Difference between revisions of "Intelligent Vehicles"
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=== [[VICTIg]] (Vehicle ICT Innovation Methodology) === | === [[VICTIg]] (Vehicle ICT Innovation Methodology) === | ||
| − | [[File: VICTIg .jpg|thumb|caption|"VICTIg"]] | + | [[File: VICTIg.jpg|thumb|caption|"VICTIg"]] |
| − | * | + | * Software intense ICT functions testing |
| − | * | + | * Test software function of vehicle cooperative, automated and assisted vehicle driving. |
| − | * | + | * Develop different level of driving simulation |
=== [[ReDi2Service]] === | === [[ReDi2Service]] === | ||
Revision as of 18:06, 14 May 2014
| Intelligent Vehicles Group | |
| Research in Intelligent Vehicles | |
|---|---|
| CAISR | |
| Contact: Roland Philippsen | |
Contents
Funding and Partners
| Funding Agencies | Academic & Research Institutions | Industrial Partners |
|---|---|---|
| European Commission (CORDIS - Seventh Framework Programme) | Örebro University | Autoliv |
| KK-stiftelsen | University of Skövde | Volvo Group Trucks Technology |
| Vinnova | SP Technical Research Institute of Sweden | Toyota Material Handling Europe AB |
| Chalmers University of Technology | Optronic Partner dp AB | |
| VTI (the Swedish National Road and Transport Research Institute) | Kollmorgen Särö AB | |
| TNO | Volvo Car Corporation | |
| Institut de Robòtica i Informàtica Industrial |
People
- Björn Åstrand
- Cristofer Englund
- Jennifer David
- Martin Cooney
- Mohamed-Rafik Bouguelia
- Sepideh Pashami
- Stefan Byttner
- Sławomir Nowaczyk
- Thorsteinn Rögnvaldsson
- Yuantao Fan
- Jawad Masood
Projects
AIMS (Automatic Inventory and Mapping of Stock)
An intelligent warehouse environment that autonomously builds a map of articles in a warehouse and relates article identity from the warehouse database with the article’s position (metric) and visual appearance in the warehouse.
- Intelligent warehouse: identity, location, and appearance of articles
- recognition and clustering
- 3D perception
- localization, mapping and map maintenance
Cargo ANTs
- automated cargo handling ITS
- AGVs at trucks in ports and terminals
- multi-vehicle path planning and adaptation
fuelFEET (Fuel FOT Energy Efficient Transport)
Explore factors affecting fuel consumption.
- Fuel FOT Energy Efficient Transport
- which fuel consumption factors can be influenced by the driver or fleet owner?
InnoMerge
- transfer to and from emerging markets
- uptime & safety
- diagnostics, maintenance, monitoring
FFI NG-TEST (Next Generation Test)
Next Generation Test Methods for Active Safety Functions. "NG TEST" aims to move parts of the verification and validation of active safety functions from the proving ground to a complete or partly virtual environment. validated virtual testing of next-generation ADAS:
- CPS modeling, executable math for requirement specification.
- real-time positioning, rapid accurate positioning on test tracks.
VICTIg (Vehicle ICT Innovation Methodology)
- Software intense ICT functions testing
- Test software function of vehicle cooperative, automated and assisted vehicle driving.
- Develop different level of driving simulation
ReDi2Service
Algorithms for self-monitoring vehicles, capable of discovering and describing their own operation, as well as detecting deviations from the norm. Data mining across many data streams available on-board a modern truck or bus. Comparing discovered relations across the whole fleet. Faults and component wear can be discovered early and continuously monitored.
- Remote Diagnostic Tools and Services
- self-monitor operation and deviations
- data mining: on-board, maintenance logs, driver comments, engineering expertise
V-Charge
Autonomous navigation in parking structures using consumer car sensor. Halmstad University is involved in V-Charge indirectly by supervising PhD student. External link to V-Charge webpage.
In4Uptime
- Vehicle diagnostics and predictive maintenance
- on-board data stream mining
- Data analysis with special focus on developing Component Degradation Models.
