Integrating Neurophysiological Sensors and Driver Models for Safe and Performant Automated Vehicle Control in Mixed Traffic

被引：0

作者：

Damm, W. ^{[1
]}

Fraenzle, M. ^{[1
]}

Luedtke, A. ^{[2
]}

Rieger, J. W. ^{[3
]}

Trende, A. ^{[2
]}

Unni, A. ^{[3
]}

机构：

[1] Carl von Ossietzky Univ Oldenburg, Dept Comp Sci, D-26121 Oldenburg, Germany

[2] OFFIS, D-26121 Oldenburg, Germany

[3] Carl von Ossietzky Univ Oldenburg, Dept Psychol, D-26129 Oldenburg, Germany

来源：

2019 30TH IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV19) | 2019年

关键词：

GAP ACCEPTANCE; SPECTROSCOPY;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：82 / 89

页数：8

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