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International Journal of Human–Computer Interaction Volume 37, 2021 - Issue 4: Human-Computer Interaction in Autonomous Vehicle and Mobility
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Research Article

Warning Apps for Road Safety: A Technological and Economical Perspective for Autonomous Driving – The Warning Task in the Transition from Human Driver to Automated Driving

Johanna Tragera Institute for Applied Informatics, Technology Campus Freyung, Deggendorf Institute of Technology, Freyung, GermanyView further author information
,
Lenka Kalováa Institute for Applied Informatics, Technology Campus Freyung, Deggendorf Institute of Technology, Freyung, GermanyView further author information
,
Raphaela Paganya Institute for Applied Informatics, Technology Campus Freyung, Deggendorf Institute of Technology, Freyung, Germany;b Department of Geoinformatics Z_GIS, Salzburg University, Salzburg, AustriaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-1746-1906View further author information
ORCID Icon &
Wolfgang Dornera Institute for Applied Informatics, Technology Campus Freyung, Deggendorf Institute of Technology, Freyung, GermanyORCID Iconhttps://orcid.org/0000-0003-3324-2316View further author information
ORCID Icon
Pages 363-377 | Published online: 19 Jan 2021

Figures & data

Table 1. Different types of warning apps and their classification

Figure 1. Categorization of warning apps according to market spread and functionality – bubble size correlates with download numbers

Figure 1. Categorization of warning apps according to market spread and functionality – bubble size correlates with download numbers

Table 2. Scenario partitioning depending on the HCI

Table 3. Evaluation of scenarios II and III for the classified warning apps

Figure 2. User interactions due to the scenarios I, II and III of driving automatization levels

Figure 2. User interactions due to the scenarios I, II and III of driving automatization levels

Figure 3. Frequency of usage

Figure 3. Frequency of usage

Figure 4. Driving behavior in case of a warning

Figure 4. Driving behavior in case of a warning

Figure 5. Frequency of usage combined with the perception about the amount of received warnings*

*combination of Q 1 and Q 2, remaining answers not included due to the low app experience (meaning Q 1 answers: usage only once/never/only downloaded because of the wildlife-vehicle service); only counted if in both section answers were filled in
Figure 5. Frequency of usage combined with the perception about the amount of received warnings*

Table 4. Results of Q5: In which warning source the app users have the highest trust in

Table 5. Applicability and success evaluation for the selected Business Models for warning services for autonomous driving

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