1 citations · 1 across the 13 of their papers we have counts for
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RLFTSim: Realistic and Controllable Multi-Agent Traffic Simulation via Reinforcement Learning Fine-Tuning
Ehsan Ahmadi, Hunter Schofield, Behzad Khamidehi +5
Supervised open-loop training has been widely adopted for training traffic simulation models; however, it fails to capture the inherently dynamic, multi-agent interactions common i…
Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories
Niloufar Saeidi Mobarakeh, Behzad Khamidehi, Chunlin Li +6
The primary goal of motion planning is to generate safe and efficient trajectories for vehicles. Traditionally, motion planning models are trained using imitation learning to mimic…
Validity Learning on Failures: Mitigating the Distribution Shift in Autonomous Vehicle Planning
Fazel Arasteh, Mohammed Elmahgiubi, Behzad Khamidehi +4
The planning problem constitutes a fundamental aspect of the autonomous driving framework. Recent strides in representation learning have empowered vehicles to comprehend their sur…
Distributed Deep Reinforcement Learning for Intelligent Traffic Monitoring with a Team of Aerial Robots
Behzad Khamidehi, Elvino S. Sousa
This paper studies the traffic monitoring problem in a road network using a team of aerial robots. The problem is challenging due to two main reasons. First, the traffic events are…
Dynamic Resource Management for Providing QoS in Drone Delivery Systems
Behzad Khamidehi, Majid Raeis, Elvino S. Sousa
Drones have been considered as an alternative means of package delivery to reduce the delivery cost and time. Due to the battery limitations, the drones are best suited for last-mi…