Traffic Signal Optimisation and Virtual Infrastructure – a case study

In this case study as part of the Traffic Signals and Management Theme Week, Bradley Taylor, UK Sales Director at INRIX explains what his company’s recent success with SBRI means for current and future transport agency operations

The Small Business Research Initiative (SBRI) has helped drive innovation for public benefit. A recent SBRI-backed competition asked the private sector to produce solutions to help the UK lead a clean, growth-led recovery from the coronavirus pandemic and towards improving net zero carbon emissions.

This SBRI challenge is managed by the Department for Transport (DfT) and is part of a multi-pronged effort to deliver Government goals for reduced traffic congestion and greenhouse gas emission. The challenge set by the DfT was, how can we better use data analysis to support local authorities in reducing congestion.

Key Takeaways from SBRI

The SBRI project from INRIX was a platform of tools developed in collaboration with 12 local authorities under the name “Performance Analysis Trajectory Help (PATH)” via a collaborative approach in line with Government Data Service principles. Using GPS floating vehicle data, PATH delivered a virtual infrastructure of corridors and junctions, giving the authorities high-level awareness of traffic signal performance.

These tools empower local authorities to assess signal performance broadly along road corridors or zoom in on a particular junction of their choice. They can see vehicle trip delay data visualised through time-space diagrams (Figure 1.), offering actionable insights into signal performance and congestion. This enables the identification and prioritisation of maintenance projects where work can be most impactful, and to follow up with before-and-after comparisons when work is completed.

The PATH project provided public sector clients with the tools (and data) to assess their key routes and roads to optimise traffic signals. The metrics within PATH helped identify the most impactful traffic signals junctions that cause a delay to the travelling public.

Figure 1. Time-space diagrams indicate vehicle trip delays, giving insight into signal performance

Why Virtual Infrastructure Matters

PATH verified the potential value of stepping away from traditional methods of determining performance and into data-driven software for traffic signal optimisation. Traditional methods call for physical hardware to measure traffic congestion, but such solutions are costly as they must be monitored, maintained, and replaced on an ongoing basis.

Getting meaningful intelligence from hardware has been a challenge as well. Data collected at the ground level by sensors requires a sizeable effort to extract and analyse, and even still, only offers limited understanding of how individual signals impact peripheral junctions. This makes it difficult for traffic managers to prioritise signal retiming projects where they are needed most. There is also a saving on the time and budget local authorities burn through each year pulling data from urban traffic control systems, either from following a pre-determined maintenance schedule or in response to a suspected issue, only to find that the signal in question was performing optimally all along. What if they didn’t need to?

Traffic signal optimisation is a key step in reducing traffic congestion, lengthy trip delays, and carbon emissions. Ensuring local authorities can pinpoint the most significant issues and direct their resources appropriately will produce the best results. Cloud-based solutions powered by GPS floating vehicle data make this possible.

Figure 2. Heat maps give local authorities high-level awareness of where congestion is the worst and during which part of the day

Community Feedback

Collaboration played an essential role to the success of PATH, as it was feedback from local authorities that helped to create the best value solution. For many, the high-level awareness of road network performance that virtual infrastructure provides was very well received. “It is important for us to see the impact on adjoining side roads,” said Daniel Anderton, Transport Control Centre Manager at Hertfordshire County Council. “We would use the metrics to help review our junction delays, [which is] great for supporting the adjustment of signal timings.”

The challenge for traffic management authorities isn’t only to ensure optimal signal performance; they must provide demonstrable evidence to accurately model future funding requirements or increase awareness of major issues. “We can evidence the junctions that are problematic and the time of day we are seeing delay,” said Jackie Davies of Bristol Traffic Control. “Using the platform, we can prioritise our validation and maintenance programmes, [and] it will help us to push for additional budget to support junction improvements.”

The DfT acknowledges the importance of embracing data-driven solutions to support policy objectives. “The PATH project has brought a crucial step-change towards a clearer and deeper understanding of traffic signal performance,” Darren Capes, ITS Policy Lead at the DfT stated. “We must continue to make the best use of data and particularly information that is typically inaccessible or too complex to understand in an operational environment. PATH begins to provide us with the tools we need to improve congestion and travel delay, ultimately contributing towards reduced carbon emissions and better journey reliability.”

INRIX IQ Signal Analytics, a fully integrated application based on the same principle of utilising floating vehicle data to optimise signal performance, is live for American markets and has already been used by several public transportation agencies to great effect. We plan to unify the learnings of PATH with this existing application, to deliver a comprehensive solution to the UK in the near future.

Through this development project, GPS floating vehicle data has proven to be a viable (even superior) alternative to legacy traffic signal performance measurement methods. With the growing urgency to reduce traffic congestion and manage carbon emissions, Local Authorities face pressure to demonstrate progress towards local policy goals. Those that are ready to embrace data-driven solutions will quickly realise improved success metrics, budget savings, and reduced greenhouse gas emissions.

To find out more about how INRIX is shaping the future of traffic signal management in the UK, click here. A summary of SBRI projects has been published on the Transport Technology Forum (TTF) website. To learn more about the projects of the SBRI Congestion Challenge, visit https://ttf.uk.net/resources/sbri-congestion-challenge-project-reports/

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