TY - GEN
T1 - Examining speech-based auditory alerts for intersection collision warning systems using a driving simulator
AU - O'Brien, West M.
AU - Wu, Xingwei
AU - Boyle, Linda Ng
N1 - Publisher Copyright:
© 2018 by Human Factors and Ergonomics Society (HFES). All rights reserved.
PY - 2018
Y1 - 2018
N2 - Collision warning systems alert drivers of potential safety hazards. Forward collision warning (FCW) systems have been widely implemented and studied. However, intersection collision warning systems (ICWS), such as intersection movement assist (IMA), are more complex. Additional studies are needed to identify the best alert for directing the driver toward the hazard. A driving simulator study with 48 participants was conducted to examine three speech-based auditory alerts (general, directional, and command) in a simulated red light running (RLR) collision scenario. The command alert that informed the drivers to brake was the most effective in reducing the number of collisions. The post-drive questionnaire showed that drivers also rated the brake alert to be best in terms of interpretation (based on the Kruskal Wallis test). This study provides insight into the performance of different types of speech-based alerts for an intersection collision warning system and can provide guidance for future studies.
AB - Collision warning systems alert drivers of potential safety hazards. Forward collision warning (FCW) systems have been widely implemented and studied. However, intersection collision warning systems (ICWS), such as intersection movement assist (IMA), are more complex. Additional studies are needed to identify the best alert for directing the driver toward the hazard. A driving simulator study with 48 participants was conducted to examine three speech-based auditory alerts (general, directional, and command) in a simulated red light running (RLR) collision scenario. The command alert that informed the drivers to brake was the most effective in reducing the number of collisions. The post-drive questionnaire showed that drivers also rated the brake alert to be best in terms of interpretation (based on the Kruskal Wallis test). This study provides insight into the performance of different types of speech-based alerts for an intersection collision warning system and can provide guidance for future studies.
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M3 - Conference contribution
AN - SCOPUS:85072756802
T3 - Proceedings of the Human Factors and Ergonomics Society
SP - 1939
EP - 1943
BT - 62nd Human Factors and Ergonomics Society Annual Meeting, HFES 2018
PB - Human Factors and Ergonomics Society Inc.
T2 - 62nd Human Factors and Ergonomics Society Annual Meeting, HFES 2018
Y2 - 1 October 2018 through 5 October 2018
ER -