RISE ICT stories: Big data tells us stories about reality

Cars on highway in sunset

The time has come for heavy traffic to be digitalized. Real life data from the vehicles, the environment and the traffic situation will pave the way for better service from the trucks, more efficient traffic flows and reduced environmental impacts.

The Swedish vehicle manufacturers, Volvo Cars, AB Volvo, and Scania, together with the Swedish Transport Administration (Trafikverket), Fordonskomponentgruppen, and RISE SICS, have started a strategic program to find out how big data analytics can benefit heavy traffic. When real data are used as a basis for decisions, the manufacturers and traffic planners can develop new services based on the real needs of the customers. The initiative is financed by the governmental agency VINNOVA and the vehicle industry (through FFI) and focuses on environment and safety.

Per Werthén, manager of the project at Volvo Cars, says big data analytics is the obvious next step in vehicle development.

“We already keep track of everything in the vehicle. We are now eager to hear the stories about reality that are hidden within these data.”

So far, big data analytics has mainly been used for human-generated data. Now, as digitalization affects all areas of society, we can ask which data can be harvested from the physical environment to tell us what is really going on there, too. In a vehicle this can be the story of brake pedal behavior, driving patterns, the driver’s eye movements, fuel consumption or air condition in the cab. In the traffic we can learn about what causes accidents, optimization of traffic flow, environmental impacts etc.

Decisions in transportation are currently generally based on experience and standards. When decisions are instead based on current data from actual situations, we will achieve models that better match reality. We already have much of the required data, which is picked up by different sensors. The challenge, in addition to storing and managing the data, is to develop algorithms that extract the value-generating information for the specific application and business model. This requires: careful selection of relevant data sources for the application; finding the right algorithms and analysis models to apply; and matching it with an appropriate choice of computational platform and infrastructure.

With the many years of experience and research in big data analytics conducted at SICS, SICS’s researchers will strike the required balance, mapping up what can be done with big data analytics and creating innovative technical algorithmic solutions for the Swedish automotive industry.

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Big data analytics, machine learning and optimization at RISE SICS

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