Presenting data for evidence-based urban planning and regulation

Evgeny Klochikhin
DataSeries
Published in
3 min readJul 21, 2020

Urban planners desperately need data. With good data, they can make evidence-based decisions about how to regulate traffic and mobility in their cities. Ultimately, everyone benefits.

Vehicle data offers much more evidence for urban planning decisions.

Data can reveal critical information about traffic patterns within a city. Let’s say that there’s a twenty-minute route within a city. But a car takes a full 40 minutes to complete the route. Good data can tell us why the 20-minute delay happened. Did the driver just grab a coffee? Or is there a larger problem, like congestion or street closures, that contributed to the delay?

This has implications for all kinds of decisions that urban planners must make. On a micro level, data can help clarify many of the day-to-day decisions that city officials make. If we close this street on a Wednesday afternoon in July, how will traffic be impacted? Can the surrounding streets accommodate the extra vehicles? With granular vehicle data rather than scattered infrastructure-based observations, e.g., from cameras, we can answer these questions with much greater confidence.

On a macro level, data can provide guidance for big-picture decisions. Do we need to add an extra lane to a particular street? Are people struggling to find parking downtown during peak hours? Urban planners will benefit greatly from understanding where vehicles are coming from, how they’re moving through the city, and what problems they’re experiencing along the way. Quality data can lead to evidence-based decisions, allowing urban planners to make cities better.

Despite the massive benefits of data, it’s often been hard for urban planners to obtain quality data. Too often, if urban planners want to know how many cars are parked downtown on a Saturday afternoon, someone must go and physically count them. Although video cameras and other static infrastructure have useful information to offer, they have limitations. A camera at an intersection can only reveal what goes on at that intersection — not where a car may have been before or after passing through.

Cell phone companies, of course, have massive amounts of data about people’s mobility patterns. But they have been extremely reluctant to share that data with urban planners because its monetary value is so high.

Here at Parkofon, we want to provide cities with the data they need to make good decisions — and we have a model to do it. By enabling our location technology on their cars, drivers receive connected services that improve the driving experience. We are completely transparent about what we’re doing and why. We are interested in helping cities develop evidence-based policies, not jeopardizing individual privacy.

Once we collect data, using complete transparency, we can use the vehicle data to help urban planners. Currently we are proud to collaborate with the City of Turin to analyze traffic data for the public good. We are interested in partnering with additional cities in the future. Eventually, we plan to offer full support for our data collection system, including analytics and visualization tools.

As scientists, we know that good data is essential for good policy. We are committed to helping cities make evidence-based decisions so that we can all benefit.

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Evgeny Klochikhin
DataSeries

Evgeny Klochikhin, PhD is the CEO of Parkofon, a smart mobility company building a fully connected #MaaS platform. Innovation scholar, data scientist, engineer.