UK motorway traffic jam

Data standards and digital skills will unlock innovation in transportation

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The more information we have about our national transport infrastructure, the better we can build for the future.

Intelligent transport systems, autonomous vehicles, the mass rollout of 5G and the growth of the Internet of Things IoT are collectively set to have a profound effect on the way we navigate our world in the coming years. Increasingly, geospatial data and the expertise to harness this information will be essential to enable new and compelling use-cases.

According to a study commissioned by the Society of Motor Manufacturers and Traders Ltd (SMMT), connected and autonomous vehicles are set to add £51bn a year to the UK economy by 2030, so there’s plenty to be excited about when it comes to innovation.

Connected autonomous vehicles (CAVs) need to know where they are at all times, as do the organisations in charge of them. For this reason, and many others, consistent, reliable geospatial data must be the baseline for any use-case related to smart transport and autonomous vehicles.

For a small island such as Great Britain, Ordnance Survey datasets provide the baseline for us to be acutely aware of the space we have, and how best to plan the infrastructure that will enable smart transport use-cases. Whether this is through the availability of dynamic, real-time information provided by sensors on a car, or updates to topographical features delivered via APIs, the availability of trusted data is essential – as are those with the skills to work with and validate this data.

The amount of contextual information about roads and the vehicles on them will increase as the presence of IoT devices and 5G networks increases. These two advances in technology will enable sophisticated telematics that will reveal previously unseen insights into road infrastructure and driving behaviour, all of which will provide valuable data that can be harnessed to improve transport systems.

Telematics can identify blackspots, for example, by providing data on road conditions and driver habits in certain locations. Harsh braking in fair weather on a certain section of road may cause occasional accidents, but if instances occur with a higher frequency in periods of poor weather, this can be addressed through road modifications, lower speed limits or roadside enforcement. The more data we have, the better we can build for the future. Again, the geospatial element of the data is paramount, which is why software developers and data scientists will be crucial for understanding, organising, and creating useful applications with this data.

To enable use-cases for connected autonomous vehicles and smart transport systems at a local, regional, and national level, there are a number of challenges that must be overcome.

Regulatory frameworks will need to be in place, which requires legislative bodies to work together with government, original equipment manufacturers (OEMs) and major vehicle manufacturers to create the ‘rules of the road’ for autonomous vehicles. Transport authorities across the country will need to oversee the operation of autonomous vehicles on their roads. An independent view of the operational design domain, at a regional level, will be essential to ensure the safe operation of vehicles as conditions change. This will then need to be scaled up to a countrywide view for the national regulator. There is also the further problem of autonomous vehicles crossing borders, which may then be subject to different regulations, meaning international interoperability must also be factored in.

Ideally, technology will move in lock-step with legislation, but this is rarely ever the case in sectors undergoing rapid technological change. To close the gap between legislation and innovation, technologists in the sector will need to work closely with government and industry bodies to ensure systems and applications are architected with agility in mind to meet new regulatory standards.

There are currently many organisations innovating in the areas of intelligent transport systems and autonomous vehicles. As these organisations build their own solutions, using various datasets, tools and technologies, they do so in isolation. This means interoperability across networks would simply not be possible if the infrastructure currently existed to enable the mass rollout of autonomous vehicles.

This is why a robust, standardised national data infrastructure must be in place. It doesn’t matter whether a CAV is an HGV, a family car, or a driverless taxi, as each of these vehicles must be able to fully understand the context of the vehicles around them and their environment. This is why standards are crucial. The data informing the onboard pilot of one vehicle should not deviate in any way when delivered to another in the same context.

Ordnance Survey data, made available through the Public Sector Geospatial Agreement (PSGA) and sponsored by the Geospatial Commission, is used extensively across the public sector, from Highways England to city transport authorities across the country and emergency services. The government has also mandated the use of unique identifiers, UPRNs and USRNs, which, if widely adopted, enhances a location standard for the entire country. Whether it’s through OS data or not, reliable data that conforms to mandated standards will be essential in enabling the future of transport.  

An area beyond legislation and data standards that must not be forgotten is accessibility. Heavier investment in rural locations, for example, will be needed to create the infrastructure to support autonomous and electronic vehicles. Geospatial data will play a crucial role in creating this infrastructure; for example, the intelligent placement of electric vehicle charging points and 5G masts will be essential for enabling CAVs and EVs to operate effectively across the entire country.

Providing access to smart transport is also a social responsibility. By combining geospatial data with demographic datasets, the government, and commercial organisations, will be able to determine where to concentrate funding to ensure consistent support and connectivity. These decisions will not always align to areas of the country where infrastructure is typically sparse. Many urban areas  contain groups that do not have access to the technology that will enable them to benefit from intelligent transport systems, and so will require further investment to democratise access to new and improved services.

Once again, those with the data science and digital skills to unlock the potential of data will be crucial to meeting these challenges.

By David Russell is principal geospatial consultant at Ordnance Survey.

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