5 citations · 5 across the 6 of their papers we have counts for
6 papers
MiMo-Embodied: X-Embodied Foundation Model Technical Report
Xiaoshuai Hao, Lei Zhou, Zhijian Huang +41
We open-source MiMo-Embodied, the first cross-embodied foundation model to successfully integrate and achieve state-of-the-art performance in both Autonomous Driving and Embodied A…
Sim-on-Wheels: Physical World in the Loop Simulation for Self-Driving
Yuan Shen, Bhargav Chandaka, Zhi-hao Lin +4
We present Sim-on-Wheels, a safe, realistic, and vehicle-in-loop framework to test autonomous vehicles' performance in the real world under safety-critical scenarios. Sim-on-wheels…
CoCAtt: A Cognitive-Conditioned Driver Attention Dataset (Supplementary Material)
Yuan Shen, Niviru Wijayaratne, Pranav Sriram +3
The task of driver attention prediction has drawn considerable interest among researchers in robotics and the autonomous vehicle industry. Driver attention prediction can play an i…
CoCAtt: A Cognitive-Conditioned Driver Attention Dataset
Yuan Shen, Niviru Wijayaratne, Pranav Sriram +3
The task of driver attention prediction has drawn considerable interest among researchers in robotics and the autonomous vehicle industry. Driver attention prediction can play an i…
Building Mental Models through Preview of Autopilot Behaviors
Yuan Shen, Niviru Wijayaratne, Katherine Driggs-Campbell
Effective human-vehicle collaboration requires an appropriate un-derstanding of vehicle behavior for safety and trust. Improvingon our prior work by adding a future prediction modu…
AutoPreview: A Framework for Autopilot Behavior Understanding
Yuan Shen, Niviru Wijayaratne, Peter Du +2
The behavior of self driving cars may differ from people expectations, (e.g. an autopilot may unexpectedly relinquish control). This expectation mismatch can cause potential and ex…