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Harnessing data from driverless cars to improve transportation.
Self-driving cars were once thought of as a far-off, and maybe even impossible, concept, but they’re here now. At the end of November, General Motors announced its plan to launch a fleet of driverless cars — without backup drivers — across several major U.S. cities, beginning in 2019. In doing so, the auto industry signified that it’s prepared to lead a dramatic shift in how both humans and commercial goods move from place to place.

Of course, powering this initiative is data — and likely exabytes of it. Driverless vehicles depend on data for everything from communicating their position on the road, to calculating speed and braking distances, to recognizing traffic signals and upcoming hazards in their path.

While the idea of AVs whisking us away to our destinations with little to no effort does sound appealing on its own, an even greater prospect comes when you consider how such information will impact the travel experience itself. The data generated from these vehicles is highly personal — from radio presets and audiobook preferences to commuting schedules and favorite destinations. With this data, automakers and other vendors can learn a great deal about a vehicle’s owner and occupants by analyzing their travel history in real time.

When you consider the sheer volume of user preferences, demographic information, and trip analysis required for a driverless vehicle to operate, the conversation evokes several different questions: