30.10.19

Saving lives with safety cameras and statistical analysis – Newcastle University

Source: PSE Oct/Nov 2019

 

Dr Neil Thorpe, Dr Lee Fawcett, Matt Linsley and Brett Cherry, from Newcastle University, discuss sustainably and efficiently improving road safety in the UK.

In the UK, over 80% of passenger miles are by car, van or taxi. But automobile transport, despite its numerous privileges and conveniences, has not come without a cost to human life. About five people die every day from traffic collisions on Britain’s roads. In 2017, if all collisions were prevented it would have saved the country an estimated £35bn, or 1.4% of GDP.

While great progress has been made in reducing road fatalities, it has stalled in recent years. One way to re-establish the long-term downward trend is by preventing speeding, which safety cameras have played a fundamental role in since the 2000s.

Speeding is a well-known contributing factor to fatal car crashes, involved in 24% of collisions that result in death. While the percentage of vehicles speeding in the UK has been going down since 2011, nearly half of all cars on Britain’s motorways exceed the speed limit. Speeding is also a challenge for road safety in our towns and cities.

Faced with a limited budget, when and where should authorities place safety cameras to make the most difference? GIS and other technologies help identify where so-called ‘collision hotspots’ occur at a particular point in time, but a statistical approach can attempt to predict where such collision hotspots might occur in the future to help prevent them.

Predicting collision hotspots

Researchers from both the School of Mathematics, Statistics and Physics and the School of Engineering at Newcastle University have created a software application that integrates collision hotspot prediction with existing traffic monitoring and management systems.

The software simulates the conditions that cause collisions and improves its predictions over time using both recent and historical data. This strengthens its accuracy in predicting where collision hot spots are more likely to occur, improves understanding of the causes of collisions and helps plan appropriate road safety interventions.  The work is co-funded by the Northumbria Safer Roads Initiative (NSRI), the Engineering and Physical Sciences Research Council (EPSRC), PTV Group and Newcastle University.

Safety cameras likely have an impact on road safety, but how do you measure their effectiveness in terms of value for money? To evaluate the effectiveness of safety cameras, the research team worked with a wide range of stakeholders, including highway operations and management organisations, law enforcement agencies, and local and regional transport planning authorities.

Making the most of data

The Newcastle University approach uses recent and historical records of collision counts to make predictions of traffic collisions. It puts more emphasis on recent observations for making predictions and incorporates multiple crash counts from different points in time. The accuracy of its estimates has been found superior to other approaches for collision hotspot prediction.

The first part of the approach looks at data on potential collision hotspots from across the road network to estimate the underlying average collision rate, then combines them with observed collisions and local trends.

A key advantage here is that it’s proactive rather than reactive, allowing practitioners to act and implement road safety mechanisms before collisions occur, potentially decreasing the number of crashes.

Better return on investment

As road safety budgets are continually under pressure, placing safety cameras effectively could likely have the greatest return on investment possible for preventing collisions. Without accounting for how many crashes would decrease regardless of intervention, it’s difficult to say with confidence if and by how much safety cameras always reduce the number of crashes. The Newcastle approach gives stakeholders confidence in planning decisions for road safety.

Encouraging investments in the wrong locations, rather than where collisions are likely to increase, makes matters worse for traffic management. In using cameras to deter speed, you want to make every penny count in preventing serious injuries and fatalities on the road. The software tool helps make this possible, enabling authorities to do something more about road safety and fulfil their responsibility in keeping roads safe.

Another advantage of the Newcastle approach is that it’s possible to use trends across multiple sites ‘to inform predictions at individual sites’, making best use of evidence to get more accurate predictions. It also makes it possible to look at the probability of a location exceeding a collision threshold count in future years to help determine if a safety intervention is required.

Using statistics to save lives

No other software tool like the one developed at Newcastle University has been in use for predicting collisions, and in the future it has potential to do so in real-time. Its use has resulted in lower casualty rates overall, working with road authorities around the world to help achieve Vision Zero to eliminate global fatal road crashes.

In the UK, North Yorkshire County Council and North Yorkshire Police were successful in assessing the performance of their safety cameras. The project covered 22 traffic sites from 2011-14. There were 46 casualties recorded in the period before intervention, and 33 after, reducing casualties by 13. The Newcastle analysis revealed that a reduction in eight casualties was attributed to the mobile safety cameras, with the remaining reduction of five due to other effects.

In response to this finding, North Yorkshire Police have expanded their fleet of mobile road safety cameras to reduce the number of collisions, deaths and serious injuries further on the region’s roads.

Northumberland and Tyne & Wear followed a similar route. They used the Newcastle approach to analyse traffic collision hot spots and used the results to predict future collisions and casualty rates. This made a difference for both regions because it helped them predict actual collision hotspots. Further data will be available in 2020 to determine the health and well-being of the hotspots predicted after implementing mobile safety cameras.

The NSRI, a partnership between Northumbria Police and six local authorities to reduce the number of fatalities and injuries on the roads within the Northumbria police force area, uses the tool and has provided data for testing and development. We are interested in working with more local authorities and stakeholders in helping them make the best use of their traffic collision data and increase local authority/police collaborations to reduce traffic collisions throughout the UK and further afield.

Our current research is exploring seasonal effects on collision rates, where there seems to be ‘significant seasonal variation’, and examining collisions at a finer scale. Improving predictions for the short-term future is the goal.

In future, it may be possible to make accurate real-time crash predictions, bringing traffic management and law enforcement closer to eliminating collisions that cause fatalities and serious injuries. Accurate collision prediction has an integral role to play in helping to make our motorways and cities truly smart.

 

Transport & Fleet

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