Several recent mobile operating systems allow users to configure the smartphone into a “driving mode”. This mode suppresses the smartphone's incoming SMS/call notifications so that it does not distract driving activities. However, currently available driving mode implementations keep all notifications from being delivered, which decreases its practical usability. We identify this as a problem and perform a survey on the preference of drivers on incoming smartphone notifications when driving. Specifically, we ask 74 survey participants on the need for a smartphone driving mode and also the need to differentiate incoming call/SMS contacts when the driving mode operates. Our results show that the need for a designated driving mode scored on average 4.3 on a 0-6 scale. When asked what criteria would be ideal for differentiating the contacts for notification prioritization, ∼59% chose the communication frequency with the contact as the main criteria. Overall, our results suggests for a careful design when implementing smartphone driving mode for incoming notification control.
|Title of host publication||UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||4|
|Publication status||Published - 2018 Oct 8|
|Event||2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 - Singapore, Singapore|
Duration: 2018 Oct 8 → 2018 Oct 12
|Name||UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers|
|Other||2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018|
|Period||18/10/8 → 18/10/12|
Bibliographical noteFunding Information:
This research was supported by the MIST(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW supervised by the IITP (2015-0-00908) and also by IITP grant funded by MSIT (No.2017-0-00501, Development of Self-learnable common IoT SW Engine).
All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Information Systems