Skip to main content

Predictive analytics aid Cologne’s congestion management

The City of Cologne, Germany, and IBM have completed a smarter traffic pilot to predict and manage traffic flow and road congestion in the city. The pilot demonstrates how the city of Cologne can anticipate, better manage, and in many cases, avoid traffic jams and trouble spots across the city using analytics technology. Germany’s fourth largest city, Cologne has a population of just over one million, is a retail centre, hub for trade shows and a cultural center with many museums and galleries. The increas
January 17, 2013 Read time: 3 mins
The City of Cologne, Germany, and 62 IBM have completed a smarter traffic pilot to predict and manage traffic flow and road congestion in the city. The pilot demonstrates how the city of Cologne can anticipate, better manage, and in many cases, avoid traffic jams and trouble spots across the city using analytics technology.

Germany’s fourth largest city, Cologne has a population of just over one million, is a retail centre, hub for trade shows and a cultural center with many museums and galleries. The increase in traffic density and congestion has prompted the city to seek out new ways to better manage and optimise traffic flow and increase the capacity if its transportation networks within the constraints of its infrastructure.

The traffic control centre collects real-time data from more than 150 monitoring stations and twenty traffic cameras on the roads, highways and at intersections that are known as traffic hot spots. However, the control centre currently does not have advanced traffic management tools or a way to forecast what traffic will be like in the near future. The advanced transportation management software could help traffic officials identify imminent road congestion and help them plan and respond ahead of time.

IBM transportation experts and researchers worked with the City of Cologne to analyse data from its traffic monitoring stations along the on the left bank of the Rhine for a period of six weeks with the aid of the IBM traffic prediction tool and IBM, intelligent transportation solutions. The detailed results, which compare the accuracy of the traffic prediction tool to the real-time data, revealed the accuracy of short-term forecasting for thirty minutes ahead to be 94 percent for vehicle speed and 87 percent for the volume of traffic.

The city’s traffic engineers and IBM were able to predict traffic volume and flow with over 90 percent accuracy up to 30 minutes in advance. As a result, travelers would be able to better plan ahead and determine whether they should leave at a different time, plan an alternate route or use a different mode of transportation.

“The traffic prediction pilot results are very encouraging,” said Thomas Weil, director of the Cologne traffic control centre. “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 centre would be able to optimise current traffic flow while anticipating and planning for potential traffic incidents.”

“As one of the first congestion-prone large 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, Europe. “Intelligent traffic management based on precise forecasting techniques can help cities anticipate and avoid traffic congestion and possibly reduce the volume of traffic, results in a more sustainable transportation network.”

The traffic prediction tool developed by IBM Research is a component of the IBM's intelligent operation centre software, which draws on experience gained from smarter cities projects with cities around the world.

For more information on companies in this article

Related Content

  • Smart city traffic systems ‘to reduce congestion by 2019’
    January 14, 2015
    A new report from Juniper Research forecasts that smart city traffic management and parking projects will reduce cumulative global emissions in the order of 164 million metric tonnes of CO2 between 2014 and 2019 - equivalent to the annual emissions produced by 35 million vehicles. Not only will this benefit the environment, but it will also significantly impact the quality of city dwellers' lives, with some 700 million automobiles projected to be on city roads by 2019. The report, Smart Cities: Strategie
  • Top 5 trends in vision technology
    June 24, 2021
    Artificial intelligence and deep learning algorithms are among the major trends having an impact on road traffic enforcement, according to leading companies in the vision sector
  • Data exploits parking potential
    March 11, 2015
    David Crawford parallel parks with innovations in two continents. Surveys of US cities indicate that drivers searching for parking can account for up to 37% of all urban traffic congestion. A 2011 study by IBM of 20 cities around the world found that nearly six out of ten drivers had abandoned their search for a parking space at least once; while motorists generally spent on average 20 minutes looking for a sought-after spot.
  • Data crunching ‘can prevent cars crashing’
    March 25, 2013
    Having already cut traffic collisions resulting in injuries and deaths by nearly forty per cent in five years by analysing patterns from data it has collected, the city of Edmonton, Canada, is using predictive technologies to increase road safety even more. The city’s Office of Traffic Safety (OTS) has installed as many as 200 digital signs as just one element of an innovative traffic safety program that has dramatically reduced vehicle collisions in the Edmonton region since OTS launched in late 2006. Unde