Research & reports

Title: Models and Methods for Collision Analysis: A guide for policymakers and practitioners

Organisation: RAC Foundation
Date uploaded: 10th April 2019
Date published/launched: March 2019

This report has been produced to help establish whether there is a case for investing more resource into the investigation of road crashes, in order to facilitate feedback and learning.

The report has been authored by professor Neville Stanton from the University of Southampton, and is the first in a series of technical notes and reports commissioned as part of the Road Collision Investigation Project, a £480k trial of new approaches to road collision investigation which was announced in June 2018 by the UK Government and is being led by the RAC Foundation.

The Road Collision Investigation Project is setting out to establish whether there is a business case for investing more resource into the investigation of road crashes, in a manner akin to that already in place for the rail, air and maritime sectors.

As part of the three-year project several police forces in England are recruiting additional staff to collect and collate collision data, which will be analysed to identify and understand common themes and patterns that result in death and serious injury.

Professor Stanton’s report describes how accident causation models have changed over time and details the rationale for taking a systems approach to collision investigation.

The report also presents a summary of key systemic human factors accident investigation models and human factors accident analysis methods, illustrated by a case study from the US where an Uber vehicle was involved in a collision with a pedestrian in March 2018.

Professor Stanton goes on to review eight different methods, and from this analysis recommends the ‘Actor Map’ and ‘AcciMap’ approaches.

He concludes that the next steps for the Road Collision Investigation Project should include: developing a classification scheme for Actor Maps and AcciMaps, and a matrix for the linking of events in AcciMaps; development of training materials for Actor Maps and AcciMaps, and conducting a pilot study of training in both methods.

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