program evaluator.

The summer program is based on Chung’s 21 years of experience with LTU student teams in the Intelligent Ground Vehicle Competition, a collegiate autonomous vehicle event held each year on the Rochester campus of Oakland University. The competition is presented by OU’s School of Engineering and Computer Science; the U.S. Army Combat Capabilities Development Command Ground Vehicle Systems Center; a local intelligent vehicle business, Great Lakes Systems and Technology; and the Association for Uncrewed Vehicle Systems International.

LTU is the six-time reigning world champion in the IGVC’s self-driving car competition. The 2024 IGVC is scheduled for May 31-June 3.

Through Chung’s efforts, LTU has obtained two Polaris GEM electric vehicles that have been modified with self-driving technology from a variety of industry partners.

The students’ demonstrations and final presentations on July 12 and 15 will be open to the public at times still to be announced.

Lawrence Technological University, www.ltu.edu, is one of only 13 private, technological, comprehensive doctoral universities in the United States. Located in Southfield, Mich., LTU was founded in 1932, and offers more than 100 programs through its Colleges of Architecture and Design, Arts and Sciences, Business and Information Technology, Engineering, and Health Sciences. PayScale lists Lawrence Tech among the nation’s top 11 percent of universities for alumni salaries. Forbes and The Wall Street Journal rank LTU among the nation’s top 10 percent. U.S. News and World Report lists it in the top tier of best in the Midwest colleges. Students benefit from small class sizes and a real-world, hands-on, “theory and practice” education with an emphasis on leadership. Activities on Lawrence Tech’s 107-acre campus include more than 60 student organizations and NAIA varsity sports.

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.