1. The Impact of and Adaptive User Interface
on Reducing Driver Distraction
Authors:
Patrick Tchankue, Janet Wesson and Dieter Vogts
3rd International Conference on Automotive User Interface,
November 29-December 2, 2011, Salzburg, Austria
2. Overview
• Background
• In-Car Communication Systems
• Driver Distraction
• Adaptive Interfaces
• Architecture of MIMI
• User Study
• Results
• Conclusion & Future work
3. Background
• In-Car Infotainment Systems are becoming common
– Information: communication, navigation and safety;
– Entertainment: radio, CD and games;
– Hands-free and eyes-free: voice-activated;
• Existing UI were not initially designed for such
applications
4. In-Car Communication Systems (ICCS)
• Most common component of in-car systems:
– Manage calls, text messages and contacts in the car via
Bluetooth (hands-free);
– Use speech (eyes-free) and steering wheels buttons (hands-
free) as input channel.
• Examples of ICCS:
Name Manufacturer Year
iDrive BMW 2001
Blue&Me Fiat 2004
SYNC Ford 2007
IQon SAAB 2011
5. Driver Distraction
• Driver distraction occurs when the driver’s attention is
diverted from driving to the extent that the driver is no
longer able to drive adequately or safely (Young &
Regan, 2005).
• Type of driver distraction:
– Visual: taking your eyes off the road;
– Auditory: internal and external noises;
– Manual: taking your hands off the steering wheel; and
– Cognitive: taking your mind off what you’re doing.
• Texting can cause more serious driver distraction.
6. Adaptive Interfaces
• Interfaces able to adapt to specific user, task or
situations;
• Inferring the distraction level;
– Fuzzy logic;
– Support Vector Machine;
– Neural networks;
• Adaptation effects
– Delaying calls and text messages;
– Resuming the notification process;
– Warn drivers before potential dangerous outgoing events
7. Architecture of MIMI
Input Module (A)
ASR NL Understanding
Multimodal Fusion
Mobile phone
Dialogue engine
Mobile phone
Dialogue manager (C)
Adaptive module interface (B)
Inputs
Dialogue Task Workload
history progress manager
CAN bus
Knowledge base
User Task Context
Phonebook DB
model model model
Output Module (D)
Adaptive engine NL
TTS
generation
8. Architecture of MIMI (cont.)
• Workload manager
speed
1 = very low
Δ speed Distraction
level 2 = low
3 = mid
angle
4 = high
Δ angle 5 = very high
9. User Study
• Aim
– Usability (task success, errors, effectiveness of tasks, time of
task)
– Safety (cognitive load, mean lateral deviation, perceived safety,
adaptation)
• Methodology
• Participants
– 30 students
• Tasks
– Calling
– Sending text messages
10. Results (cont.)
• Usability
7
6
5 6.33
5.90
5.70
6.10
4 5.07
6.17 6.23
5.73
5.43
3
4.47
2
1
Call effectiveness SMS effectiveness Barge-in Recognition Number dictation
Non adaptive Adaptive
Comparison of the usability of the non-adaptive and adaptive version of MIMI (n=30)
13. Results
• Safety
7
6.17
5.87 5.97
6 5.63
5.43 5.43 5.37
5.13
5
4
3
2
1
Safe to make calls Safe to send SMS Safe to answer calls Safe to read SMS
Non adaptive Adaptive
Comparison of the safety ratings of non-adaptive versus the adaptive version of MIMI (n=30).
14. Results
• Adaptation
Postponing Warning sound
MIMI 1 non MIMI 2 MIMI 1 non MIMI 2
adaptive adaptive adaptive adaptive
Mean 4.76 5.80 4.80 4.80
Median 5.00 6.00 4.00 5.00
Mode 4.00 6.00 4.00 4.00
StdDev 1.87 1.45 1.56 1.65
p-value 0.01 1.00
Comparing the adaptation of MIMI 1 and MIMI 2 (n=30).
15. Conclusion & Future work
• ICCS can be affected by usability and safety issues;
• An adaptive interface for an ICCS was designed;
• A user study compared MIMI 1 and MIMI 2 in terms of
usability and safety;
• The Adaptive interface had a positive impact on the
usability and safety of MIMI;
• Future work
– Other adaptation effects to be investigated;
– Alternative warning strategies.
16. Thank you for your attention!
Questions ?
Contact:
Emails: Patrick.TchankueSielinou@nmmu.ac.za
Janet.Wesson@nmmu.ac.za
Dieter.Vogts@nmmu.ac.za
Website: www.nmmu.ac.za/cs
Tel: +27 41 504 2323