83 citations · 102 across the 9 of their papers we have counts for
9 papers
Safe POMDP Online Planning among Dynamic Agents via Adaptive Conformal Prediction
Shili Sheng, Pian Yu, David Parker +2
Online planning for partially observable Markov decision processes (POMDPs) provides efficient techniques for robot decision-making under uncertainty. However, existing methods fal…
Trust-Aware Motion Planning for Human-Robot Collaboration under Distribution Temporal Logic Specifications
Pian Yu, Shuyang Dong, Shili Sheng +2
Recent work has considered trust-aware decision making for human-robot collaboration (HRC) with a focus on model learning. In this paper, we are interested in enabling the HRC syst…
Safe POMDP Online Planning via Shielding
Shili Sheng, David Parker, Lu Feng
Partially observable Markov decision processes (POMDPs) have been widely used in many robotic applications for sequential decision-making under uncertainty. POMDP online planning a…
Enjoy the Ride Consciously with CAWA: Context-Aware Advisory Warnings for Automated Driving
Erfan Pakdamanian, Erzhen Hu, Shili Sheng +3
In conditionally automated driving, drivers decoupled from driving while immersed in non-driving-related tasks (NDRTs) could potentially either miss the system-initiated takeover r…
A Study on Learning and Simulating Personalized Car-Following Driving Style
Shili Sheng, Erfan Pakdamanian, Kyungtae Han +2
Automated vehicles are gradually entering people's daily life to provide a comfortable driving experience for the users. The generic and user-agnostic automated vehicles have limit…
DeepTake: Prediction of Driver Takeover Behavior using Multimodal Data
Erfan Pakdamanian, Shili Sheng, Sonia Baee +3
Automated vehicles promise a future where drivers can engage in non-driving tasks without hands on the steering wheels for a prolonged period. Nevertheless, automated vehicles may…
Planning for Automated Vehicles with Human Trust
Shili Sheng, Erfan Pakdamanian, Kyungtae Han +4
Recent work has considered personalized route planning based on user profiles, but none of it accounts for human trust. We argue that human trust is an important factor to consider…
Probabilistic Conditional System Invariant Generation with Bayesian Inference
Meriel Stein, Sebastian Elbaum, Lu Feng +1
Invariants are a set of properties over program attributes that are expected to be true during the execution of a program. Since developing those invariants manually can be costly…
A Case Study of Trust on Autonomous Driving
Shili Sheng, Erfan Pakdamanian, Kyungtae Han +4
As autonomous vehicles have benefited the society, understanding the dynamic change of humans' trust during human-autonomous vehicle interaction can help to improve the safety and…