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The Car Data Gold Rush: Why Cities Need to Keep Up


For centuries, cities have developed spontaneously and uncontrollably, struggling with an inability to respond flexibly to rapidly changing conditions, while city managers acted blindly trying to find the right solutions to handle numerous challenges. Today, however, technologies finally gave us an opportunity to analyze, simulate and predict urban development with data generated on city streets, but most cities still don’t have any clear policies that would define how they use it for improved decision making.

The main reason for that is a big number of different private and public mobility operators, i.e. data sources: bus companies, ride-sharing and ride-hailing services, navigation systems developers, private traffic data collection platforms, tech giants, carmakers, etc. Each of them has its own data sharing principles, and there’s no system combining them all.

It’s relatively easy with public transport which is usually controlled by local authorities, and some cities actively use real-time bus data to improve mobility. For example, in 2016 Moscow Government invited a team of experts to analyse routes, schedules, number of passengers, and combining this data with information on population density and number of offices in different parts of the city, they managed to optimize 65 bus routes and open 58 new bus stops where it was necessary according to research.

But as public transport is just a part of daily traffic, using its data is not enough for more nuanced urban planning. To see the whole picture cities have to approach numerous private companies that collect high-quality GPS data generated by vehicles. However, the market of traffic-related data is relatively new, and in addition to technical issues, like a lack of uniform data-sharing standards, there is also a more general problem related to a lack of regulation, and as companies consider their data private and proprietary, requesting for their data is a complicated process with an unpredictable result.

For example, in a lot of cities where Uber operates local authorities ask – if not demand – its anonymous information about the trips. But the car-hailing company doesn’t seem to like the idea of giving away its valuable asset, claiming it’s a matter of drivers’ and customers’ privacy, and what cities still get from Uber is a listing of pick-up and drop-off locations based just on zip codes and neighbourhoods instead of specific addresses. Clearly, this information is limited and insufficient for meaningful analysis and decision making.

Another source of information is companies providing services like Google Maps that can also track cars and identify or even predict traffic, but for such businesses data is not just some kind of a spin-off benefit, but a core income-generating asset. Besides, modern cars increasingly have sensors and cameras to track their performance, and automobile manufacturers already look for new business opportunities here – for instance, by some forecasts the autonomous taxi market could be worth $10 trillion in the early 2030s compared to a $2 trillion vehicle sales market today.

This means data becomes more and more comprehensive and accurate each year, and also, extremely useful for urban planning purposes. For this reason, now it’s just the right time to start working on legal frameworks to create a strong template for the mutually advantageous future relationship between cities and data providers. Failing this, we risk to overlook the opportunity to take city management to the next level and for the first time in human history make evidence-based decisions to actually improve our cities.


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