Astute symposium 2013-10-10_smart_automotiveinfotainmentsystem_lucacontini_mirkofalchetto
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Astute symposium 10/10/2013 - Smart automotive infotainment system
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Astute symposium 2013-10-10_smart_automotiveinfotainmentsystem_lucacontini_mirkofalchetto
- 1. A context aware and proactive in-vehicle information system: Matching infotainment with safety Luca Contini Akhela 10/10/2013
- 2. Agenda • • • • • • • • • • • SOTA and current limitations The Solution Car Sensors Software Reference Architecture Aggregator Context Engine Proactive Decision Engine Adaptive HMI Engine Database Results Future Work
- 3. SOTA Current IVI systems are difficult to navigate: user must dig into too many levels
- 4. SOTA Information is not filtered or recommended proactively
- 5. SOTA The interface can be distractive and unsafe
- 6. The Solution A minimal, context sensitive and proactive user interface
- 7. The Solution Featuring a warning-based recommendation system
- 8. The Solution To achieve context modelling and thus proactivity goals, sensors must be used
- 9. Car Sensors Location sensor Visual algorithm dedicated HW Local and remote database Visual Odometry External cameras for video processing Weather Visual Search OBD Sensors OBD Fuel Level Proactive HMI OBD RPM OBD Engine Temperature Virtual Sensors Weather Distance to destination Cruise Range OBD Speed
- 10. Car Sensors Location sensor OBD Fuel Level Visual Odometry OBD RPM Visual Search OBD Engine Temperature Weather OBD Speed Distance to destination Cruise Range
- 11. Car Sensors Location sensor OBD Fuel Level Visual Odometry CONTEXT DEFINITION Visual Search OBD RPM PROACTIVITY Weather OBD Engine Temperature OBD Speed Distance to destination Cruise Range
- 12. Car Sensors Visual Odometry Visual Search Weather PROACTIVITY Distance to destination Cruise Range CONTEXT DEFINITION Location sensor OBD Fuel Level OBD RPM OBD Engine Temperature OBD Speed
- 13. Software Reference Architecture Visual Odometry ADAPTIVE HMI ENGINE Visual Search Weather PROACTIVE Distance to destination DECISION ENGINE To achieve context definitition and proactivity we use a 4 layer Cruise Range software stack CONTEXT ENGINE Location sensor OBD Fuel Level OBD RPM AGGREGATOR Reference Architecture OBD Engine Temperature OBD Speed
- 14. Reference Architecture: Aggregator CONTEXT ENGINE Cruise Range The Aggregator component collects sensor data, aggregates them according to specific rules, and pushes them to the context engine AGGREGATOR Location sensor OBD Fuel Level OBD Speed
- 15. Reference Architecture: Context Engine PROACTIVE DECISION ENGINE m_ContextAction0= "Show Default Panel" The Contextm_ContextAction1= "Showthe ontology rules to the sensor Engine applies Parking Warning" m_ContextAction2= "Show Fuel Warning" values and generates lists of facts m_ContextAction3= "Show POI Available Warning" m_ContextAction4= "Show VS Match Warning" Context Facts Ontology Rules CONTEXT ENGINE
- 16. Reference Architecture: Proactive Decision Engine The Proactive Decision Engine is composed by separated subengines communicating via task-board Adaptive HMI Engine Proactive Decision Engine Taskboard Navigation Manager POI Manager Panel Manager Warning Manager
- 17. Reference Architecture: Proactive Decision Engine Each sub-engine filters its specific category of facts and creates and ordered (priority based) list of facts (actions) to be shown in the HMI Adaptive HMI Engine PDE takes “decisions” between possible solutions Show default panel Show fuel warning Proactive Decision Engine Navigation Manager POI Manager Panel Manager Warning Manager
- 18. Reference Architecture: Adaptive HMI Engine Finally, the Adaptive HMi Engine selects the proper modality Show fuel warning Show default panel AHE selects modality Adaptive HMI Engine Show default panel PDE takes “decisions” Show fuel warning Proactive Decision Engine Navigation Manager POI Manager Panel Manager Warning Manager
- 19. Database Remote database manages: • • • Normal Points of Interest Visual Search Multimedia information ofr Augmented Reality The database is locally buffered when a specific route is selected, to avoid connection issues during the trip
- 20. Results The result is an HMI proactively presenting the information to the driver
- 21. Results When a route is not set, the system calculates the cruise range based on current fuel level and shows it on the map
- 22. Results When the fuel level is low, the system recommends the closest gas stations
- 23. Results 3D Bubbles are used for Augmented Reality trip preview
- 24. Results Visual Odometry algorithms are used when the GPS signal gets lost in urban canyons, keeping the car position on the map up to date
- 25. Results Visual Search algorithms find a visual match on what the camera is shooting, allowing specific POI information to be delivered when actually facing a meaningful building
- 26. Results Augmented reality is used only when the car is stopped
- 27. Results Safety is achieved by reducing the amount of information when dangerous or not needed
- 28. Future Work • • • • Improve Improve Improve Improve Context Models and Rules/Engine Proactive Decision Rules/Engines mental workload control user state detection
- 29. Thank You