Difference between revisions of "Vehicle Operation Classification"
| Line 9: | Line 9: | ||
... | ... | ||
|Prerequisites=Cooperating Intelligent Systems and Learning Systems courses | |Prerequisites=Cooperating Intelligent Systems and Learning Systems courses | ||
| − | |Supervisor=Sławomir Nowaczyk, | + | |Supervisor=Sławomir Nowaczyk, Yuantao Fan |
|Level=Master | |Level=Master | ||
|Status=Open | |Status=Open | ||
Revision as of 16:48, 25 October 2016
| Title | Vehicle Operation Classification |
|---|---|
| Summary | Classify modes of operation of Volvo vehicles based on on-board data |
| Keywords | Data Mining |
| TimeFrame | Spring 2016 |
| References | Time series classification
Unsupervised and semi-supervised clustering ... |
| Prerequisites | Cooperating Intelligent Systems and Learning Systems courses |
| Author | |
| Supervisor | Sławomir Nowaczyk, Yuantao Fan |
| Level | Master |
| Status | Open |
In the ReDi2Service project we have collected approximately 500GB of data from Volvo buses in normal operation. It is interesting to analyse this data from the usage point of view, and come up with good description and/or classification (possibly hierarchical or even an ontology) of vehicle operation.
The data contains both GPS positions, as well as on-board signals such as vehicle speed or engine torque. The goal of the project is to provide a framework for organising the data in a way that will facilitate future access to interesting portions of this data according to multiple criteria.
We are interested in both low-level information (for example, detecting workshop visits, splitting the data into trips from turning the engine on to turning it off, distinguishing between highway and in-city operation, or finding uphill and downhill driving) as well as in more abstract description (is the bus in regular line traffic or performing some other duty, automatically finding similarities and differences between missions, etc).
More details to come...
