Paper Info
Title
Complexity Of In-Vehicle Controllers And Their Effect On Task Performance
Abstract
Smart functions in vehicles have led to an increase in the complexity of control interfaces. This study aims to develop a model for evaluating in-vehicle controller complexity and to investigate the relationship between complexity and task performance. A research framework consisting of three complexity dimensions (functional, behavioral, and structural dimensions) and controller-related variables was developed based on previous literature. A user experiment was conducted using 10 vehicles and 91 participants. A regression analysis was used to examine the relationship between the measurement variables and perceived controller complexity, and the results indicated correlations between them. An increase in functional dimension variables caused an increase in the perceived complexity level, while behavioral dimension variables are not a statistically significant predictor. Structural dimension variables showed different results depending on the characteristics of the variables. The results of the control task experiment showed a negative correlation between task performance and the perceived complexity level. In addition, satisfaction decreased with increasing levels of complexity. These results provide insights for managing in-vehicle controller complexity.
Year
DOI
Venue
2019
10.1080/10447318.2018.1428263
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
Field
DocType
Volume
Control theory,Regression analysis,Computer science,Human–computer interaction,Artificial intelligence,Conceptual framework,Machine learning
Journal
35
Issue
ISSN
Citations 
1
1044-7318
0
PageRank 
References 
Authors
0.34
23
2
Name
Order
Citations
PageRank
Seul Chan Lee165.64
Yong Gu Ji223822.42