Mathworks

Emerging mobility systems, e.g., connected and automated vehicles (CAVs), shared mobility, and electric vehicles, provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make decisions for improving safety and transportation efficiency. However, before connectivity and automation are deployed en masse, a thorough evaluation of CAVs is required, ranging from numerical simulation to real-world public roads. The assessment of the performance of CAVs in scaled testbeds has recently gained momentum due to the flexibility they offer to conduct quick, repeatable experiments that could go one step beyond simulation. The research objectives of this project are to use the Information and Decision Science Lab Scaled Smart City (IDS3C), a 1:25 research and educational scaled robotic testbed that is capable of replicating different real-world urban traffic scenarios, to (1) develop novel approaches on model predictive control in autonomous driving systems aimed at creating new features in Mathworks’ related products, (2) validate Mathworks’ virtual sensors by using machine learning techniques and synthetic data created in IDS3C, (3) develop educational modules for Mathworks, and (4) develop a digital twin of IDS3C (a virtual testbed) that can be used for student competitions.