Abstract
Automobile instrument clusters and infotainment systems are commonly used and prominent in modern cars and trucks. Thus, the design of these systems and their usability can significantly affect driving performance and satisfaction. This study demonstrates how biometric sensor methods can be used to assess such usability. Specifically, the study examines users' visual attention and affective states in response to instrumentation in two hybrid cars. The study combines eye tracking, facial expression analysis, and electroencephalography (EEG) data to investigate how these two cluster and infotainment designs (a) capture visual attention; (b) potentially inspire engagement, frustration and confusion; and (c) impact users' perception of ease of use.
| Original language | English (US) |
|---|---|
| Title of host publication | 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - Conference Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538604342 |
| DOIs | |
| State | Published - Jun 26 2018 |
| Event | 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - San Francisco, United States Duration: Apr 4 2017 → Apr 8 2017 |
Other
| Other | 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 |
|---|---|
| Country | United States |
| City | San Francisco |
| Period | 4/4/17 → 4/8/17 |
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Keywords
- biometric measurement system
- EEG
- eye tracking
- facial expression analysis
- infotainment system
- instrument panel cluster
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Information Systems
- Information Systems and Management
- Energy Engineering and Power Technology
- Safety, Risk, Reliability and Quality
- Urban Studies
Cite this
A biometric usability evaluation of instrument cluster and infotainment systems in two hybrid cars. / Kula, Irfan; Atkinson, Robert; Roscoe, Rod; Branaghan, Russell.
2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-6.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A biometric usability evaluation of instrument cluster and infotainment systems in two hybrid cars
AU - Kula, Irfan
AU - Atkinson, Robert
AU - Roscoe, Rod
AU - Branaghan, Russell
PY - 2018/6/26
Y1 - 2018/6/26
N2 - Automobile instrument clusters and infotainment systems are commonly used and prominent in modern cars and trucks. Thus, the design of these systems and their usability can significantly affect driving performance and satisfaction. This study demonstrates how biometric sensor methods can be used to assess such usability. Specifically, the study examines users' visual attention and affective states in response to instrumentation in two hybrid cars. The study combines eye tracking, facial expression analysis, and electroencephalography (EEG) data to investigate how these two cluster and infotainment designs (a) capture visual attention; (b) potentially inspire engagement, frustration and confusion; and (c) impact users' perception of ease of use.
AB - Automobile instrument clusters and infotainment systems are commonly used and prominent in modern cars and trucks. Thus, the design of these systems and their usability can significantly affect driving performance and satisfaction. This study demonstrates how biometric sensor methods can be used to assess such usability. Specifically, the study examines users' visual attention and affective states in response to instrumentation in two hybrid cars. The study combines eye tracking, facial expression analysis, and electroencephalography (EEG) data to investigate how these two cluster and infotainment designs (a) capture visual attention; (b) potentially inspire engagement, frustration and confusion; and (c) impact users' perception of ease of use.
KW - biometric measurement system
KW - EEG
KW - eye tracking
KW - facial expression analysis
KW - infotainment system
KW - instrument panel cluster
UR - http://www.scopus.com/inward/record.url?scp=85050189300&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050189300&partnerID=8YFLogxK
U2 - 10.1109/UIC-ATC.2017.8397594
DO - 10.1109/UIC-ATC.2017.8397594
M3 - Conference contribution
SP - 1
EP - 6
BT - 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -