LSU EE Professor Acquires Self-Driving Car Studio for Students, Faculty

August 8, 2024

Xiangyu Meng and two students kneel on trackBATON ROUGE, LA – LSU Electrical Engineering Assistant Professor Xiangyu Meng has acquired a new Self-Driving Car Studio (SDCS) that will be used by faculty and students. Meng says the new SDCS will encourage synergistic research between multiple groups across campus working on intelligent transportation, including those in electrical and computer engineering, mechanical engineering, civil engineering, and construction management.

The project is funded by a $107,000 Board of Regents grant.

“The goals of this project are to provide faculty a fertile environment for intelligent transportation research, including CAV (connected autonomous vehicles) and AI (artificial intelligence), and provide students with up-to-date, immersive learning experiences in important application areas,” Meng said. “This will aid faculty in adjacent areas to move into intelligent transportation and maintain research productivity in current CAV and AI areas.

“Faculty members from various disciplines can collaborate on connected and autonomous vehicles, focusing on diverse aspects such as control algorithm development, object detection based on computer vision, battery management, the safety impact of platooning, and the effects on pedestrian safety and passenger comfort. The equipment will make it easier for them to try out new ideas and generate preliminary results needed to obtain research funding.”

Students work on the test track and vehicles

As for students, working with the SDCS equipment will give them practical knowledge of programming languages, such as Python and Matlab/SIMULINK. The work in CAVs will also empower students to learn skills in distributed autonomy, multi-agent systems, and decentralized systems by understanding vehicle-to-vehicle and vehicle-to-infrastructure communication in CAVs.

“These skills will be necessary to train the next group of engineers that will be tasked with integrating autonomous systems into society,” Meng said.

One example of this is an intelligent transportation system in which all vehicles and infrastructure components are interconnected, providing precise knowledge of the traffic situation across the entire road network, which in turn helps optimize traffic flows, enhance safety, reduce congestion, and minimize emissions. Vehicle-to-infrastructure communication is a potential engineering countermeasure to reduce red light running.

“The proposed project will have a real-world component and will challenge students to think about how they can innovate to solve complex problems,” Meng said.

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