DrivingBeacon: Driving Behaviour Change Support System Considering Mobile Use and Geo-information

Jawwad Baig, Guanyi Chen, Chenghua Lin, Ehud Reiter


Abstract
Natural Language Generation has been proved to be effective and efficient in constructing health behaviour change support systems. We are working on DrivingBeacon, a behaviour change support system that uses telematics data from mobile phone sensors to generate weekly data-to-text feedback reports to vehicle drivers. The system makes use of a wealth of information such as mobile phone use while driving, geo-information, speeding, rush hour driving to generate the feedback. We present results from a real-world evaluation where 8 drivers in UK used DrivingBeacon for 4 weeks. Results are promising but not conclusive.
Anthology ID:
2022.nlg4health-1.1
Volume:
Proceedings of the First Workshop on Natural Language Generation in Healthcare
Month:
July
Year:
2022
Address:
Waterville, Maine, USA and virtual meeting
Venue:
NLG4Health
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–8
Language:
URL:
https://aclanthology.org/2022.nlg4health-1.1
DOI:
Bibkey:
Cite (ACL):
Jawwad Baig, Guanyi Chen, Chenghua Lin, and Ehud Reiter. 2022. DrivingBeacon: Driving Behaviour Change Support System Considering Mobile Use and Geo-information. In Proceedings of the First Workshop on Natural Language Generation in Healthcare, pages 1–8, Waterville, Maine, USA and virtual meeting. Association for Computational Linguistics.
Cite (Informal):
DrivingBeacon: Driving Behaviour Change Support System Considering Mobile Use and Geo-information (Baig et al., NLG4Health 2022)
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PDF:
https://aclanthology.org/2022.nlg4health-1.1.pdf