Paper Info
Title
Attuning in-car user interfaces to the momentary cognitive load
Abstract
Cars, trucks and busses are more and more equipped with functions and services that drivers are supposed to operate and understand. The most important developments in this area are the Advanced Driver Assistance Systems (ADAS) and In Vehicle Information Systems (IVIS). In order to make sure that the driver understands and appreciates (comfort) these services and traffic safety is not at risk (distraction, workload), the HMI's (Human Machine Interfaces) of all these functions should be attuned to each other, to the driver, and to the context. For attuning the functions to each other, a HMI platform is needed on which these functions are integrated. For attuning the functions to the driver it is necessary to have knowledge about the momentary state of the driver and of the intentions of the driver at a certain moment. For attuning the functions to the context, it is required to sense the relevant environmental conditions or states. This paper shows that a recent cognitive task load model from process control domain can be applied for the design of adaptive in-car user interfaces. Furthermore, current developments of such interfaces are being discussed.
Year
DOI
Venue
2007
10.1007/978-3-540-73216-7_32
HCI (16)
Keywords
Field
DocType
vehicle information systems,current development,momentary state,assistance systems,certain moment,human machine interfaces,important development,momentary cognitive load,advanced driver,adaptive in-car user interface,hmi platform,information systems,trucks,process control,cognitive load,user interfaces,user interface,human machine interface
Information system,Truck,Distraction,Adaptive user interface,Human–machine system,Computer science,Simulation,Advanced driver assistance systems,Human–computer interaction,Cognitive load,User interface
Conference
Volume
ISSN
Citations 
4565
0302-9743
6
PageRank 
References 
Authors
0.70
2
2
Name
Order
Citations
PageRank
Marika Hoedemaeker160.70
Mark Neerincx210210.76