A recent smarter traffic pilot in Cologne, Germany, illustrated how the city can predict, better manage and in many instances avoid traffic jams and trouble spots with analytics.
The pilot, conducted by the city and IBM, wrapped up with some surprising results: City traffic engineers and IBM could predict traffic volume and flow with over 90% accuracy and up to 30 minutes in advance.
That level of accuracy would give travelers a good indication of what to expect and what they should do next: change their travel time, take an alternate route or maybe take public transportation instead of driving.
"The traffic prediction pilot results are very encouraging," said Thomas Weil, director of the Cologne Traffic Control Center. "Having the ability to create actionable insight from the traffic monitoring data gives us an ability to better manage congestion as well as provide citizens with more precise traffic information. Our Traffic Control Center would be able to optimize current traffic flow while anticipating and planning for potential traffic incidents."
Cologne could use the help. It's Germany's fourth largest city with a population of a little over one million – and it is a retail center, a hub for trade shows and a cultural center with numerous galleries and museums. The city's traffic density and congestion made it clear to city officials they needed to find an effective way to better manage and optimize traffic flow and grow the capacity of its transportation networks.
The Traffic Control Center collected real-time data from over 150 monitoring stations and 20 traffic cameras on roads, highways and intersections considered traffic trouble spots.
IBM transportation experts and researchers worked with the city to analyze data from traffic monitoring stations on the left bank of the Rhine River for six weeks with help from the IBM Traffic Prediction Tool and its Intelligent Transportation solutions. The results comparing traffic prediction tool accuracy with real-time data found the accuracy of short-term forecasting (30 minutes ahead) to be 94% for the speed of the vehicle and 87% for traffic volume.
"As one of the first congestion-prone cities to do so, Cologne has taken an important step in the right direction with this project," said Eric-Mark Huitema, IBM Smarter Transportation leader in Europe. "Intelligent traffic management based on precise forecasting techniques can help cities anticipate and avoid traffic congestion and possibly reduce the volume of traffic, resulting in a more sustainable transportation network."