Traffic flow improved by big data analytics used to predict bus arrival and transit times

Advertising Feature Dublin City Council delivers housing, water and transport services to 1.2 million citizens in the Irish capital. The roads and traffic department manages the city’s road network and a bus fleet of roughly 1,000 vehicles

IBM

Mon, Mar 31, 2014, 09:52

The opportunity

To improve public transport services, Dublin City Council sought a way to dynamically monitor the movement of each of the city’s 1,000 buses and better gauge if each one was operating on time.

What makes it smarter

The city deployed an intelligent traffic control solution that uses geospatial data from GPS-equipped buses to visually display the near-real-time position of each bus on a digital city map. Controllers can locate areas experiencing delays at a glance and instantly drill down to live camera feeds to identify root causes. Predictive analytics take into account speed, traffic flow and other factors to continually generate up-to-date estimates for bus arrival and transit times.

Real business results

The solution provides a dynamic, near-real-time view of bus movements and arrival times, empowering traffic controllers to help ensure buses run on time and riders receive excellent service. Using the solution’s dynamic digital map and camera feeds, controllers can more quickly identify congestion in its early stages and gather the information they need to mitigate the impact on affected areas. By making underlying bus fleet trends more transparent to planners, Dublin City Council can also more effectively manage resources and optimize bus routes to help save energy and reduce pollution.

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To learn more about Dublin City Council, visit www.dublincity.ie.