Intelligent transport: hosted traffic light systems upgrade city travel

Buses benefit from priority decision making, but GLOSA data and time-to-green information can help car drivers too.
24 August 2022

Lighting the way: London has served as a valuable test-bed for transport monitoring systems developers, but smart city solutions can be found elsewhere too. Image credit: Shutterstock.

It’s all too easy to complain about traffic, but look a bit deeper and you’ll likely find technology hard at work on making journeys easier for commuters. City planners have been deploying intelligent transport solutions for some time, and these systems – such as smart traffic lights – do make a difference. Today, what’s more likely to be blocking the path to smoother travel isn’t a lack of traffic management hardware and software, it’s having a jumble of systems that makes for inefficient communications across the transport network. But providers are working hard to change that by offering modern hosted solutions that enable urban traffic management controllers to migrate away from older in-house equipment that’s no longer up to the job.

Legacy setups can be a pain on multiple fronts, as maintenance and power costs add to the burden. But on the flip side, it makes the decision to upgrade an even easier one for operators, who turn to firms such as Ticketer – one of a number of global players that are helping customers to roll out integrated traffic management systems. This month, Ticketer – which, since the company’s acquisition of Faro, includes facilities not just in the UK, but also in Norway, Poland, Sweden, Finland, and Denmark – announced the completion of another successful traffic light priority (TLP) project. The solution, which links around 300 sets of traffic lights, has gone live in Bristol – a city in the South West of England – and could add 12-15% additional capacity to the road transport network.

Green wave

TLP systems can react to changing traffic conditions to minimize journey times for bus passengers, gathering signals from transport operators’ existing GPS sensors and even counting the number of pedestrians waiting at a crossing, for example. They are welcome too, as reduced waiting times at traffic lights translate into reduced fuel consumption – the long service times of buses mean that even small changes can amount to notable operational savings.

Urban traffic control solutions – Scoot by TRL Software is another example – can be programmed to adjust queuing times based on emissions levels detected by roadside pollution sensors. And central control models are able to digest data from across the city to prioritize routes. In 2020, Siemens and Transport for London teamed up on a real time optimization system that would be able to pull in data from a variety of transport modes to further enhance travel in the UK capital. London, which hosted the Olympic games in 2012 and a stage of the Tour de France in 2014, has served as a valuable test-bed for developers of transport systems technologies.

Plans in the city include a surface intelligent transport systems program (due to be completed in 2022/23), which features the real time optimizer work carried out with Siemens – who spun out its intelligent transport systems expertise as an independently managed business, Yunex Traffic, in July 2021, and announced that it would divest the operation to Italian transport group Atlantia in a deal that was completed this year. Improving transportation is good business and automotive firms have taken note too.


Car maker Audi debuted green light speed optimized speed advisory (GLOSA) in its vehicles back in 2016. Using traffic signal cycle information provided over vehicle-to-everything (V2X) infrastructure – which leverages a 4G LTE mobile connection in the case of the Audi example – together with the relative position of the vehicle, GLOSA notifies drivers of the speed required to arrive at upcoming traffic lights as they turn green. By 2019, Audi users with compatible vehicles could access traffic light information in 13 metro areas in the US, including Las Vegas, Los Angeles, New York City, San Francisco, Washington, D.C., and other locations. Research has shown that reducing stop and go driving patterns can make a big difference in energy consumption (saving fuel in ICE vehicles or making battery charges last longer for EV users). Tailpipe emissions are reduced too, in fossil fuel-powered scenarios – most likely by avoiding that energy-hungry blast of acceleration away from the lights.

Installation costs for cities appear modest, based on trials conducted in the UK back in 2018 – working out at around GBP 1000 per junction. And that spend could make motorists happy. Drivers traveling over a 10-junction route lasting 6 km experienced a 7% reduction in journey times, which is a noticeable result. More recently, field tests have been conducted in the US using heavy goods vehicles (PDF), which examined how providing either timing information alone or GLOSA estimates compared with an uninformed base case. In the GLOSA example, which delivered the best results, the 30 participants (who each made 16 trips) were able to save, on average, 22.1 % in fuel. The tests were carried out on Virginia Tech Transportation Institute’s smart road – a 3.5 km section equipped with wireless roadside equipment. And the researchers point to the generation of eco-driving algorithms, which are ripe for making use of data from smart cities, as an interesting space to watch.