An Evaluation of Input Controls for In-Car Interactions
Authors:
Open Access
- 2 May 2017
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 2845-2852
Abstract
The way drivers operate in-car systems is rapidly changing as traditional physical controls, such as buttons and dials, are being replaced by touchscreens and touch-sensing surfaces. This has the potential to increase driver distraction and error as controls may be harder to find and use. This paper presents an in-car, on the road driving study which examined three key types of input controls to investigate their effects: a physical dial, pressure-based input on a touch surface and touch input on a touchscreen. The physical dial and pressure-based input were also evaluated with and without haptic feedback. The study was conducted with users performing a list-based targeting task using the different controls while driving on public roads. Eye-gaze was recorded to measure distraction from the primary task of driving. The results showed that target accuracy was high across all input methods (greater than 94%). Pressure-based targeting was the slowest while directly tapping on the targets was the faster selection method. Pressure-based input also caused the largest number of glances towards to the touchscreen but the duration of each glance was shorter than directly touching the screen. Our study will enable designers to make more appropriate design choices for future in-car interactions.Keywords
Funding Information
- Horizon 2020 HAPPINESS project (645145)
This publication has 26 references indexed in Scilit:
- Tactile feedback for virtual automotive steering wheel switches2015
- Bimanual Input for Tablet Devices with Pressure and Multi-Touch Gestures2015
- How to make large touch screens usable while driving2013
- A study of unidirectional swipe gestures on in-vehicle touch screens2013
- Designing browsing for in-car music player2012
- Some hazards are more attractive than others: Drivers of varying experience respond differently to different types of hazardAccident Analysis & Prevention, 2012
- Visual–haptic feedback interaction in automotive touchscreensDisplays, 2012
- The impact of an adaptive user interface on reducing driver distraction2011
- The aligned rank transform for nonparametric factorial analyses using only anova procedures2011
- Combining cognitive and visual distraction: Less than the sum of its partsAccident Analysis & Prevention, 2010