Intelligent scheduling for in-car notifications.
View / Open Files
Authors
Wright, Jonathan
Stafford-Fraser, Quentin
Mahmoud, Marwa
Dias, Eduardo
Publication Date
2017-09Journal Title
RTSI
Conference Name
IEEE Forum on Research and Technologies for Society and Industry
ISBN
978-1-5386-3906-1
Publisher
IEEE
Pages
1-6
Type
Conference Object
Metadata
Show full item recordCitation
Wright, J., Stafford-Fraser, Q., Mahmoud, M., Robinson, P., Dias, E., & Skrypchuk, L. (2017). Intelligent scheduling for in-car notifications.. RTSI, 1-6. https://doi.org/10.1109/RTSI.2017.8065957
Abstract
The process of driving a car involves a cognitive
load that varies over time. Additional load comes from secondary
factors not directly associated with the driving process, including
navigation devices, entertainment systems and the car’s own
warnings. In this paper, we present a framework for intelligent
scheduling of in-car notifications based on the driver’s estimated
cognitive load. As the single channel for communication, it
reschedules the notifications using a priority queue, and relays
them to the driver based on the urgency of the notification and
the overall estimated cognitive load being experienced by the
driver at any given moment. We evaluate our system using a
dataset collected from a car’s CAN bus during multiple onroad trials and show that our proposed approach reduces the
number of simultaneous calls on the driver’s attention during the
driving task. We also demonstrate that our intelligent scheduling
significantly reduces the maximum cognitive load experienced by
the driver and the frequency with which high loads occur.
Identifiers
External DOI: https://doi.org/10.1109/RTSI.2017.8065957
This record's URL: https://www.repository.cam.ac.uk/handle/1810/284533
Rights
Licence:
http://www.rioxx.net/licenses/all-rights-reserved
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: support@repository.cam.ac.uk