A Smarter Transport Management System for London with the Help of WSO2

Transport for London (TfL) has a daily challenge – to keep a city of over 8 million people moving around the metropolis. Its magnitude can neither guarantee the transport system will always absorb commuters nor give them a congestion-free experience. It is a place where the smallest of changes would have a massive impact on your journey. Citing an example, Roland Major, a former enterprise architect at TfL, says that a London Underground strike once saw a 3% increase in traffic and a staggering 90 minute increase in journey time. Estimates project a 60% increase in congestion around central London by 2031.

Given all these complications, TfL decided to become more intelligent with technology to reduce commuter times, make the roads safer for pedestrians, cyclists and drivers, and to slow the pace of traffic. Intelligence and data with a purpose are the buzzwords here. “We need better understanding of real-time demand. What insight can we get from our data, and how can we get innovative with all this information?” says Roland. He was actively involved with TfL’s Surface Intelligent Transport System (or SITS), a project that aims to better manage the city’s entire road space of pavements, cycle lanes, and motorways.

SITS’ business proposition is that it can offer billion pounds’ worth benefit to London by identifying delays in the road networks sooner than it is done at present: “We weren’t detecting incidents, and by the time we have detected them, they were already over. With technology, we can see these incidents early. We recognized that the market can do sensible things with our data,” says Roland. For example, within the traffic light system in London, TfL manages an estimated 7,000 junctions around the city and 14,000 magnetometers detect millions of daily events. This data is discarded after analysis; however, if used, TfL realized that the response time to delays improved by 15 minutes.

TfL has a 10 year plan in place, with all the of different required components mapped out. Data analytics form the core of this operational model. Data is obtained from GPS systems and bus routes. The road incidents are logged and used to determine what additional information is needed to understand and manage each leg of commuter journeys. All the data is hosted on the cloud and currently TfL is in the process of adding these components to the framework.

TfL’s transport management system

London’s new road management system relies on WSO2’s API management, integration, identity and access management, and analytics products for the intelligent work needed. These products are deployed on a private cloud managed by WSO2. The starting point – LondonWorks, a registry of all road works and street related events, both planned and current, in the Greater London area. LondonWorks is used to assess road networks, coordinate the various road works to minimize congestion and for inspection, compliance, and monitoring. Maps and forms of type data have been integrated to allow entry of incidents into the system and their identification on the map.

As their model progresses, TfL has ambitious plans for all the data they have streaming in – big data analytics to give them more insights to road movements, which will enable them to give the necessary alerts and empower them with smarter ways to deliver better, safer commuter experiences for London.

Watch Roland’s presentation for more details on TfL’s plans for London.

Explore the WSO2 middleware platform with its offerings in API management, integration, identity and access management, analytics, and IoT.

Did you know that WSO2 won TfL’s data analytics Hackathon contest? Learn all about it.