Multidimensional Prediction; Autonomous Driving Simulator

Cui, Xuhao, School of Engineering and Applied Science, University of Virginia
Wang, Tianhao, EN-Comp Science Dept, University of Virginia
Stafford, William, EN-Engineering and Society, University of Virginia

Self-driving cars are complex and need thorough testing to make sure they are safe before
they are used in public. Testing them in real-life situations is risky and very expensive. My
project aims to solve these problems by creating an advanced simulator for self-driving
cars. This simulator uses the latest machine learning techniques and realistic data to
simulate different driving conditions, traffic situations, and how pedestrians behave. This
lets us test self-driving cars safely in a virtual world, including in rare but dangerous
situations that don’t happen often in real life but are important for testing. This method
cuts down on the need for physical testing, which lowers costs and speeds up
development. We use high-quality graphics technology to make sure the simulations look
and feel real, which helps in testing how the cars perceive their environment.

BS (Bachelor of Science)
Simulator, AI, Machine learning
Issued Date: