Monitoring of changes in driving speed in DB long-distance traffic
In an interactive web application, GPS data and other data are used to display sections of long-distance traffic (FV) on which trains are travelling more slowly than usual.
Slow speed points recognisable at a glance
Focusing on the most important jobs possible
Challenge
- In slow speed sections, FV trains may only run at reduced speed.
These therefore have a significant influence on the FV punctuality of Deutsche Bahn - Slow speed sections of high speed traffic (>160km/h) are not relevant to safety and therefore do not need to be recorded centrally
- Due to this difficult data situation, there is a lack of transparency about the current operating situation and efficient management of punctuality is difficult.
Solution
- Speed dips are determined from the GPS data of long-distance trains using an empirical approach
- The identified route sections are visualised on a map and their relevance is determined based on the travel time loss from the operational data
- An R-Shiny web application intersects the data with information from the network control centre and provides the content to a panel of experts
Result
- The slow speed sections are compiled in a view
- A focus on the most important places is possible on the basis of the travel time loss
Are you interested in your own use cases?
Challenge
An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.
Solution
There will be a interactive and Flexible application, including of different maps with two different views implemented.
Result
Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.