Integrating Neurophysiological Sensors and Driver Models for Safe and Performant Automated Vehicle Control in Mixed Traffic
| Title | Integrating Neurophysiological Sensors and Driver Models for Safe and Performant Automated Vehicle Control in Mixed Traffic |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Werner Damm, Martin Fränzle, Andreas Lüdtke, Jochem W. Rieger, Alexander Trende, Anirudh Unni |
| Conference Name | IEEE Intelligent Vehicles Symposium |
| Publisher | IEEE |
| Conference Location | Paris, France |
| Keywords | automotive, detection, driver models, driving behavior modeling, HAV, Highly Automated Vehicles, Human Behavior, human interaction, human operated traffic, neurophysiological sensors, Performance optimization, Safety, Transportation |
| Abstract | In the future, mixed traffic Highly Automated Vehicles (HAV) will have to resolve interactions with human operated traffic. A particular problem for HAVs is the 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. |
| URL | https://arxiv.org/pdf/1902.04929.pdf |
| Citation Key | node-62084 |