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AutoBot April 10, 2012
Introduction   Mission of Autobot   Influencer Matrix   Research   Solution   Autobot Demonstration     Video, Desig...
Mission of Autobot Problem: People give little         Mission:  thought to how well they are         1) Design a system...
Influencer Matrix
Research   Personal Interviews   Personas and Scenarios   Survey   Comparative Analysis   User Testing Competitive Apps
Personas & Scenarios
Survey SI Distributed   126 responses      Thanks! What direction  should we take?   Driving behavior?   Maintenance...
Survey: Important Results89 %         43 %       40 %                          Know What’s      Improve              drivi...
Comparative Analysis Competition thought  of many ways to  provide driving  feedback Easy to understand  metrics for any...
Testing the Competition 5 volunteers drove  around with “Driver  Feedback”   Impressed with the    simplicity of app   ...
Solution Multi-platform 3 Key Metrics Behavioral Change Techniques
The AutoBot Prototype
In-Car App
Console Design   myFord Touch   Toyota Prius
Console Design, cont’d             Autobot
Functions    Minimized   Summary
Login
Login                 Limited barriers                 to entrySimple sign-in& added socialinfluence
Login: Facebook        Easy out                     Simple language                     of what will be                   ...
Settings                Fine grainPersonalized                control ofsettings for                socialuser-specific   ...
Record a Trip   (video)
Record a TripApp recordsdriving data usingthe phone’saccelerometer, gyroscope and GPSsensors.                     The devi...
Self-Report              Shows perception              vs reality to reveal              misperceptions
Summary, Maps and Alerts       (video)
Summary                        Average PointsContextualization:Shows impact ofdriving on fueleconomy andenvironment       ...
MapContextualization:Shows where userdrive well (green)and poorly (red)     Alerts: Shows specific                     are...
Alerts                       Problem specific adviceContextualization:Shows the cost ofwear and tearincurred by mistakes
Trip Log and Compare Trips          (video)
Trip Log                     Users can toggle                     Routes to see howHistory tracking:    routine trips chan...
Compare TripsUsers can juxtaposedata from two tripsto see how theycompare
Graphs(video)
Graphs                   Trends over timeSimple and CleanDesign                   Impact
Social(video)
Social: ProfileSocial influence                    Earning awards                    for driving                    behavior
Social: GroupsGroup inclusionaligned by commoninterests, location,…                       Gamification
Green and Tips   (video)
Green   Eco Status Level                      Progress                      VisualizationEco Points History
Tips                   Simple                   instructionsBenefits clearlylaid out                   Social influenceCle...
Conclusion Gamification    Users receive points based     on their driving behavior and     car maintenance    Leaderbo...
Conclusion Information Visualization    Stats pages display both      broad and specific views of      user’s data    M...
Conclusion Social Influence    Users can customize their     profiles, giving them ownership     of their data and progr...
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AutoBot Presentation for Personal Informatics

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This is the final presentation for the design of Autobot, a smart phone app and built-in dashboard interface that provides information about your driving habits and promotes positive behavior change. This presentation details our design process, AutoBot's functions, and some of the theoretical framework used to explain our design decisions.

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  • Everyone interviewed someone on their driving habits, which helped us create the following personas. We wanted to think about people who may use this app to improve their understanding of their own driving habits and also have a desire to learn more about being a conscious driver, to people who already take good care of their cars, and want a way to track information. We accounted for a large range of domain knowledge around cars by allowing users to choose how engaged in the system they want to be.
  • Multi-PlatformA mobile and in-car application that informs drivers of their driving behavior based on three primary metrics: acceleration, braking, and cornering3 Key MetricsAcceleration, Braking and Cornering and fuel economy to a lesser extentBehavioral Change TechniquesThe mobile app informs and motivates users by taking advantage of behavioral change techniques. The app provides structure where was none before incentivizing positive driving behavior using a points system, offering status titles, easy to understand personalized feedback, and utilizing social influence through the AutoBot online community and other social networks.
  • This technology is still emerging, but we wanted to integrate into car’s existing dashboard functions. As you can see, this is how two of the major players in the automotive world present their consoles.
  • We limited the functions to summarizing the information listed, and to minimize the score so that the driver could use other functions. We didn’t include other tools available on the phone application because we didn’t want to distract the driver any more than was necessary, especially since that was a lot of the criticism levied at current car console interfaces. That’s why we included the more interactive and engaging functions directly in our phone application.Here, we begin directing the rider by displaying the current score and giving the users a glimpse of how well they’re doing. This provides structural support in the form of points and motivation in terms of giving the user a guage of how well they’re doing on a 100 point scale.
  • Nesser’s Ecological Self: Self-reporting shows how you perceive yourself, and then Autobot juxtaposes your perceived driving performance with your actual driving performance
  • Nesser’s Ecological Self: Self-reporting shows how you perceive yourself, and then Autobot juxtaposes your perceived driving performance with your actual driving performance
  • Nesser’s Ecological Self: Self-reporting shows how you perceive yourself, and then Autobot juxtaposes your perceived driving performance with your actual driving performance
  • Personal Motivation (Influencer matrix component)The graphs address the personal ability barrier. These data visualizations allow the user to determine whether or not changes in her driving behavior are having an effect on the quality of her driving, be it positive or negative. For example, if a user decides to follow the advice provided with one of her alerts she can determine if that change in behavior has had an impact on any, or all, of the driving metrics by referring to the line graph.Direct the Rider (Rider and path)Although the graphs do not direct the rider in and of themselves, they are a key part of that goal. Telling someone to drink 2% milk, or in this case slow down as they enter a turn, is important but it is also important to give that person feedback on their progress toward change. So I’ve been drinking 2% milk for a month now, did that really make a difference and if so, how much of a difference? Graphs, and other data visualizations, can help answer these questions and in doing so motivate a person to continue to change their behavior.Simple and Clean (UI standards)For the graphs I wanted the data to be presented to the user as clearly as possible. Although a more artistic representation would have done more to motivate the elephant I was focused on directing the rider. If you want to make a data visualization easy for a person to decipher you need to make the visualization simple and clean. This is a common practice in the field of psychology, to avoid using things like 3-D bar graphs and other more complex visualizations when a simple 2 dimensional graph could have presented the information just as well. Something to keep in mind is that our user base will be rather broad and that all of them will not be able to find meaning in more complex visualizations.That being said we’ve given the user a line graph that allows her to observe changes and trends in her driving behavior over an extended period of time. The scatter plot below allows the user to identify correlations between her scores on the three metrics and her fuel economy. She can determine the impact of a score of 70 on acceleration versus a score of 95 in terms of fuel economy, something that should be meaningful to most users. It is our hope that when the user observes the negative impact of her poor scores on her fuel economy she will be further motivated to improve her driving behavior.
  • Structural Motivation (Influencer matrix component)This visualization is meant to help break down the barrier in structural motivation. Watching her tree grow provides the user with an immediate, and visible, reward for her eco friendly behavior. Aside from watching her tree grow the user can also track her progress toward obtaining the next level of proficiency in her eco friendly behavior.Motivate the Elephant (Rider and path)The tree visualization is meant to motivate the elephant. Unlike the graphs, with visualization we wanted to appeal to the user’s emotional side and therefore went with a more artistic visualization. Simply providing the user with numbers to demonstrate her environmental impact didn’t seem like it was sufficient to quantify diverse data. A common unit by which environmental impact is often measured are pounds of carbon saved. Now I don’t know about you but that unit is meaningless to me. So for our visualization we chose something familiar to people, one that they immediately identify with the environment, a tree.Design to Evoke Emotion (UI standards)For this visualization the I felt that the most appropriate choice would be a more visually appealing and somewhat atypical design. When trying to evoke emotion in a observer it is more important to provide an interesting visualization than one that is clean and simple, such as the graphs presented earlier.
  • Transcript of "AutoBot Presentation for Personal Informatics"

    1. 1. AutoBot April 10, 2012
    2. 2. Introduction Mission of Autobot Influencer Matrix Research Solution Autobot Demonstration  Video, Design defense, Relevance to course concepts, UI Standards
    3. 3. Mission of Autobot Problem: People give little  Mission: thought to how well they are 1) Design a system that informs driving because it is people of their driving habits ingrained, habitual behavior. 2) Leverage Lack of awareness and gamification, information overconfidence prevents people visualization, and social influence from improving their driving to promote positive behavior habits, which can lead to change unsafe, costly, and environmentally harmful driving.
    4. 4. Influencer Matrix
    5. 5. Research Personal Interviews Personas and Scenarios Survey Comparative Analysis User Testing Competitive Apps
    6. 6. Personas & Scenarios
    7. 7. Survey SI Distributed  126 responses  Thanks! What direction should we take?  Driving behavior?  Maintenance reminder?  What do people want to know about?
    8. 8. Survey: Important Results89 % 43 % 40 % Know What’s Improve driving morewrong with habits about their my car? habits
    9. 9. Comparative Analysis Competition thought of many ways to provide driving feedback Easy to understand metrics for any driver  Acceleration  Braking  Cornering
    10. 10. Testing the Competition 5 volunteers drove around with “Driver Feedback”  Impressed with the simplicity of app  Enjoyed seeing where on their driving path they made mistakes  Did not feel motivated to improve
    11. 11. Solution Multi-platform 3 Key Metrics Behavioral Change Techniques
    12. 12. The AutoBot Prototype
    13. 13. In-Car App
    14. 14. Console Design myFord Touch Toyota Prius
    15. 15. Console Design, cont’d Autobot
    16. 16. Functions Minimized Summary
    17. 17. Login
    18. 18. Login Limited barriers to entrySimple sign-in& added socialinfluence
    19. 19. Login: Facebook Easy out Simple language of what will be posted on FBWhat informationis required of you
    20. 20. Settings Fine grainPersonalized control ofsettings for socialuser-specific mediafeedback options
    21. 21. Record a Trip (video)
    22. 22. Record a TripApp recordsdriving data usingthe phone’saccelerometer, gyroscope and GPSsensors. The device must remain stationary while recording.
    23. 23. Self-Report Shows perception vs reality to reveal misperceptions
    24. 24. Summary, Maps and Alerts (video)
    25. 25. Summary Average PointsContextualization:Shows impact ofdriving on fueleconomy andenvironment Praise and advice based on your data
    26. 26. MapContextualization:Shows where userdrive well (green)and poorly (red) Alerts: Shows specific areas where the user drove poorly
    27. 27. Alerts Problem specific adviceContextualization:Shows the cost ofwear and tearincurred by mistakes
    28. 28. Trip Log and Compare Trips (video)
    29. 29. Trip Log Users can toggle Routes to see howHistory tracking: routine trips changeUser can pick and over timechoose previoustrips to view Users can retrieve old data and reflect on past mistakes
    30. 30. Compare TripsUsers can juxtaposedata from two tripsto see how theycompare
    31. 31. Graphs(video)
    32. 32. Graphs Trends over timeSimple and CleanDesign Impact
    33. 33. Social(video)
    34. 34. Social: ProfileSocial influence Earning awards for driving behavior
    35. 35. Social: GroupsGroup inclusionaligned by commoninterests, location,… Gamification
    36. 36. Green and Tips (video)
    37. 37. Green Eco Status Level Progress VisualizationEco Points History
    38. 38. Tips Simple instructionsBenefits clearlylaid out Social influenceClear monetaryincentive topartake in this Earning pointsactivity
    39. 39. Conclusion Gamification  Users receive points based on their driving behavior and car maintenance  Leaderboards and groups provide an engaging, competitive environment  Visualizations display progress toward goals and new levels
    40. 40. Conclusion Information Visualization  Stats pages display both broad and specific views of user’s data  Maps and Tips contextualize data to be more compelling  Graphs allow the user to compare variables  Self-reporting reveals misconceptions about behavior
    41. 41. Conclusion Social Influence  Users can customize their profiles, giving them ownership of their data and progress  Leaderboard publishes the user’s data to their friends pages, making them more conscious of their driving
    42. 42. Questions?
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