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University Students Showcase Skills in Real-World Autonomous Driving Competition
Original from leaderobot.com: University Students Compete in Real-World Autonomous Driving Challenge

University Students Showcase Skills in Real-World Autonomous Driving Competition

On August 6, the 28th China Robotics and Artificial Intelligence Competition, featuring the Baidu Apollo Autonomous Driving Challenge, commenced at Hohai University's Suzhou Institute. This influential national competition focuses on practical industry applications, utilizing Baidu's real test vehicles and open scenarios to evaluate teams' capabilities in environmental perception, decision-making, and vehicle control.

A total of 122 teams from over 100 universities, comprising more than 350 students and faculty, advanced to the finals, competing in three main events: simulation, real vehicle challenges, and business presentations. Unlike traditional online simulations, this competition brought real road conditions to the arena, allowing students to modify code and deploy systems in real-time to ensure smooth vehicle operation and precise obstacle avoidance.

The event introduced the Apollo Claw intelligent agent, enhancing efficiency in environment deployment by 80% and reducing the development cycle from one month to ten days. Baidu's commitment to talent development in autonomous driving is evident, with over 20,000 participants from 600 universities over five years. The finals in Suzhou aim to connect university talent and innovative projects with regional industry resources, showcasing the shift from theoretical knowledge to practical application in autonomous driving.

Editor's Note

This competition highlights the growing intersection of academia and industry in the autonomous driving sector. By providing students with hands-on experience in real-world scenarios, it fosters innovation and prepares the next generation of engineers for the challenges of intelligent transportation systems. The integration of advanced tools like Apollo Claw signifies a shift towards more efficient development processes in this rapidly evolving field.

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