Intelligent driver profiling system for cars – a basic concept


Type
Conference Object
Change log
Authors
Langdon, PM 
Clarkson, PJ 
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.

Description
Keywords
Automotive engineering and technology, Advanced driver assistance systems, Car driver profiling, Customisation, Personalisation, Inclusive design, Human factors and ergonomics
Journal Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Conference Name
HCI International 2018
Journal ISSN
0302-9743
1611-3349
Volume Title
10908 LNCS
Publisher
Springer International Publishing
Sponsorship
EPSRC (via University of Southampton) (515532101)