105 citations · 134 across the 8 of their papers we have counts for
8 papers · 1 filter
Guiding End-to-End Driving Models with Endpoint-Constrained Trajectory Optimization
Brayden Zhang, Mahsa Golchoubian, Igor Gilitschenski +2
End-to-end driving policies are commonly trained through open-loop behavior cloning, yet they must ultimately operate in closed-loop when deployed on a vehicle, creating a fundamen…
Belief-Aware Influence and Trust (BAIT): Shaping Human Belief During Repeated Human-Robot Interaction
Ye-Ji Mun, Mahsa Golchoubian, Shahabedin Sagheb +4
Repeated human-robot interaction (HRI) requires proactively accounting for humans who continually adapt to evolving beliefs about the robot. Prior frameworks often treat encounters…
Dynamics Distillation for Efficient and Transferable Control Learning
Xunjiang Gu, Kashyap Chitta, Mahsa Golchoubian +2
Robust control policy learning for autonomous driving requires training environments to be both physically realistic and computationally scalable, properties that existing simulato…
Rethinking Gaussian Trajectory Predictors: Calibrated Uncertainty for Safe Planning
Fatemeh Cheraghi Pouria, Mahsa Golchoubian, Katherine Driggs-Campbell
Accurate trajectory prediction is critical for safe autonomous navigation in crowded environments. While many trajectory predictors output Gaussian distributions to represent the m…
Characterizing Structured versus Unstructured Environments based on Pedestrians' and Vehicles' Motion Trajectories
Mahsa Golchoubian, Moojan Ghafurian, Nasser Lashgarian Azad +1
Trajectory behaviours of pedestrians and vehicles operating close to each other can be different in unstructured compared to structured environments. These differences in the motio…
Uncertainty-Aware DRL for Autonomous Vehicle Crowd Navigation in Shared Space
Mahsa Golchoubian, Moojan Ghafurian, Kerstin Dautenhahn +1
Safe, socially compliant, and efficient navigation of low-speed autonomous vehicles (AVs) in pedestrian-rich environments necessitates considering pedestrians' future positions and…
Polar Collision Grids: Effective Interaction Modelling for Pedestrian Trajectory Prediction in Shared Space Using Collision Checks
Mahsa Golchoubian, Moojan Ghafurian, Kerstin Dautenhahn +1
Predicting pedestrians' trajectories is a crucial capability for autonomous vehicles' safe navigation, especially in spaces shared with pedestrians. Pedestrian motion in shared spa…
Pedestrian Trajectory Prediction in Pedestrian-Vehicle Mixed Environments: A Systematic Review
Mahsa Golchoubian, Moojan Ghafurian, Kerstin Dautenhahn +1
Planning an autonomous vehicle's (AV) path in a space shared with pedestrians requires reasoning about pedestrians' future trajectories. A practical pedestrian trajectory predictio…