Better Driving and Recall When In-car Information Presentation Uses Situationally-Aware Incremental Speech Output Generation

Kennington, Casey and Kousidis, Spyridon and Baumann, Timo and Buschmeier, Hendrik and Kopp, Stefan and Schlangen, David

It is established that driver distraction is the result of sharing cognitive resources between the primary task (driving) and any other secondary task. In the case of holding conversations, a human passenger who is aware of the driving conditions can choose to interrupt his speech in situations potentially requiring more attention from the driver, but in-car information systems typically do not exhibit such sensitivity. We have designed and tested such a system in a driving simulation environment. Unlike other systems, our system delivers infor- mation via speech (calendar entries with scheduled meetings) but is able to react to signals from the environment to interrupt when the driver needs to be fully attentive to the driving task and subsequently resume its delivery. Distraction is measured by a secondary short-term memory task. In both tasks, drivers perform significantly worse when the system does not adapt its speech, while they perform equally well to control conditions (no concurrent task) when the system intelligently interrupts and resumes.

In AutomotiveUI 2014: Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications , 2014
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@inproceedings{Kennington-2014,
  author = {Kennington, Casey and Kousidis, Spyridon and Baumann, Timo and Buschmeier, Hendrik and Kopp, Stefan and Schlangen, David},
  booktitle = {AutomotiveUI 2014: Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications},
  location = {Seattle, Washington, USA},
  pages = {7:1--7:7},
  title = {{Better Driving and Recall When In-car Information Presentation Uses Situationally-Aware Incremental Speech Output Generation}},
  doi = {10.1145/2667317.2667332},
  year = {2014},
  topics = {},
  domains = {},
  approach = {},
  project = {}
}