CSEE student investigates public acceptance and trust of shared autonomous vehicles

One of his current research projects investigates how passengers experience riding a self-driving shuttle in Buffalo, New York. Shahin aims to uncover what shapes acceptance and trust in shared autonomous vehicles and how shuttle operations and environmental conditions can affect passenger acceptance and trust.

“Understanding public acceptance is critical for the future of autonomous vehicles. To ensure the widespread use of shared autonomous vehicles and bring their benefits to the public, understanding acceptance is a major priority,” says Shahin.

Alongside his main project, Shahin is also advancing his technical expertise in simulation and modeling. He is experimenting with computer vision models such as You Only Look Once, a computer vision algorithm that uses deep learning to detech objects in real time to identify and locate muliple objects in images or videos, to assess road conditions and infrastructure safety.

In an earlier machine learning course, his team developed a pothole detection and severity assessment model that was selected among the best projects in class, an experience that motivated his interest in applying AI to transportation challenges. Building on this foundation, Shahin is now working to strengthen his skills in reinforcement learning, preparing to conduct future research on AI-driven applications in transportation systems.

Shahin plans to continue his career in academia and applied research with the goal of contributing to smarter, safer, more sustainable and people-centered transportation systems.

“I’ve always been interested in how technology can improve the way we move by integrating advanced modeling with human-centered design. I hope to support transportation solutions that balance efficiency, safety and public trust,” Shahin says.