2 research outputs found
The development of a multidisciplinary system to understand causal factors in road crashes
The persistent lack of crash causation data to help inform and monitor road and vehicle
safety policy is a major obstacle. Data are needed to assess the performance of road
and vehicle safety stakeholders and is needed to support the development of further
actions. A recent analysis conducted by the European Transport Safety Council
identified that there was no single system in place that could meet all of the needs and
that there were major gaps including in-depth crash causation information. This paper
describes the process of developing a data collection and analysis system designed to fill
these gaps. A project team with members from 7 countries was set up to devise
appropriate variable lists to collect crash causation information under the following topic
levels: accident, road environment, vehicle, and road user, using two quite different sets
of resources: retrospective detailed police reports (n=1300) and prospective,
independent, on-scene accident research investigations (n=1000). Data categorisation
and human factors analysis methods based on Cognitive Reliability and Error Analysis
Method (Hollnagel, 1998) were developed to enable the causal factors to be recorded,
linked and understood. A harmonised, prospective āon-sceneā method for recording the
root causes and critical events of road crashes was developed. Where appropriate, this
includes interviewing road users in collaboration with more routine accident investigation
techniques. The typical level of detail recorded is a minimum of 150 variables for each
accident. The project will enable multidisciplinary information on the circumstances of
crashes to be interpreted to provide information on the causal factors. This has major
applications in the areas of active safety systems, infrastructure and road safety, as well
as for tailoring behavioural interventions. There is no direct model available
internationally that uses such a systems based approach
The development of a multidisciplinary system to understand causal factors in road crashes
The persistent lack of crash causation data to help inform and monitor road and vehicle
safety policy is a major obstacle. Data are needed to assess the performance of road
and vehicle safety stakeholders and is needed to support the development of further
actions. A recent analysis conducted by the European Transport Safety Council
identified that there was no single system in place that could meet all of the needs and
that there were major gaps including in-depth crash causation information. This paper
describes the process of developing a data collection and analysis system designed to fill
these gaps. A project team with members from 7 countries was set up to devise
appropriate variable lists to collect crash causation information under the following topic
levels: accident, road environment, vehicle, and road user, using two quite different sets
of resources: retrospective detailed police reports (n=1300) and prospective,
independent, on-scene accident research investigations (n=1000). Data categorisation
and human factors analysis methods based on Cognitive Reliability and Error Analysis
Method (Hollnagel, 1998) were developed to enable the causal factors to be recorded,
linked and understood. A harmonised, prospective āon-sceneā method for recording the
root causes and critical events of road crashes was developed. Where appropriate, this
includes interviewing road users in collaboration with more routine accident investigation
techniques. The typical level of detail recorded is a minimum of 150 variables for each
accident. The project will enable multidisciplinary information on the circumstances of
crashes to be interpreted to provide information on the causal factors. This has major
applications in the areas of active safety systems, infrastructure and road safety, as well
as for tailoring behavioural interventions. There is no direct model available
internationally that uses such a systems based approach