Using Predictive Analytics to Improve Public Transportation

Using Predictive Analytics to Improve Public Transportation

Using live public data feeds from trains and buses, the Swiss-German technology firm GeOps and the University of Freiburg have launched an interactive map of the world’s major transit systems to show how major cities move, according to an article in Engineering and Technology Magazine.

Called the Travic Map, it includes more than 200 systems from around the world depicted as colorful dots that slowly move across the grid. Although the interactivity is mainly based on static schedule data from transit authorities, the map does incorporate live data where possible so people can watch the public transportation systems of various cities live, according to Lauren Onita, the author of the article.

Transportation officials worldwide are collecting massive amounts of data to better understand how individuals get from place to place in their cities. While that’s important, it’s even more important for officials to “harvest” that Big Data to glean insights that they can use to improve their transportation systems, Onita noted.

That’s where predictive analytics comes in.

Using predictive analytics, transportation officials can mine the data “to find solutions to transportation problems we couldn’t really ‘see’ until recently,” according to the article.

For instance, officials in Boston could use predictive analytics to develop a citywide picture of transportation operations that’s similar to Travic, but where schedules, parking availability or passenger flux come together.

“Applications to support public transport, travel, and parking have widespread use and offer the possibility to develop smarter and more user-friendly services, which will promote more sustainable transport use in major cities,” said Phil Blythe, Professor of Intelligent Transport Systems at Newcastle University and IET (The Institution of Engineering and Technology) Fellow, in the article.

Xerox has developed an analytics platform that filters anonymous transportation data collected from commuters who buy and use tickets every day. The company presents that information with graphics to help transportation officials and parking operators understand and predict commuter needs, according to Onita.

The company’s Mobility Analytics Platform (MAP) uses data analytic algorithms and visualization tech to predict where passengers will disembark. It also predicts the effect running ahead or behind schedule—and even the weather—has on commuters, the article noted.

Adelaide in Australia is piloting MAP to improve its public transportation system by analyzing how people move between different areas of the city. But, in general, cities are still slow to take advantage of the data that they have to improve their transportation systems, according to the article.

“Most of the time transit authorities just guess or do surveys, but they ask a very small fraction of passengers,” said Leonid Antsfeld, Transportation Program Manager at Xerox, in the article.

However, if city transportation officials could get information in real time alerting them to the fact that a certain route is overloaded, they could then add more buses to the route, Antsfeld said.

“We need live data telling us how to get from point A to point B with all the different components coming together to suggest what is the best way to do it,” Antsfeld said. “This is what we call future urban mobility; it’s holistic, not fragmented—door to door.”