Metadata
Title
Intelligence-led safe road systems
Category
general
UUID
d376f3d47dc04d2b935c027cc0fefacf
Source URL
https://www.lboro.ac.uk/research/spotlights/safe-roads/
Parent URL
https://www.lboro.ac.uk/research/spotlights/
Crawl Time
2026-03-24T00:03:10+00:00
Rendered Raw Markdown

Intelligence-led safe road systems

Source: https://www.lboro.ac.uk/research/spotlights/safe-roads/ Parent: https://www.lboro.ac.uk/research/spotlights/

Advanced algorithms transform our strategic road networks – saving lives

Road traffic collisions and congestion cost the UK more than £72 billion a year. Latest Department for Transport figures showed that 1,580 people died on our roads (year to June 2020), and drivers can spend an average of 31 hours a year in rush hour queues.

Highways England (HE) was tasked by the Government, in 2015, with reducing the number of deaths and serious casualties on the UK’s 4,300-mile strategic road network (SRN) by 40% before the end of 2020. To achieve this target, HE needed accurate, high-quality data and modelling.

We have developed artificial intelligence (AI) based collision mapping and risk modelling that provide an unprecedented accuracy of 99% in pinpointing accident hotspots.

Since 2014, in partnership with AECOM, we have been helping HE to deploy these algorithms and develop a holistic understanding of road safety – looking at how vehicles, people and the design of road infrastructure interact.

This has supported targeted investment in safety measures and the successful implementation of a new range of interventions spanning road engineering, behavioural change campaigns, and technology improvements to vehicle maintenance.

Our impact

Accurate accident data improves road safety

Casualty reduction

Driving Highways England’s safety strategies

Map-matching algorithms

The research

Indeterminate locational accuracy makes effective analyse of geo-spatial data extremely challenging.

In 2006, we began to address this issue. Our innovative and transferable statistical and artificial intelligence-based map-matching algorithms make analysis of these data far more reliable – achieving over 99% accuracy so that effective road safety measures can be devised and implemented.

In 2018, we used the algorithms to analyse data, supplied by the Department for Transport, comprising more than 70,000 traffic collisions from the preceding six years. This analysis allowed us to create more than 500 spatio-temporal safety risk maps, identifying fatal hotspots and high-risk routes.

These maps have enabled Highways England – in partnership with AECOM – to identify the factors underlying the frequency and severity of traffic collisions, and to develop and evaluate effective collision prevention schemes.

Our work with Highways England to improve UK road safety is ongoing.

Improved data accuracy developed by Loughborough has enabled us to strengthen our evidence-based strategies to deliver targeted road safety interventions with greater confidence.

Anne-Marie Penny Senior Road Safety Policy Advisor – Highways England

### UK road accidents cause an annual loss of ≈£15B

### Every £1 invested in SRN delivers >£2 in economic benefits

Research funders

Development partners

Meet the experts

Professor Mohammed Quddus

Professor of Intelligent Transport Systems - Imperial College, London

Dr Marianna Imprialou

Lecturer (2012-16)