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Not long ago, self-driving cars were merely the stuff of science fiction. Today, however, researchers across the globe are diligently working to integrate autonomous vehicles (AVs) into everyday life. Among these trailblazers is a team of students from 91亚色鈥檚 Lassonde School of Engineering who achieved a second-place win in the Self-Driving Car Student Competition at the 2024 American Control Conference in Toronto last month.
One of the most prestigious conferences in the field of control systems, it brings together experts from academia, government, and industry to share creative ideas and network with like-minded individuals. The Self-Driving Car Student Competition, sponsored by Quanser 鈥 a company that designs and manufactures engineered lab equipment 鈥 provides an opportunity for student researchers to apply their critical thinking skills and solve technical challenges faced by autonomous vehicles.
The competing team from Lassonde, known as Full Throttle 鈥 Spacecraft Dynamics Control and Navigation (SDCN), was led by Mingfeng Yuan, a postdoctoral researcher working under the supervision of Jinjun Shan, a professor in the Department of Earth & Space Science & Engineering.
As the only Canadian team at the competition, the Full Throttle 鈥 SDCN team's award-winning performance highlighted their technical expertise and capacity to represent Canada on a global stage.
The team also included PhD candidates Hunter Schofield and Yida Zang, MASc candidate Amal Haridevan and undergraduate students Hao Zhang and Yiqun Ma.
鈥淪elf-driving cars are complex systems, and it鈥檚 impossible for a single person to design and debug the entire system on their own in a short period of time,鈥 says Yuan. 鈥淭he success we achieved at this competition was a result of the unity and full commitment of our team.鈥


The competition was structured into three distinct phases, starting with an initial pool of 40 teams, representing 28 universities and 15 countries.
First, teams developed and validated solutions using a cutting-edge digital twin platform for self-driving cars. This phase was followed by the implementation of solutions on actual hardware.
The final and most difficult challenge took place at the American Control Conference, where teams navigated a complex circuit with a fully operational self-driving car. This stage required expert-level programming, as teams ensured their car demonstrated impeccable driving accuracy and appropriately responded to street signs, traffic lights and various obstacles.
The high-pressure environment put the team鈥檚 programming and problem-solving skills to the ultimate test.


鈥淓vents like this are incredibly valuable for the student experience,鈥 says Yuan. 鈥淭hey foster team spirit and provide an opportunity to apply our knowledge in a practical setting.鈥
In addition to the educational experience gained by participating students, this competition allowed the Full Throttle 鈥 SDCN team to meaningfully contribute to the exciting future of the AV market.
鈥淎utonomous vehicles are revolutionizing the transportation industry due to their potential to enhance safety, improve driving efficiency and increase vehicle accessibility,鈥 explains Yuan. 鈥淭he applications for AVs are vast, diverse, and have the potential to reshape cities, economies and our daily lives.鈥
