Engineer the Future of Mobility
For high school students, 15 and up, interested in engineering, robotics, AI, computer science and programming
July 19–23, 2027
University of Delaware | ICAT Lab at STAR Campus, Newark, Del.
REGISTRATION OPENS DECEMBER 1, 2026.
Autonomous vehicles are transforming how the world moves — and the engineers designing them are shaping industries far beyond transportation. The Autonomous Driving Academy invites motivated high school students to explore the engineering principles, systems thinking and technologies behind modern self-driving systems.
Designed for rising high school sophomores, juniors and seniors (ages 15+), this five‑day, hands‑on program is ideal for students interested in engineering, robotics, AI, computer science and programming who want to go beyond the basics.
Students gain:
- A strong foundation in engineering and autonomous systems
- Teamwork, communication and analytical skills
- Exposure to a college-level research environment
- Project-based experience that supports college and internship applications
Wondering if this program is right for you? Share your interests and experience through the form below.
About the program
Developed with University of Delaware’s Connected and Autonomous Research Laboratory (CAR Lab) and the Department of Computer and Information Sciences, this program focuses on how engineers design, integrate and test real-world autonomous systems.
More than a coding camp, this program emphasizes:
- Engineering design and systems integration
- How software, sensors and control systems work together
- Applying theory to real-world challenges
Learn where autonomous driving innovation happens
At UD’s CAR Lab, led by internationally recognized researcher Weisong Shi, students explore the technologies behind autonomous vehicles in an active research environment.
Through hands-on projects and interactions with CAR Lab researchers, students gain insight into the engineering, data and decision-making systems that power self-driving vehicles.
Engineering in practice
Participants gain applied experience working with industry-relevant tools and technologies, including:
- Robot Operating System (ROS)
- Python and C++
- Sensor integration, perception and control logic
Working in teams, students design and refine autonomous driving behaviors, applying engineering concepts step by step to solve real-world constraints. The week culminates in an engaging final challenge where student-built systems navigate real-world-inspired scenarios.
Registration and schedule
Autonomous Driving Pre-College Program — Noncredit Program
REGISTRATION OPENS DECEMBER 1, 2026.
To start the registration process, please complete our interest form by July 5.
SCHEDULE: July 19-23, 2027, 9 a.m.-4 p.m., Monday-Friday
LOCATION: ICAT Lab at STAR Campus, University of Delaware, Newark, Del.
PRICE:
- Early Bird: $1995 (February 28) | No additional discounts applicable | Code: EBIRD
- Standard: $2250 (March 1-May 31)
- Late Registration: $2500 (June 1-July 7)
REGISTRATION CLOSES: July 5, 2027
NONCREDIT CONTACT HOURS: 3.0 CEUs | 30 noncredit contact hours
TECHNOLOGY REQUIREMENT: Students must bring their own laptop.
ACCOMODATIONS: Housing is not provided; rooms can be reserved at the Hyatt on Main Street for 20% off through the booking link provided upon registration. At least one guest in each room must be 21 or older.
LUNCH: Students should bring their own lunch for the first four days of the program. Lunch is provided on the final day of the program.
Financial options available
Only one discount or scholarship award can apply per registration.
DISCOUNTS: A 15% discount is available for dependents of military and veterans, UD employees and UD alumni, or two or more siblings registering from the same family. For details or to receive the discount code, please email continuing-ed@udel.edu.
University of Delaware, Professional and Continuing Studies is committed to making educational opportunities accessible to all students. Scholarships will be reviewed and awarded based on the degree of demonstrated financial need, in alignment with Federal TRIO guidelines. Because funding and capacity vary across our different pre-college offerings, scholarship awards are program-specific and may range from partial assistance (e.g., 25% of tuition) up to full program coverage (100%). To secure their enrollment, students awarded a 100% scholarship are required to submit a $100 commitment deposit; this deposit will be fully reimbursed upon the student's successful completion of the program. Priority is given to students who meet federal low-income guidelines, are potential first-generation college students or are currently enrolled in a recognized TRIO program. Awards are strictly need-based and are granted as funding permits. Pre-college program scholarship info
Pre-college program refund policy
Written cancellation requests must be submitted by email to continuing-ed@udel.edu.
- A full refund, less a $75 processing fee, will be issued for written cancellations received up to 60 days ahead of the program start date.
- A 50% refund, less a $75 processing fee, will be issued for written cancellations received between 59 and 30 days ahead of the program start date.
- No refunds will be issued for withdrawals received after 30 days ahead of the program start date.
The University of Delaware is not responsible for any costs incurred as a result of program cancellation or schedule changes. If this program is canceled by the University, a full refund is provided.
Registration by July 5 is required to order supplies.
See the Academy in Action
Get a glimpse of the hands-on learning and collaboration that define the Autonomous Driving Academy. This short video features participants engaging with cutting-edge technology, building skills and exploring real-world applications in autonomous systems.
Program Details
Recommended experience
The ideal candidates will have a background in robotics and proficiency in Python with some knowledge of coding in C++. Students will be given coding exercises but will not need to code from scratch. Instead, they will receive prompts where they can use resources like Google or ChatGPT for help.
Course outline
Monday
Topics:
- Introduction to the hardware of autonomous robots
- Safety protocols
- Vehicle control fundamentals
- Sensing technologies overview
Activities:
- Assembling autonomous robot kits in groups
- Testing the robot's control and reading sensor data
Tuesday
Topics:
- Autonomous driving system fundamentals
- Programming tools overview: ROS, Python, C++
- Key autonomous driving functions: mapping, localization, path planning
Activities:
- Installation of ROS and autonomous driving packages
Wednesday
Topics:
- Autonomous racing and parking systems
- Optimization techniques for racing, including trajectory optimization and reinforcement learning
Activities:
- Hands-on baseline implementation of autonomous racing application
- Optimization of the baseline implementation
Thursday
Topics:
- Autonomous parking systems
Activities:
- Continuing hands-on optimizing the racing system
- Hands-on autonomous parking system implementation
Friday
Competition Day
Participants will put their knowledge and skills to the test in an exciting, high-energy racing challenge. After four days of hands-on learning, they will race their autonomous vehicles on a track, showcasing their custom-built designs and problem-solving abilities. It’s not just about speed — teams will be judged on the creativity and technical execution of their systems, with the team achieving the fastest time taking home the win! This final event emphasizes real-world applications of autonomous driving technology, providing students with a unique opportunity to see their hard work come to life in a dynamic and competitive environment.
Learner outcomes
Participants in this program will:
- Develop skills in programming tools such as ROS, Python and C++, essential for implementing and troubleshooting autonomous driving algorithms.
- Implement and enhance autonomous parking and racing applications, focusing on performance optimization and efficiency.
- Apply theoretical knowledge in practical, hands-on projects that simulate real-world autonomous driving scenarios.
- Work effectively in teams to design, build and improve autonomous driving systems, fostering a collaborative learning environment.
- Prepare and deliver technical presentations showcasing project outcomes and innovations to an audience, honing communication skills.
- Gain insights into potential career paths in the rapidly growing autonomous driving and robotics sectors.
- Develop critical thinking and problem-solving abilities in a cutting-edge technological context.
- Enhance teamwork, leadership and communication skills through collaborative group projects.
Instructional team
Weisong Shi is an Alumni Distinguished Professor and the chair of the Department of Computer and Information Sciences at UD who founded the Connected and Autonomous Research Laboratory (CAR Lab) at UD in December 2017. Shi is an internationally renowned expert in edge computing, autonomous driving and connected health: His pioneer paper in the field, "Edge Computing: Vision and Challenges,” has been cited more than 7,500 times.
Before joining UD, Shi was a member of the computer science faculty at Wayne State University, where he held multiple administrative roles, including associate dean for research and graduate studies in the College of Engineering and interim chair of the computer science department. From 2013 to 2015, he served as a program director for the National Science Foundation (NSF). Currently, he is the editor in chief of Institute of Electrical and Electronics Engineers (IEEE) Internet Computing Magazine and Elsevier Smart Health. He is the founding steering committee chair of three conferences: the Association for Computing Machinery (ACM)/IEEE Symposium on Edge Computing (SEC), the IEEE/ACM International Conference on Connected Health (CHASE) and the IEEE International Conference on Mobility (MOST). Additionally, he is the general chair of ACM MobiCom ’24, the flagship conference on Mobile Computing and Wireless Networking. Shi is a fellow of IEEE, a distinguished scientist of ACM and a member of the NSF Computer and Information Science and Engineering Advisory Committee and Computing Community Consortium Council.
Yuxin Wang is a third-year doctoral student in the CAR Lab. Her research primarily focuses on autonomous vehicle storage systems, with an emphasis on building intelligent, scalable and sustainable storage platforms to support a variety of autonomous driving applications. She also works with real-world vehicles to develop and deploy autonomous driving systems and has collaborated with Autoware and Western Digital.
Mingyu Guo is a doctoral student in the CAR Lab. His research focuses on autonomous systems and efficient computing, with an emphasis on smart mobility and resource management for machine learning workloads. He works on developing smart autonomous wheelchairs for safe and reliable navigation and patient transportation in complex indoor environments. His research also investigates multi-tenant GPU resource scheduling and performance variability, with the goal of improving the predictability and efficiency of concurrent deep learning inference workloads on shared computing platforms.
