期刊
ACCIDENT ANALYSIS AND PREVENTION
卷 117, 期 -, 页码 410-426出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.aap.2018.01.040
关键词
In-vehicle collision avoidance assistance; Warning strategy/specificity; Head-up display (HUD) visualization; Hazardous urban incidents; Driving simulator experiment; Driver behavior/subjective acceptance evaluation
类别
资金
- German Federal Ministry for Economic Affairs and Energy [19S12009O]
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.
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