103 citations · 103 across the 6 of their papers we have counts for
7 papers
Spatial Constraint Generation for Motion Planning in Dynamic Environments
Han Hu, Peyman Yadmellat
This paper presents a novel method to generate spatial constraints for motion planning in dynamic environments. Motion planning methods for autonomous driving and mobile robots typ…
Multi-lane Cruising Using Hierarchical Planning and Reinforcement Learning
Kasra Rezaee, Peyman Yadmellat, Masoud S. Nosrati +3
Competent multi-lane cruising requires using lane changes and within-lane maneuvers to achieve good speed and maintain safety. This paper proposes a design for autonomous multi-lan…
How To Not Drive: Learning Driving Constraints from Demonstration
Kasra Rezaee, Peyman Yadmellat
We propose a new scheme to learn motion planning constraints from human driving trajectories. Behavioral and motion planning are the key components in an autonomous driving system.…
Motion Planning for Autonomous Vehicles in the Presence of Uncertainty Using Reinforcement Learning
Kasra Rezaee, Peyman Yadmellat, Simon Chamorro
Motion planning under uncertainty is one of the main challenges in developing autonomous driving vehicles. In this work, we focus on the uncertainty in sensing and perception, resu…
CoachNet: An Adversarial Sampling Approach for Reinforcement Learning
Elmira Amirloo Abolfathi, Jun Luo, Peyman Yadmellat +1
Despite the recent successes of reinforcement learning in games and robotics, it is yet to become broadly practical. Sample efficiency and unreliable performance in rare but challe…
SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving
Ming Zhou, Jun Luo, Julian Villella +34
Multi-agent interaction is a fundamental aspect of autonomous driving in the real world. Despite more than a decade of research and development, the problem of how to competently i…