77 citations · 219 across the 30 of their papers we have counts for
5 papers · 2 filters
Trajectory Planning for Autonomous Vehicles Using Hierarchical Reinforcement Learning
Kaleb Ben Naveed, Zhiqian Qiao, John M. Dolan
Planning safe trajectories under uncertain and dynamic conditions makes the autonomous driving problem significantly complex. Current sampling-based methods such as Rapidly Explori…
Safe Trajectory Planning Using Reinforcement Learning for Self Driving
Josiah Coad, Zhiqian Qiao, John M. Dolan
Self-driving vehicles must be able to act intelligently in diverse and difficult environments, marked by high-dimensional state spaces, a myriad of optimization objectives and comp…
Behavior Planning at Urban Intersections through Hierarchical Reinforcement Learning
Zhiqian Qiao, Jeff Schneider, John M. Dolan
For autonomous vehicles, effective behavior planning is crucial to ensure safety of the ego car. In many urban scenarios, it is hard to create sufficiently general heuristic rules,…
Safe planning and control under uncertainty for self-driving
Shivesh Khaitan, Qin Lin, John M. Dolan
Motion Planning under uncertainty is critical for safe self-driving. In this paper, we propose a unified obstacle avoidance framework that deals with 1) uncertainty in ego-vehicle…
Safe Planning for Self-Driving Via Adaptive Constrained ILQR
Yanjun Pan, Qin Lin, Het Shah +1
Constrained Iterative Linear Quadratic Regulator (CILQR), a variant of ILQR, has been recently proposed for motion planning problems of autonomous vehicles to deal with constraints…