What are the Potential Consequences of “Defective” Road Markings?
It is widely accepted that the proper maintenance of line and road markings is vital to the safety of road users, but as we move into a more automated future, it could also have implications for the rollout of new technologies.
New research has revealed that roughly a third of road markings on the major road network (MRN) in England can be graded as “defective” or completely absent, which has significant implications for the introduction of automated vehicles in the UK and has raised questions over whether standards should be improved.
Commissioned by the Road Safety Markings Association (RSMA), one of the largest specialist trade bodies in the Highways sector, this research was shared in part at the organisation’s annual conference in February, with the full report to be released in Spring next year.
By teaming up with Reflective Measurement Systems Ltd, whose advanced mobile retro-reflectometers are designed to accurately measure across the full lane width in a single pass, the RSMA was able to assess 2,100km of the MRN in this independent survey.
What is the MRN?
The Major Road Network refers to a network of important roads (such as A-roads) that fall under the jurisdiction of local authorities. While only comprising 4% of the country’s road length, the MRN accounts for 43% of traffic flows.
The Strategic Road Network (SRN), on the other hand, is managed by National Highways and encompasses 4,500 miles of motorways and major A roads. As one of the most important pieces of infrastructure in the country, all road markings on the SRN are held to standards set out in the CS 126 “Inspection and Assessment of Road Markings and Road Studs”, with regular inspections revealing where road markings need to be reapplied to meet compliance.
However, this is not the case on the MRN, where a lack of equivalent regulations, differences in approaches by local councils and the impact of budgetary constraints has led to more patchwork results.
What the survey found
The survey measured both the retro-reflectivity and contrast of road markings, with the RSMA explaining that while retro-reflectivity is an important measurement in testing whether intervention is needed to improve road markings and therefore reduce accidents, contrast is vital to “machine reading” on the roads.
Under the aforementioned CS 126, anything below 80 millicandelas (mcd) retro-reflectivity is considered defective. The survey found that 36.15% of edge-line markings and 26.40% of centre-line markings failed to meet this standard, while a whopping 79.275% of road markings were revealed to be under the 3:1 minimum level of contrast required for machine reading.
What does this mean for automated cars?
We have explored in previous articles how missing, confusing, degraded or poorly applied road markings can represent a safety hazard for road users, but one of the more surprising outcomes of ineffective line markings is the impact it is projected to have on the rise of “driverless” cars.
Self-driving vehicles are a major area of research and development in the modern transport industry, with the potential to match the private car in convenience while offering far more efficiency as a means of public transport. While likely to be very expensive for a long time, there is also scope for private driverless cars to become a regular feature on the road, taking the labour and (it is theorised) much of the risk out of driving.
While still some way off, driverless cars promise a revolution in transport, and progress is being continually made which could make visions of a greener, safer and more equitable future through the use of automated vehicles a reality. However, automated vehicles, like human drivers, need rules to read the road, and a language with which to parse this information.
This is what makes supporting infrastructure so important to driverless vehicles, and road markings are a key part of this. While a human could look at a road with incomplete markings and make a judgment call – even if this scenario is far from ideal and will increase the likelihood of accidents – at this time even highly sophisticated automated cars are unlikely to have the same capacity to do so.
One of the major challenges with the development of automated vehicles is that they will need to operate in a very human environment – where human error is a constant factor they will have to account for in their calculations. It will therefore be vital that the complex set of data points a driverless car uses to make decisions are as comprehensive as possible, so it can navigate its environment safely.
What this research reveals is that, were automated cars to be put on the road tomorrow, standards are such that they would be confined to the SRN, while their ability to read the road in other areas would be hampered by inadequate road markings. While not an urgent concern, it is certainly one we are likely to need to consider in future, suggesting that major investment in road infrastructure will be required to capture the full potential of this technology.
