Serious injuries in the traffic accident situation: definition, importance and orientation for countermeasures based on a representative sample of in-depth-accident-cases in Germany

ABSTRACT

For many years, there are three groups of injury severity used for describing traffic accident patterns, i.e. minor, severe and fatal. In 2015, the European Commission has committed to set a common EU target for the reduction of the number of seriously injured traffic participants by 2020. This leads to the need of new criteria of seriously injured casualties, for which MAIS 3+ is proposed.

A study on a representative accident data collection GIDAS (German In-Depth Accident Study) was used to calculate the percentages of seriously injured casualties for different kinds of traffic participants based on a statistical random procedure and weighting process in relation to the German national statistics. All injuries (kind, location, AIS) and other accident parameter (deformation, speed, accident types) of the in-depth-accident-sample are documented by a scientific team. Accidents from the years 2009 to 2013 were evaluated for this study. 8,217 accidents with 15,955 participants and 20,083 injured persons of all kind of traffic participants were analysed, 2,000 were severely injured, of these 416 seriously MAIS 3+.

The assumption of seriously injured persons except fatalities in traffic accidents for Germany based on GIDAS calculation can be stated as 21% of severe injured persons and as 4% of all injured traffic participants in Germany.

The study describes one way to get information (numbers/percentages) of seriously injured casualties based on MAIS 3+ and based on real-world in-depth accident cases. The study gives proposals for countermeasures on further safety issues for avoiding severe injuries, distinguished for different kinds of traffic participants and shows injury characteristics for the help for protective tasks.

KEYWORDS:

• Injury severity
• MAIS 3+
• serious injuries
• traffic accident
• traffic participants

Acknowledgments

GIDAS collects records and processes data from accidents of all kinds and, due to the on-scene investigation and the full reconstruction of each accident, gives a comprehensive view on the individual accident sequences and their causation. The project is funded by the Federal Highway Research Institute (BASt) and the German Research Association for Automotive Technology (FAT), a department of the VDA (German Association of the Automotive Industry). Use of the data is restricted to the participants of the project. Further information can be found on GIDAS at http://www.gidas.org.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by GIDAS (German In-Depth Accident Study) data. The project is funded by the Federal Highway Research Institute (BASt) and the German Research Association for Automotive Technology (FAT), a department of the VDA (German Association of the Automotive Industry).