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Journal Article


Winkler S, Kazazi J, Vollrath M. Accid. Anal. Prev. 2018; 117: 410-426.


Technische Universität Braunschweig, Department of Engineering and Traffic Psychology, Gaußstraße 23, 38106 Braunschweig, Germany.


(Copyright © 2018, Elsevier Publishing)






Technological advances allow supporting drivers in a multitude of occasions, ranging from comfort enhancement to collision avoidance, for example through driver warnings, which are especially crucial for traffic safety. This psychological driving simulator experiment investigated how to warn drivers visually in order to prevent accidents in various safety-critical situations. Collision frequencies, driving behavior and subjective evaluations of situation criticality, warning understandability and helpfulness of sixty drivers were measured in two trials of eight scenarios each (within-subjects factors). The warning type in the head-up display (HUD) varied (between-subjects) in its strategy (attention-/reaction-oriented) and specificity (generic/specific) over four warning groups and a control group without a warning. The results show that the scenarios differed in their situation criticality and drivers adapted their reactions accordingly, which underlines the importance of testing driver assistance systems in diverse scenarios. Besides some learning effects over the trials, all warned drivers showed faster and stronger brake reactions. Some warning concepts were understood better than others, but all were accepted. Generic warnings were effective, yet the warning strategy should adapt to situation requirements and/or driver behavior. A stop symbol as reaction generic warning is recommendable for diverse kinds of use cases, leading to fast and strong reactions. However, for rather moderate driver reactions an attention generic approach with a caution symbol might be more suitable. Further research should investigate multi-stage warnings with adaptive strategies for application to various situations including other modalities and false alarms.

Copyright © 2018 Elsevier Ltd. All rights reserved.

Language: en


Driver behavior/subjective acceptance evaluation; Driving simulator experiment; Hazardous urban incidents; Head-up display (HUD) visualization; In-vehicle collision avoidance assistance; Warning strategy/specificity


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