Maryland Robotics Student Seminar: Modeling Human Driver Behavior in Dense Urban Traffic Environment
Friday, March 5, 2021
301 405 8870
Modeling Human Driver Behavior in Dense Urban Traffic Environments Using Graph Theory
Ph.D Student, Computer Science
Advisor: Dr. Dinesh Manocha
Studies have shown that autonomous vehicles (AVs) behave conservatively in a traffic environment composed of human drivers and do not adapt to local conditions and socio-cultural norms. It is known that socially aware AVs can be designed if there exists a mechanism to understand the behaviors of human drivers. We present an approach that leverages graph theory and machine learning to predict the behaviors of human drivers. The underlying intuition of our approach is similar to how humans implicitly interpret the behaviors of drivers on the road by only observing the trajectories of their vehicles. We use graph-theoretic tools to extract driver behavior features from the trajectories and obtain a computational mapping between the extracted trajectory of a vehicle in traffic and the driver behaviors. Compared to prior approaches in this domain, we prove that our method is robust, general, and extendable to broad-ranging applications such as autonomous navigation. We evaluate our approach on real-world traffic datasets captured in the U.S., India, China, and Singapore, as well as in simulation.
About the Robotics Student Seminars
The Robotics Student Seminars at the University of Maryland College Park are a student-run series of talks given by current robotics students.
The purpose of these talks is to:
- Encourage interaction between Robotics students from different subfields;
- Provide an opportunity for Robotics students to be aware of and possibly get involved in the research their peers are conducting;
- Provide an opportunity for Robotics students to receive feedback on their current research;
- Provide speaking opportunities for Robotics students.