Charlie
Voice-Based Navigation Assistant
Overview
Within the vast field of retail, there are specialized areas like outdoor recreational gear. From our research we found that novice shoppers do a majority of surface-level research on color and style but lack information on technical information regarding safety and maintenance. Technical information is extremely important to understand because in some cases it could be the deciding factor of life and death. Our team designed Scout, an in-store tool that helps shoppers explore and learn about different products and activities and in turn make informed decisions.
Scout is a white-label system, with hopes that the product can be used in other specialized areas of retail.
Role
UX Researcher
UX Designer
Director
Editor
Timeline
1.5 Weeks
Team
Eugene Meng
Mai Bouchet
Marina Lazarevic
Siyi Kou
Shravya Neeruganti
Sponsored by
University of Washington, Seattle
Process
01
Research
Secondary Research
Competitive Analysis
Multimodal Systems
Portable Navigation Devices
02
Ideation
Concept Generation
Individual Ideation
Team Ideation
03
Design
Script Creation
Film-Making
Animation
RESEARCH
From our research we found that the majority of navigation systems today rely heavily on visual components. This is extremely dangerous as this kind of navigation tends to increase the cognitive load on the driver and therefore attention is taken away from actually driving and placed somewhere else. We found from our research that this division of attention has proved to be fatal.
Our team researching the navigation space.
problem space
"When drivers left their route intentionally, navigation systems produced 56% false acoustics and 65% false visual messages respectively."
1. Current navigation applications do not adapt well to changes. For example, if a driver chooses to deviate from a route, he/she will receive insufficient feedback or cryptic, unhelpful commands.
2. Communicating intentions during a trip is difficult. Often it results in drivers needing to fumble with a touchscreen while driving which is dangerous.
3. Information exchange loops are inadequate and existing navigation improvements do not focus enough on driver-device interactivity.
Ideation
After conducting secondary research and understanding our problem space well, we found that the most promising navigation system would adapt to driver behavior and changes integrating multimodal capabilities such as tactile, audible, or visual to enhance voice interactions. Our team set out to find out how other sense modalities could be tapped into for our navigation system. Our team began to brainstorm ideas to explore how someone would interact with a navigation system.
Some of our team's concepts during ideation phase.
Design
After the ideation phase, we identified 3 ways Charlie could help the driver reach his/her destination by combining different multimodal elements to develop a seamless interaction between Charlie, the driver and even a passenger seated in the car.
Designing 3 navigation modes
Guided Mode - Leader
Current navigation applications speak a mechanical language and gauge the road by numbers. The information is absurd for drivers who lack contextual awareness of the road. In guided mode, Charlie offers navigation information in conversational language and develops a customized language set for different users. In order to prevent errors and make accurate decisions, Charlie will notify the user when she does not understand the input or the road condition, and will prompt the user to act accordingly.
Learning Mode - Follower
In real-life driving scenarios, people often want to take a detour or their preferred routes different from what recommended by their navigation. Learning mode features background machine learning when Charlie is muted to follow the lead of the user. In this mode, Charlie learns the user's preferred route and driving habits, and applies those to her future work.
Assisted Mode - Helper
In assisted mode, a passenger is guiding the driver with visual guidance offered by Charlie while the default setting of Charlie is mute. When the passenger is distracted, by double-tapping or calling Charlies name, the driver can re-activate Charlie to acquire the guidance for the next step. Learning mode can work concurrently with this mode for Charlie to pick up the language of the guiding passenger.
Next Steps
Our team would like to test Charlie's intelligence and functionality. We would create a behavioral prototype to understand if Charlie is giving useful and intuitive information to the driver. This would be a crucial step in developing the navigation system.
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