Data standards and digital skills will unlock innovation in transportation
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.