Human in the Loop Control
Victor Shia
TeleImmersion Lab
BEARS 2012
TeleImmersion Lab
Tai Chi Teaching
Remote Dancing
Virtual Choreography
(UCB, Stanford Univ.)
(UCB, UIUC)
(UCB, UIUC)
Portable Teleimmersion
Virtual Geology
Virtual Archeology
(UCB)
(UCB, UC Davis)
(UCB, UC Merced, UC Davis)
Human-in-the-Loop Control
Control Theory
Human input
Not completely predictable
In certain scenarios, can be somewhat
predicted
Can we develop control algorithms to keep
systems safe while incorporating nominal
human input?
Past Work
Autonomous cars
Semi-autonomous cars
Contributions
Develop a model for the driver using data learned
over time
Apply this model to semi-autonomous cars and
intervention
Illustrate that incorporating human behavior
improves the performance of a semi-autonomous
architecture
Vasudevan R., Shia V., et al. Safe Semi-Autonomous Control with Enhanced Driver
Modeling, ACC2012 (accepted)
Experimental Setup
Models : Results
• Model 1: current
techniques (no driver
modeling)
• Model 2: driver model
created from past
actions and outside
environment
Model
1
Normal
Model
2
Distracted
Models: Metric
Accuracy of
prediction
Precision of
prediction
Recall of
intervention
function
Precision of
intervention
function
Model 1
1
0
1
0.0031
Model 2
0.81
0.82
1
0.68
Conclusion
Driver modeling can improve the performance
for the semi-autonomous framework
Currently implementing model learning and
prediction system in real time
Thank You
475 Hearst Memorial Building
Demos/Poster
Gregorij Kurillo
Aaron Bestick
Daniel Aranki
Acknowledgments: NSF, NSF Grant #0903711 – CiBER-IGERT
Collaborators: Yigi Gao, Andrew Gray, Theresa Lin, Prof.
Francesco Borrelli
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