[Seminar] Transportation Safety in the Modern World
Friday, September 27, 2024
11:00 am - 12:00 pm
Speaker
Senior Research Associate
Virginia Tech Transportation Institute
Location
PGH 232
Abstract
In the rapidly evolving landscape of transportation, safety remains a paramount concern, especially as emerging technologies like automated driving systems (ADS) and advanced driver-assistance systems (ADAS) become integral to our daily lives. In this talk, we will navigate the complexities of ensuring safety in modern transportation systems through data analytics, artificial intelligence, naturalistic driving studies, data privacy, and health monitoring. We will discuss how a multi-disciplinary approach is required to address challenges in transportation safety and its intricate relationship with AI ethics, system reliability, and human factors engineering. We will cover the latest research in the field, highlight practical and open challenges, and explore the potential scope of research that can shape the future of a safe, reliable, and equitable transportation ecosystem.
About the Speaker
Dr. Abhijit Sarkar is a Senior Research Associate in the Division of Data & Analytics at Virginia Tech Transportation Institute. He currently leads the computer vision and machine learning group. His research focuses on the application of computer vision, machine learning, and time series data analysis for transportation safety and mobility. His recent projects involve perception of autonomous systems, sensor fusion, driver distraction, data deidentification, cardiac biometrics, human psychophysiology, operation of heave vehicles, intersection safety, and naturalistic driving data. As a PI and Co-PI he has led projects with total value of more than $18 Million. These projects were funded by NHTSA, FHWA, NSF, FMCSA, Safe-D UTC, NASA, NCHRP, and multiple private sponsors. He earned his Ph.D. from Virginia Tech, USA, his master鈥檚 from IIT Kharagpur, and his bachelor鈥檚 from Jadavpur University, India, all in Electrical Engineering.
- Location
- PGH 232