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Five Ways Big Data Will Revolutionize City and Transportation Planning

It’s time for city and transportation planners to meet the power of big data! Mobile phone data holds valuable insights for city and transportation planners looking to modernize their processes and better prepare for a rapidly growing population.

Currently city and transportation infrastructure decisions in the U.S. rely on costly household travel surveys for information. With this static information, city officials and real estate developers make billion dollar investment decisions, such as where to build new housing, if more public transit is needed and where to make infrastructure upgrades. The sample size is small (less than 1% of the population) due to the expense and surveys are only conducted every three to five years. City governments also struggle to get a strong response rate which makes the modeling even less accurate.

Meanwhile we’re in a digital age of real time data available with commuting patterns, demographics and behavior from anonymized mobile phone data that is actionable and far more accurate than a traditional U.S. survey.

Near real time data in Atlanta demonstrates traffic decreases (blue) at the site of a bridge collapse and the traffic detour routes (orange).Near real time data in Atlanta demonstrates traffic decreases (blue) at the site of a bridge collapse and the traffic detour routes (orange).

Five crucial points emerge to demonstrate the superiority of mobile phone data over surveys:

● Scale: More than 300 million mobile devices in the U.S. generate data on a near real time basis, signaling billions of locations and behavioral patterns. In comparison, a traditional U.S. survey samples thousands of people — a fraction of the population — living in specific metropolitan areas.

● Timeliness: Not only is mobile phone data updated on a near real time basis, but it tells a complete story of users’ mobility behavior and habits. Traditional surveys cannot anticipate trends such as the popularity of ride-sharing services.

● Accuracy: Low income households are less likely to respond to traditional surveys, so the results are not an accurate reflection of the population. Meanwhile, mobile phones collect data from households across all income levels.

● Actionable: Data shows trends including travel patterns, home and work neighborhoods and mobile app-usage. For instance, if a growing population relies on ride-sharing apps rather than owning a car, then housing developers should reconsider building garages on new housing intended for millennials.

● Demographics: User demographics — such as age, interests and home location — provide a comprehensive picture of the population through anonymous mobile phone data. Traditional U.S. surveys do not provide an in-depth understanding of the population.

Overall, big data improves information accuracy to allow commercial developers, cities and transportation agencies make better investment decisions. At times when everyone is under pressure to be more efficient, we must embrace new data-driven technology for smarter city and transportation planning.