Energy-efficient and safe driving using a situation-aware gamification approach in logistics
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Transcript of Energy-efficient and safe driving using a situation-aware gamification approach in logistics
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Energy-efficient and safe driving using a situation-aware 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
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Image: Phil Rogers, http://www.flickr.com/photos/erase/5572308872/sizes/l/in/photostream/
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What is a mobile serious game?
Image: Phil Rogers, http://www.flickr.com/photos/erase/5572308872/sizes/l/in/photostream/
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Mobile Serious Games
• Mobile Serious games allow connecting learning, gaming and situation • Embedded in Context • Exploration and utilization of context • Augmentation of reality
Image: Phil Rogers, http://www.flickr.com/photos/erase/5572308872/sizes/l/in/photostream/
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BACKGROUND: LOGIASSIST
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Mobile Learning in Logistics - Situation Workforce in logistics is inherently mobile
Image Source: http://www.flickr.com/photos/kenjonbro/3418689657/
Regular education is hard to perform
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LogiAssist – Learning & Assistance approach
+
Dangerous goods
DocStop
Language learning
Map
Events
Forms Education
Community
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Location-based services
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SITUATION-AWARENESS IN LOGIASSIST
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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
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Situation-awareness Architecture
ActionManagement
RuleManagement
ContextModel ContextMonitor
Rule Observation
Action Management
History Management
Rule Manager Rules Rules Rules
Rule Actions Rule
Actions Rule Actions
Context Container
Context Service
Context Managers Context Managers Context Managers
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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
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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)
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Example: Low fuel warning as blocking update
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GAMIFICATION FOR LOGIASSIST – THE TEGA PROJECT
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Project Goal
A telematics-based learning game that encourages the driver to drive economically and environmentally safe.
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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
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LogiAssist – TEGA
LogiAssist Community Portal - Members
- Friendships - Profiles
Vehicle information CAN Bus
LogiAssist App Framework
TEGA App
Bluetooth
Gamification Framework
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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
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TEGA App
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USER STUDY
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Study elements
• Small scale user study for usability • Using simulated test drives for safety, cost, and technical aspects
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Test setup
Bluetooth-Adapter
Vehicle-Simulation
Data-Receiver
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Technical results
• Integration of TEGA in LogiAssist works • Rule-based system triggers actions • Adjustments to gamification rules made
according to simulated test-drives
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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
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CONCLUSION
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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
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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
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Thank you …
@rklemke
www.linkedin.com/in/rolandklemke
… and drive carefully!