Who owns the driving data?

Autonomous and automated driving are on the rise. But who owns the generated data? Who gets to use it? Who can evaluate the data and develop new business models based on it? These questions are not only interesting to the individual drivers and car manufacturers, but also to the logistics industry. If they want to develop their business models, they need a lot of information – and, therefore, they need to know what data they are allowed to use.

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Each hour, several gigabytes of data accumulate

Already today, there is a lot of information being generated during the operation of vehicles. In today’s serial vehicles, there are several gigabytes per hour including information on engine temperature, oil level, speed, tire pressure, route or individual driving behavior. In addition, there is data on the weather or the current traffic situation. “Here is real potential for social progress and new business models – from intelligent car parking to foreseeable rather than prophylactic maintenance,” says Dr. Maik Böres, Chairman of the Focus Group Connected Mobility in the Federal Association Digital Business (BVDW). “This clearly shows how valuable such data can be when it is processed and analyzed accordingly.”

Dr. Maik Böres, BVWD

“The core of the discussion is not the ownership but the use of data.”

Data ownership?

The BDWV points out that the current legal situation is clear: data cannot be owned. Data does not belong to anybody. At present, however, associations, industry and politicians are discussing whether or not it is useful to allow ownership of data by law. “Often, it is not so much about who owns the data, but rather about the question whether the citizens get to control how their personal data is used,” says Böres. “The core of the discussion is not the ownership but the use of data.”
Here, the parties are pragmatic. Logisticians such as DB Schenker often use partnership co-operation regarding the use of data, for example, when using autonomous vehicles. “This data belongs to the individual project partners, who collect it,” says Dr. Chung-Anh Tran, project leader Platooning. “The partners exchange project-relevant data with each other to further develop the project.” Because autonomous vehicles are accompanied and supervised by drivers, data can also be assigned to the individual driver. In that case, the data will be anonymized before it gets evaluated.

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Who gets to control the data?

But can this partnership model be applied to the whole industry? Here, opinions tend to differ sharply. Automakers, for instance, would like to retain control of the driving data. There is a lot of criticism, however, because, first, the personal privacy of motorists seems at risk. Second, some believe that the auto industry raises data in the name of security or better traffic flow, in order to use it for other – profitable purposes.
The insurance companies would also like to process the data freely. They could make rates dependent on the driving behavior of their customers.
Another approach is to have the drivers own their data. This is also what the majority of Germans want, as the Bitkom Digital Association together with the Association of TÜV Companies found out. Less than half, however, want to provide the data to third parties – and that only to improve traffic or to investigate crime.

What data is actually important?

It is still unclear what kind of information the companies actually seek. Some companies ask for the general provision of data, others wish to analyze only the data relevant to the driver. Weather and traffic position data is also interesting, as well as position data, speed, acceleration and braking data, according to Bitkom. Only the maintenance data of a vehicle was, for the most part, rather unimportant to the companies.

“#Autonomous and #automatized driving generates a lot of # data. But who has the right to use it?“

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However, this could change soon. Due to competitive pressure, companies need to develop their business models. In order to do this, they need increasingly more data. Furthermore, it is still unforeseeable which services and business models will make it easier to manufacture, transport and trade in the future. Sure, the future lies in the data, but it still needs to be found.