Geospatial Commission Transport Report

How to unlock transport’s geospatial revolution

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Karl Tomusk

Location data has “huge potential” to power a greener, faster, better transport sector in the UK – but much of the data we need is still missing. A new Geospatial Commission report has identified six transport opportunity areas and the data that could unlock significant advances.

The report, Positioning the UK in the fast lane, comes ahead of the Department for Transport’s data strategy, which seeks to address some of the problems with the use and accessibility of transport data in the UK.

Roads

The opportunity:

  • Better use and exchange of planning, design, construction and maintenance data. Data often lacks interoperability, which means different stakeholders do not share data between them and local authorities maintain multiple versions of the same road network, inconsistently updating local road data
  • More effective management of street works and communication of those works to road users
  • Optimising traffic management systems with a central view of the road network that could enable proactive decision-making and real time insights

What data we already have:

  • National road networks mapped and accessible from the Ordnance Survey and other open sources
  • Traffic flows and density collected by Highways England

What data we still need:

  • Planning and construction data that is compatible with other Geographic Information System (GIS) data
  • Movement of people and goods, including the origin and destination of journeys, which would make planning road infrastructure less challenging

Road and rail haulage

The opportunity:

  • Encouraging greater adoption of vehicle telematics systems to manage delivery fleets and save journey times and fuel emissions
  • Developing common standards for telematics routing systems because data collected from vehicle telematics systems is often not standardised
  • Modelling freight networks: there is good data available on freight moving in and out of the UK but not as much within the UK

What data we already have:

  • Railway mapping and timetables
  • Distribution centre locations
  • National delivery route data

What data we still need:

  • Accurate aggregated delivery numbers: the growth of e-commerce and the presence of multiple operators means logistics requirements are underestimated
  • Last-mile delivery, given the sector’s reliance on gig economy drivers in their own or rented vans

Route optimisation

The opportunity:

  • Investing in more bespoke operational route planning systems. Most route planning systems now focus on the shortest, quickest or cheapest route options, but there is scope for more customisation (crime rates, street lighting, etc.)
  • Supporting the development of strategic route planning tools

What data we already have:

  • National road networks
  • Average traffic flows

What data we still need:

  • Origin/destination data about regular trips. This data is often highly aggregated, out of date or prohibitively expensive
  • Traffic speeds. Ordnance Survey intends to make road speed data available from April 2023
  • Dynamic road conditions, including real time data on jams and collisions

Electric vehicles

The opportunity:

  • Planning new charging infrastructure
  • Enabling bespoke EV routing applications that meet users’ needs with data such as charging point availability
  • Managing grid capacity to ensure local distribution networks are not overwhelmed by an influx of EVs

What data we already have:

  • Existing EV charging infrastructure through services such as Zap-Map

What data we still need:

  • Latent demand: good, granular data on where people are buying and using EVs
  • Parking, including home parking access data, which would inform planning where on-street charging points should go
  • Underlying grid connection data, including the location of existing electricity networks, low voltage networks and substations

Connected and autonomous vehicles

The opportunity:

  • Enabling the generation and exchange of HD mapping data. Driverless vehicles will require vehicle-mounted sensors and/or high definition maps to navigate their surroundings
  • Investing in incremental testing and trials

What data we already have:

  • Data to support driverless vehicle navigation, provided by Global Navigation Satellite Systems and sensors on the vehicle
  • Average traffic flows and density data, which can be used to train vehicles to understand normal traffic conditions

What data we still need:

  • Dynamic road conditions, including temporary hazards that can change quickly
  • High resolution, standardised information on lanes and other road information
  • Position of vehicles relative to each other

Drones and unmanned aircraft systems

The opportunity:

  • Improving navigation and positioning systems with 3D spatial data, including building height, topography and land use
  • Managing flight paths and airspace. Airspace will need to manage between competing uses to minimise collision risks and manage ethical, privacy, noise and security concerns
  • Creating digital testing and simulation environments. Digital twin technology could be used to simulate flights before real world trials

What data we already have:

  • Mapped and tracked airspaces
  • Drone locations

What data we still need:

  • Risk assessments and other arrangements for conducting drone trials
  • Real time, or near-real time, risk assessment data and precise 3D maps of an area in beyond visual line of sight (BVLOS) operations

Rachel Maclean, transport minister at the Department for Transport, said: “This report from the Geospatial Commission is a perfect example of the significant benefits of data in delivering tangible transport benefits, from planning where to place new electric vehicle charging points, to making last-mile journeys quicker, easier and more efficient.

“This is the perfect complement to our upcoming transport data strategy, which will help overcome the barriers to data sharing and use, as well as improving the discoverability, accessibility and quality of data.”

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