TomTom is the world’s leading supplier of in-car location and navigation products and services focused on providing all drivers with the world’s best navigation experience. TomTom’s products include portable navigation devices, in-dash infotainment systems, fleet management solutions, maps and real-time services, including the award-winning TomTom HD Traffic.
The Traffic and Travel Information department is collecting and evaluating anonymous Floating Car Data from connected devices, connected cars enhanced by external sources. These data are on the one hand used for live traffic information and on the other hand stored in database for further evaluation. The live traffic data allow precise statements on travel times or currents speeds on a highly segmented level in the network which can be enhanced by additional information that are required by in-car applications. The historic floating car data allow a broad and detailed analysis on precise time dependent behaviour of traffic flow on single or more complex road structures.
Fusing these different data sources and extracting the significant information to provide the different live (and thus time-critical) services is challenging as it is. We foresee however a shift towards increasingly rich and complex descriptions of relevant information such as details about traffic incidents, events that might have influence on traffic flow (such as concerts) and points of interests. Moreover, we discover new data sources and new ways of combining existing data all the time. One of the most versatile machine-processable ways of describing data is undoubtedly provided with the standards of the Semantic Web community, in particular the Resource Description Framework (RDF).
Our participation in HOBBIT helps us to assess to which degree we can expect such technologies to be applicable to our data formats and what the impact on processing performance and thus the reactiveness of our live services might be.