Accident data analysis: The German In-Depth Accident Study (GIDAS) database analysis
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1 Accident data analysis: The German In-Depth Accident Study (GIDAS) database analysis Presented by: Iztok I Ciglarič Company Name: VSI-TUG
2 General information on GIDAS database Geographical area of the accident data sampling is the area of Hanover and Dresden. Accident investigation takes place daily during two six-hour shifts following a 2-week cycle. Data is collected by Investigation Teams. Special vehicles equipped with instruments for measuring and data recording are available.
3 Scope of GIDAS database Available information collected "on the scene" complemented by the information on the vehicles and by injury information (AIS coded) for each individual. Available technical information on accident reconstruction generated from colected evidence. Up to 3,000 pieces of information per accident is coded as specified in manual.
4 GIDAS database analysis-sample Considered number of cases: N=1175. Relevant sample distribution: First registration No. of cases N1=339 N2=296 N3=310 N4=155 N5=36 N6=15 N7=24 Level of considered injuries: AIS +2 (consortium request AIS +3). Considered body regions: All as coded by AIS.
5 GIDAS database analysis-general TARGETS Baseline passenger injury analysis. Injury analysis related to age. Injury analysis related to impact type and impact severity.
6 RESULTS-GENERAL TARGETS Thorax, Spine and lower extremity are critical for AIS+3 injuries. Head and upper extremity are citical for AIS 2 injuries. No risk group related to age was identified.
7 RESULTS-GENERAL TARGETS Injury (AIS +3) frequency distribution expressed in a total number of cases according to delta velocity of first impact, body region and injury severity.
8 GIDAS database analysis-specific TARGETS Injury analysis related to anthropometric parameters. Injury analysis related to passenger position and posture. Analysis of the cause of injury for specific body part related to vehicle safety equipement function and/or contact with specific vehicle interior parts.
9 RESULTS-SPECIFIC TARGETS Considering BMI frequency distribution it is possible to conclude that female passenger with BMI greater than 24 (overweight and obese) represent risk group regarding to frequency and severity of injuries. Small female population (with body height up to 165cm) represent risk group regarding to frequency of injury occurrence. BMI (Body Mass Index) frequency distribution for female population
10 RESULTS-SPECIFIC TARGETS Injury (AIS +2) frequency distribution expressed in a total number of cases according to seating position in the vehicle (see figure on left) No information on injuriy outcom related to passenger posture available.
11 RESULTS-SPECIFIC TARGETS Injury (AIS +3) frequency distribution expressed in a total number of cases according to body region and injury severity for frontal airbag function (deploy, not applicable, did not deploy).
12 RESULTS-SPECIFIC TARGETS Injury (AIS +3) frequency distribution expressed in a total number of cases related to body region, injury severity and contact with specific vehicle parts.
13 GIDAS database analysis-conclusion GIDAS database could provide important information on injury genesis for each individual involved in accident. Some information such as human body contact specification with vehicle interior and components are already addresed. But more and detailed information are needed to address problems related to smart restrain systems. Methodology based on CCIS was confirmed.
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