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
Overview• Background• In-Car Communication Systems• Driver Distraction• Adaptive Interfaces• Architecture of MIMI• User Study• Results• Conclusion & Future work
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
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
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.
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
Architecture of MIMI Input Module (A) ASR NL Understanding Multimodal Fusion Mobile phone Dialogue engine Mobile phoneDialogue 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
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
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
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)
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).
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).
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.
Thank you for your attention! Questions ? Contact:Emails: Patrick.TchankueSielinou@nmmu.ac.za Janet.Wesson@nmmu.ac.za Dieter.Vogts@nmmu.ac.zaWebsite: www.nmmu.ac.za/csTel: +27 41 504 2323