3 papers
cs.RO2026
What's Hidden Matters: Identifying Planning-Critical Occluded Agents using Vision-Language Models
Amirhosein Chahe, Tyler Naes, Jovin D'sa +4
Autonomous vehicles must safely navigate complex environments where planning-critical agents may be hidden from view. Current approaches often treat all occlusions with uniform con…
cs.RO2024
Modeling the Lane-Change Reactions to Merging Vehicles for Highway On-Ramp Simulations
Dustin Holley, Jovin Dsa, Hossein Nourkhiz Mahjoub +4
Enhancing simulation environments to replicate real-world driver behavior is essential for developing Autonomous Vehicle technology. While some previous works have studied the yiel…
cs.RO2023
Active Learning with Dual Model Predictive Path-Integral Control for Interaction-Aware Autonomous Highway On-ramp Merging
Jacob Knaup, Jovin D'sa, Behdad Chalaki +4
Merging into dense highway traffic for an autonomous vehicle is a complex decision-making task, wherein the vehicle must identify a potential gap and coordinate with surrounding hu…