Using Big Data to Optimise Road Improvement Spend

Data collection and analysis that would have taken months can now be performed in seconds. And big data can help planners and funders ensure that road infrastructure spending is optimised and society gains the most.

Economics is the study of scarce resources, and what is more scarce than our roadways. For example, in England the Strategic Road Network represents just 2% of all roads but carries over a third of all traffic and two thirds of all freight. 

Over the last fifty years the volume of traffic in the UK has risen dramatically - from 70 billion vehicle miles travelled per year in 1960-61 to 304 billion in 2011-12. However, the level of public investment in the road network has not kept pace with this trend, spending a third of what it did in the 1970s and 80s.

As a result, congestion has risen dramatically damaging the economy. Combined with sustained economic growth and increased efforts by cities on enabling multi-modal transport options, road traffic may continue to increase by up to 50%. In response, the UK has announced the largest road building programme since the 1970's, trebling the annual investment in major road schemes by 2020-21. Plans include adding extra lanes to the busiest motorways, identifying solutions to tackle some of the most notorious and longstanding traffic hotspots in the country, upgrading the national non-motorway network managed by Highways England to dual-lane and ￡10 billion to repair the national and local road network.

However, there is what economists call an opportunity cost involved. Every ￡1 invested in a specific transport project is ￡1 that isn't spent improving transport elsewhere in the network. It is therefore critical that we maximise the impact of our road infrastructure investments and ensure that we are targeting the worst affected areas. Furthermore, to aid accountability and to inform future decision making it's critical that we evaluate the performance of these improvement programmes.

This is where big data can help. Want to know where your traffic hotspots are? Want to quantify the benefit to be gained through new road investments? Or do you need to perform a before and after evaluation of a new road project? These are the types of questions that can be asked and answered quickly, cheaply and efficiently thanks to the advent of big data analytics. 

For example, INRIX processes over 500 Terabytes of data from over 300 million connected cars and devices every month to provide real time traffic insights to drivers. Now this data can be leveraged by governments, public agencies and transport professionals through a cloud-based, on-demand tool called INRIX Roadway Analytics.

INRIX Research used INRIX Roadway Analytics to produce "Europe's Traffic Hotspots" , a study that analysed every traffic jam in September 2016 in 19 European countries. Over 200,000 instances at more than 45,000 traffic hotspots in 123 European cities. Using this rich dataset, we were able to rank Europe's worst traffic hotspots by their total impact on car drivers and passengers.

It's great to see that the government's latest announcement will tackle a number of the UK's top traffic hotspots identified by our study, including the A63 in North Yorkshire, M5 around Bristol, M25 near London Heathrow airport and the M27 to the south coast. However, a number of the UK's worst traffic hotspots are omitted from the list including the A48 in Cardiff, A720 outside Edinburgh and M62 in Liverpool - which collectively had 1920 jams last year according to our analysis.

Big data can help planners and funders to ensure that road infrastructure spending is optimised so that society gains the most. Data collection and analysis that would have taken months historically can now be performed in seconds so there is no longer an excuse.