Stephen Russell, transportation director at engineering consultancy Sweco UK, explains that using data-driven technology to optimise traffic flows could help unlock one of the UK’s major transport challenges.
The recent National Infrastructure Assessment (NIA) report highlighted the importance of the infrastructure investment currently being channelled into inter-urban connectivity. For example, Highways England funding will deliver new major route corridors and the investment in HS2 will herald the beginning of a new dawn for the UK rail network.
These are undoubtedly key programmes that will give a major boost to the continuing growth of the UK’s regional economies. But the report also pointed out that greater efforts need to be made to address the other major challenge – improving mobility within our cities, not just between them.
The main strategy that UK city councils have adopted to tackle this is through public transport, specifically enhancing bus and tram networks. Light rail schemes have now been rolled out across many of the UK’s major cities, recording numerous successes. The Manchester tram saw an extra four million trips taken in the year to September 2017, which represents an increase of 11% year-on-year. But the problem is that public transport only accounts for an average of 20% of all motorised travel in urban areas.
Active travel programmes – which involve the use of any form of physical activity, be it walking, cycling or even rollerblading, to get from A to B – form part of the solution and we’re seeing a growing number of forward-thinking councils engage with businesses to encourage people to travel sustainably to reduce congestion.
Yet there is more to be done to increase the use of public transport. Delivering a service that can move people more efficiently across urban areas is one strategy to achieve this. New infrastructure is part of the solution but collecting, analysing and using data from a growing number of sources, to get more out of existing transport networks has a vital role to play too.
A key step towards improving mobility and connectivity
Across the motorway network, authorities are already using traffic parameters to collect data such as vehicle count, speed, flow and classification. This is generally derived from radar detection and inductive loops installed on the carriageway to automatically control traffic speed, reduce congestion and improve journey times. But, in the near future, connected cars and the availability of more data streams will help make these transport links even smarter.
The same concept can be adopted across our urban transport networks by capturing data from the people using them and the thousands of traffic signals located in each city. The theory is that by collating and analysing this data over a short period of time, detailed models can be produced, depicting how people and vehicles move through a city and how this fluctuates depending on variables such as time of day, weather changes or the impact of maintenance.
Sweco is trialling this concept in Helmond in the Netherlands. Our simulations have shown that a cloud-based system that uses this data to automatically change traffic signals has the potential to reduce congestion by up to 40%, thereby improving journey time reliability, network resilience and air quality.
The programme involves collecting data from existing loop sensors – installed at certain points before each signal – which detect vehicle movement through changes in the magnetic field. It then merges this information with GPS location data, collected from apps on people’s smartphones and from sim cards embedded in ticketing systems on-board buses and trams.
Previously this information would have been passed to local authorities to advise on how their signalling could be changed. Instead, this system uses an algorithm to create a predictive model from the data, and then connects directly with each traffic signal via the cloud to customise its timings. The trial started on 12 September and, once completed, we expect several further trials to be rolled out across other urban areas in the Netherlands.
By providing this flexibility, it holds the potential for councils to optimise traffic flow and give far greater priority to public transport. For example, ‘green light phases’ could be introduced at intersections on busy rush hour routes. It would also undoubtedly have a positive impact on air quality, which is a key concern for city councils in meeting their carbon reduction targets.
Councils up and down the country are certainly focusing on improving cross-city connectivity. But rather than concentrating solely on introducing new infrastructure for public transport, advances in data analysis and cloud technology will soon offer the potential to significantly cut journey times across their cities.