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Integrating Neurophysiological Sensors and Driver Models for Safe and Performant Automated Vehicle Control in Mixed Traffic
February 13, 2019 Β· Declared Dead Β· π 2019 IEEE Intelligent Vehicles Symposium (IV)
"No code URL or promise found in abstract"
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Authors
Werner Damm, Martin FrΓ€nzle, Andreas LΓΌdtke, Jochem W. Rieger, Alexander Trende, Anirudh Unni
arXiv ID
1902.04929
Category
cs.HC: Human-Computer Interaction
Citations
17
Venue
2019 IEEE Intelligent Vehicles Symposium (IV)
Last Checked
4 months ago
Abstract
In future mixed traffic Highly Automated Vehicles (HAV) will have to resolve interactions with human operated traffic. A particular problem for HAVs is detection of human states influencing safety critical decisions and driving behavior of humans. We demonstrate the value proposition of neurophysiological sensors and driver models for optimizing performance of HAVs under safety constraints in mixed traffic applications.
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