Abstract

Many industries have been transformed by the provision of service solutions characterised by personalisation and customisation - most dramatically the development of the iPhone. Personalisation and customisation stand to make an impact on cars and mobility in comparable ways. The automobile industry has a major role to play in this change, with moves towards electric vehicles, auton-omous cars, and car sharing as a service. These developments are likely to bring disruptive changes to the business of car manufacturers as well as to drivers. However, in the automobile industry, both the user's preferences and demands and also safety issues need to be confronted since the frequent use of different makes and models of cars, implied by car sharing, entails several risks due to variations in car controls depending on the manufacturer. Two constituencies, in particular, are likely to experience even more difficulties than they already do at present, namely older people and those with capability variations. To overcome these challenges, and as a means to empower a wide car user base, the paper here presents a basic concept of an intelligent driver profiling system for cars: the sys-tem would enable various car characteristics to be tailored according to individual driver-dependent profiles. It is intended that wherever possible the system will personalise the characteristics of individual car components; where this is not possible, however, an initial customisation will be performed.


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.1007/978-3-319-92052-8_16 under the license http://www.springer.com/tdm
https://www.repository.cam.ac.uk/handle/1810/279154,
http://publications.eng.cam.ac.uk/977947,
https://dblp.uni-trier.de/db/conf/hci/hci2018-8.html#CaberLC18,
https://rd.springer.com/chapter/10.1007/978-3-319-92052-8_16,
https://academic.microsoft.com/#/detail/2805660687


DOIS: 10.1007/978-3-319-92052-8_16 10.17863/cam.26534

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Published on 01/01/2018

Volume 2018, 2018
DOI: 10.1007/978-3-319-92052-8_16
Licence: CC BY-NC-SA license

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