Technical details
Client
Department for Transport (DfT)
Dates

2023-2024

Missions
Data Science, Statistical Analysis, Geospatial Analysis, Machine Learning applications, Data Visualisations
Location
United Kingdom
Perimeter
Consultancy
Activity
Roads and Highways

A combination of statistical analysis, geospatial analysis and innovative machine learning* techniques were applied to highlight the circumstances and contributory factors that lead to death and serious injury on roads in Great Britain and determine the key components affecting the outcome of reported collisions.

Fine-tuning data

More specifically, the machine learning* techniques were applied to correlate collision data with detailed mapping information (OpenStreetMap and OS MasterMap), allowing exploration of relationships between collisions and the physical environment.

The key findings were that most collisions occur in densely populated areas, however fatal and serious collisions are more commonly observed on rural roads. The most vulnerable road users in these rural areas are motorcyclists or pedal cyclists.

A clear view of results

An interactive StoryMap was delivered to visualise the project outcomes, highlighting problematic areas and demonstrating the value of maps to assist in decision making.

*Machine learning is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalise to unseen data and thus perform tasks without explicit instructions.