@inproceedings{c602c3cef0bb42479d2f2709c36b87dd,
title = "Integrating Trust in Automation into Driver State Monitoring Systems",
abstract = "Inappropriate trust in highly automated vehicles (HAVs) has been identified as one of the causes in several accidents [1--3]. These accidents have evidenced the need to include a Driver State Monitoring System (DSMS) [4] into those HAVs which may require occasional manual driving. DSMS make use of several psychophysiological sensors to monitor the drivers' state, and have already been included in current production vehicles to detect drowsiness, fatigue and distractions [5]. However, DSMS have never been used to monitor Trust in Automation (TiA) states within HAVs yet. Based on recent findings, this paper proposes a new methodology to integrate TiA state-classification into DSMSs for future vehicles.",
keywords = "Trust in Automation, Driver State Monitoring Systems, Highly automated vehicles, Machine learning",
author = "Jaume Perello-March and Christopher Burns and Mark Elliott and Stewart Birrell",
year = "2019",
month = jul,
day = "25",
doi = "10.1007/978-3-030-25629-6_53",
language = "English",
isbn = "978-3-030-25628-9",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer",
pages = "344--349",
editor = "Tareq Ahram and Redha Taiar and Serge Colson and Arnaud Choplin",
booktitle = "Human Interaction and Emerging Technologies (IHIET 2019)",
address = "United Kingdom",
note = "1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019 ; Conference date: 22-08-2019 Through 24-08-2019",
}