Energy-efficient and safe driving using a situation-aware gamification approach in logistics


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Presentation at the GALA Conference in Paris.
Safety and energy-efficiency is the main aim of every reasonable driver. But often there is too much relevant information a driver has to take into account and evaluate. A useful support can be provided by technology that can observe the driver’s situation, analyze it, and offer individualized information and services to the driver. Moreover, by means of gamification mechanisms drivers can receive valuable feedback and motivation to improve their behavior.
This paper presents such a situation-aware gamification approach in logistics, which has been elaborated in the LogiAssist project and enhanced in the TEGA game. A first user study indicated the general usefulness of this approach and revealed also several shortcomings. These results imply that this synergy of various technologies provides a promising opportunity for further investigation and development.

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Energy-efficient and safe driving using a situation-aware gamification approach in logistics

  1. 1. Energy-efficient and safe driving using a situationaware gamification approach in logistics Roland Klemke (Open Universiteit Nederland) Milos Kravcik (RWTH Aachen) Felix Bohuschke (Humance AG, Cologne) GALA Conference, Paris, 23.-25.10.2013 page 1
  2. 2. page 2 Image: Phil Rogers,
  3. 3. What is a mobile serious game? page 3 Image: Phil Rogers,
  4. 4. Mobile Serious Games • Mobile Serious games allow connecting learning, gaming and situation • Embedded in Context • Exploration and utilization of context • Augmentation of reality page 4 Image: Phil Rogers,
  6. 6. Mobile Learning in Logistics - Situation Workforce in logistics is inherently mobile page 6 Regular education is hard to perform Image Source:
  7. 7. LogiAssist – Learning & Assistance approach Map Dangerous goods Events + DocStop Language learning Community Education page 7 Forms
  8. 8. Location-based services page 8
  10. 10. Situations to recognize • Recognition of national borders to be crossed • E.G. different rules apply in the country to enter • Driving time related hints • Proposal of nearby rest areas • Detection of driver license related information • expiration of a specific certificate • offering access to relevant educational material during breaks page 10
  11. 11. Situation-awareness Architecture ActionManagement Rule Observation Action Management History Management RuleManagement Rule Manager ContextModel Rules Rules Rules Rule Rule Actions Rule Actions Actions ContextMonitor Context Container page 11 Context Service Context Managers Context Managers Context Managers
  12. 12. Context Parameters in the Context Model •  Technical parameters •  retrieved via CAN-bus •  speed, gear used, fuel consumption •  Driver related parameters •  retrieved via LogiAssist app •  GPS position, destination, traffic information, routing information •  Infrastructural parameters •  retrieved via LogiAssist backend •  community information, profile information page 12
  13. 13. Rules •  Rule contains: rule trigger and a rule action •  Rule trigger: •  Combination of a set of context parameters •  Priorities •  Rule action •  Background actions (status updates to the backend) •  Non-intrusive user interface updates (status updates for map) •  Intrusive user interface updates (warning messages) •  Blocking user interface updates (warnings requiring interaction) page 13
  14. 14. Example: Low fuel warning as blocking update page 14
  16. 16. Project Goal A telematics-based learning game that encourages the driver to drive economically and environmentally safe. page 16
  17. 17. TEGA Project as part of RWTH Course "Hightech Entrepreneurship and New Media" • Student project • Simulated start-up experience • Connected to LogiAssist project • Approach: Gamified extension to LogiAssist to support safe driving • TEGA: Telematics Ecologic Game page 17
  18. 18. LogiAssist – TEGA LogiAssist App Framework Vehicle information CAN Bus TEGA App Bluetooth LogiAssist Community Portal -  Members -  Friendships -  Profiles page 18 Gamification Framework
  19. 19. Gamification Elements in TEGA • Level system: continuous use of the app is awarded • Scoring system: gain points by using an economically friendly driving style • Reward/Achievement system: receive badges and titles by reaching goals – e.g. reducing average fuel consumption by 5%, 10%, or 15% • Ranking system: compare driving style with others: leaderboard page 19
  20. 20. TEGA App page 20
  21. 21. USER STUDY page 21
  22. 22. Study elements •  Small scale user study for usability •  Using simulated test drives for safety, cost, and technical aspects page 22
  23. 23. Test setup Bluetooth-Adapter Vehicle-Simulation page 23 Data-Receiver
  24. 24. Technical results • Integration of TEGA in LogiAssist works • Rule-based system triggers actions • Adjustments to gamification rules made according to simulated test-drives page 24
  25. 25. User feedback •  Rule-based gamification approach generally works and was accepted by the users •  TEGA app needs to be less intrusive •  Should operate mainly in the background •  Only notify user of achievements and scores •  Use audio notifications for achievements or leveling information •  Underlying goals for achievements to be unlocked and scores to be gained have to be communicated to the user in a more explicit way page 25
  26. 26. CONCLUSION page 26
  27. 27. Conclusion •  TEGA extends rule-based approach of situation- awareness in LogiAssist •  Rules to detect the energy-efficient driving •  Gamification elements such as scores, levels, achievements, and badges •  Gamification outcomes added to user profile to share results page 27
  28. 28. Conclusion •  Weaknesses in implementation detected •  Broader user study needed under real-life conditions •  Complement gamification with training offers •  Integrate gamification elements in core LogiAssist tools page 28
  29. 29. Thank you … @rklemke … and drive carefully! page 29