Publikation

Local Danger Warnings for Drivers: The Effect of Modality and Level of Assistance on Driver Reaction

Yujia Cao, Angela Mahr, Sandro Castronovo, Mariet Theune, Christoph Stahl, Christian Müller

In: Proceedings of the International Conference on Intelligent User Interfaces. International Conference on Intelligent User Interfaces (IUI-10) February 7-10 Hong Kong China ACM 2/2010.

Abstrakt

Local danger warning is an important function of Advanced Driver Assistance Systems (ADAS) to improve the safety of driving. The user interface (the warning presentation) is particularly crucial to a successful danger avoidance. We present a user study investigating various warning presentations using a scenario of emergent road obstacles. Two presentation factors were selected: modality and level of assistance. The modality factor had 4 variants: speech warning, visual and speech warning, visual warning with blinking cue, and visual warning with sound cue. The level of assistance varied between with or without action suggestions (AS). In accordance with the ISO usability model, a total of 6 measurements were derived to assess the effectiveness and efficiency of the warnings and the drivers' satisfaction. Results indicate that the combination of speech and visual modality leads to the best performance as well as the highest satisfaction. In contrast, purely auditory and purely visual modalities were both insufficient for presenting high-priority warnings. AS generally improved the usability of the warnings especially when they were accompanied by supporting information so that drivers could validate the suggestions.

cao_et_al_2010_iui.pdf (pdf, 1 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence