Medizinische Hochschule Hannover Hannover Medical School The Accident Research Unit -1-
Content of lecture Vulnerable road users are the main topic Research on In-Depth-Investigation i.e. GIDAS New Aspects on Bicycle Helmets Whiplash problematic Practices on forensic expertises in Germany 2-2-
Accident Research and Forensics Tasks common workprocess Accident analysis Accident causation Aviodance stategies Injuries and injury pattern Speed of driving Impact Speed Avoidance speed Documentation of traces Questionairing witnesses and participants Analysis of injury causation and mechanisms Determination of impact and driving speed Avoidance and failures Effectiveness of safety eqippments Impact and moving behavior of persons -3-
Real World Analysis Experimental Simulation Nat. + int. statistics Accident Research Unit Crashtests Component tests Vehicle development Field analyses Computersimulation -4-
In-Depth Research Teams Germany Hannover since1973 Dresden since1999 Investigation Area 60 km radius -5-
Technical University Dresden methodology Medical University Hannover 2000 accidents annual 1000 accident 1000 accident By order of Federal Highway Research Institute BAST Automotive Research Association FAT -6-
Kind + Location + Severity AIS 2005 Injury documentation Abbreviated Injury Scale Commotio Cerebri AIS 2 MAIS 2 AIS-Head 2 Laceration Head right frontal AIS 1 Fracture of head of radius right AIS 2 Rupture left crucial ligament AIS 2 AIS-Arms 2 AIS-Legs 2-7-
3020100207-8-
3-D-picture scene of accident (30060206) 3-D-Scan -9-
True to scale drawing as basis for reconstruction -10-
On scene investigation Hannover [n] 2.000 1.000 0 Year of investigation Number of cases 1973 to 2013 Accidents 29.359 Vehicles 56.143 Persons 73.486 Casualties 39.532 Injuries 131.501 11/18/2013 11-11-
Pedestrian Safety -12-
Development of safety car frontal against pedestrian in the 70s Collision Opel Ascona frontal against pedestrian, Collision speed 45 kph, Deformation front edge of hood, Impact on windshield MAIS 3 Pedestrian female, 48 years, MAIS 3 Contusions and abrasions (AIS 1) Comotio cerebri (AIS 2) Dislocated lower leg fracture left (AIS 3) Symphyseal disruption (AIS 2) -13-
87.2% pedestrian - collision with car - 70-ies frequencies of injured body regions 6.8% injured by body impact with 57.3% 32.1% 21.3% 26.2% vehicle part is cause of injury 82.5% 53.1% 53.3% road surface 59.9% total n = 392-14-
Development of safety car frontal against pedestrian in the 90s 1991-217 Collision VW Jetta frontal against pedestrian, Collision speed 45 kph, Impact on right front bumper and hood MAIS 2 Pedestrian female, 21years, MAIS 2 Abrasion forehead right side (AIS 1) Abrasion right hand (AIS 1) Abrasion right knee (AIS 1) Fracture of left fibula (AIS 2) -15-
62.1% pedestrian - collision with car - 90-ies frequencies of injured body regions 4.9% injured by body impact with 42.5% 23.2% 8.8% 16.3% vehicle part is cause of injury 69.5% 31.8% 33.0% road surface 58.7% total n = 1074-16-
Development of safety car frontal against pedestrian up to date Collision BMW-one frontal against pedestrian, Collision speed 45 kph, Deformation front edge of hood, Impact on windshield MAIS 1 Pedestrian male, 56 years, MAIS 1 Contusions and abrasions (AIS 1) 30120539-17-
45.4% pedestrian - collision with car - actual frequencies of injured body regions 37.6% 6.7% 22.0% 6.3% 17.7% injured by body impact with vehicle part is cause of injury 67.7% 26.5% 27.1% road surface 52.7% total n = 780-18-
Injury probability pedestrians (adults > 150 cm) Collisions of car-front 100% 90% 80% MAIS 5/6 Most heavily injured killed % cumulative 70% 60% 50% 40% 30% 20% 10% MAIS 1 Slightly injured MAIS 2-4 Seriously injured 0% bis 30 31-50 51-70 > 70 Collision speed car total n = 935-19-
Impact of pedestrians < 40 km/h Frontal impact all types of cars Head-impact Maximum x-distance -20-
Impact of pedestrians > 40 km/h Frontal impact all types of cars Head-impact Maximum x-distance -21-
accident reality Testvorschlag für die Windschutzscheibe -22-
History of Traffic Safety BICYCLISTS -23-
bicycle collision with car - 70-ies frequencies of injured body regions 84.3% 5.2% injured by body impact with 64.4% 34.9% 15.2% 15.2% vehicle part is cause of injury 77.8% 38.2% total n = 217 road surface 60.4% -24-
bicycle collision with car - 90-ies frequencies of injured body regions 51.2% 6.9% injured by body impact with 44.5% 24.5% 5.8% 11.8% vehicle part is cause of injury 68.3% 16.0% total n = 1614 road surface 70.8% -25-
especially effective for persons > 40 yeard bicycle helmet increases safety elderly persons helmet with without good protections against head injuries by bicycle helmets age classification -26-
European Standard for bicycle helmet production Sichtfeld Horizontal min. 105 Grad Nach oben min. 25 Grad Nach unten mind. 45 Grad Stoßdämpfung Stirn, Hinterkopf,Seiten, Schläfen, Oberkopf schützen Max.Beschleunigung < 250g 5,42 m/s flacher Sockel (1,5m) 4,57 m/s Bordsteinkante (1,0m) Trageeinrichtung Dyn. Dehnung max. 25 mm -27-
Shock Absorber Test of Helmet determination of test area 1 reference level 2 reference line for angular measurement test area above by Worst case Method -28-
Bilder der Radhelme 30040547 30050479 30050711 30050800 30060275 30060712 experiences from real world accidents -29-
Definition of Impact and Damage Matrix on Helmet protective are by CEN 1078-30-
Location of Damages / Impact Areas on Helmet Scratches, Traces Deformations Bursts -31-
Proposal for Extension of Protective Area -32-
Radhelm und Verletzungsschwere Radfahrer % 80 70 60 50 40 30 20 10 0 3,3 4,3 not injured with helmet (n=433) 72,074,4 21,2 17,5 without helmet (n=3812) 2,8 2,8 0,7 0,7 0,0 0,3 0,0 0,0 MAIS 1 MAIS 2 MAIS 3 MAIS 4 MAIS 5 MAIS 6 maximum injury severity grade -33-
% 80 70 60 50 40 30 20 10 0 Injury Severity Grade of Head 70,2 61,9 not injured with helmet (n=433) 18,1 27,7 11,18,8 without helmet (n=3812) AIS > 2 1.6 % without helmet 0.6 % with helmet 0,2 0,9 0,4 0,5 0,0 0,2 0,0 0,0 AIS 1 AIS 2 AIS 3 AIS 4 AIS 5 AIS 6 injury severity grade of head -34-
% 40 35 30 25 20 15 10 5 0 reduction 75% 0,2 Frequencies of Head Injuries 0,8 skull fracture with helmet (n=433) 11,0 8,8 reduction 83% 0,2 1,2 0,2 0,5 brain brain injury AISinjury AIS 2 3+ without helmet (n=3812) reduction 60% base fracture head injury 2,6 2,7 facial frakture reduction 33% 22,9 34,3 soft tissue injury -35-
Example: Bicyclist without Helmet headimpact windscreen impact zone left side -36-
Example: Bicyclist without Helmet bicyclist: female, 69 Jahre MAIS 3 compression fracture skull deeply wound fronthead fracture right patella compl. fracture right lower leg multiple soft tissue injuries legs -37-
Example: Bicyclist with Helmet impact zone front wheel head impact A-pillar -38-
Example: Bicyclist with Helmet bicyclist: male, 8 Jahre MAIS 1 laceration left knee no injuries head -39-
Example: Bicyclist with Helmet used helmet deformation outer shell by impact with A-pillar -40-
Statistical Probability to Suffer Head Injuries - ODDS-RATIO Odd Ratio, to rate the difference of two Odds resulting in classifying the intensity values >1 increasing probability values <1 decreasing probability Task variable AIS-Head Brain Injury AIS >3 Facial Fracture -41-
Logistical Regression AIS-Head Odds Ratio impact speed collision partner 1.035 <0,0001 age of bicyclist 1.011 <0,0001 BMI 1.000 0.9856 accident location rural 2.131 <0,0001 daytime type of bicycle dust night BMX bicycle n.f.s. mountainbike racing bicycle 1.132 1.298 1.649 1.004 1.115 1.049 p 0.9580 0.0950 0.2106 0.1711 0.8066 0.5529 cycle path none, not used 1.463 <0,0001 collision partner object 1.469 <0,0001 bicycle pedestrian truck multiple mot. two-wheeler 0.902 0.750 1.577 1.133 0.908 0.0589 0.0339 0.0069 0.9952 0.3799 gender female 1.066 0.9587 helmet without 1.503 0.0005-42-
Logistical Regression Brain Injuries AIS 3+ (n=62 vs. 1153) Odds Ratio impact speed collision partner 1.070 <0.0001 age of bicyclist 1.025 0.0023 BMI 1.046 0.1403 accident location rural 0.779 0.6179 daytime type of bicycle dust night BMX bicycle n.f.s. mountainbike racing bicycle 1.345 2.178 0.001 0.925 1.796 1.271 p 0.0978 0.1219 0.9220 0.9366 0.9000 0.9191 cycle path none, not used 1.463 0.1831 collision partner object 2.652 0.6889 bicycle pedestrian truck multiple mot. two-wheeler 1.797 0.001 1.061 2.981 0.001 0.7306 0.8734 0.7877 0.6777 0.8061 gender female 0.750 0.9809 helmet without 8.560 0.0471 < number of cases! -43-
Logistical Regression Facial Frakture (n=124 vs. 4091) Odds Ratio impact speed collision partner 1.026 <0.0001 age of bicyclist 1.005 0.3302 BMI 1.031 0.1922 accident location rural 2.060 0.0276 daytime type of bicycle dust night BMX bicycle n.f.s. mountainbike racing bicycle 0.835 1.672 2.891 0.992 0.866 1.116 p 0.2836 0.0541 0.1678 0.3574 0.1463 0.7939 cycle path none, not used 1.378 0.0935 collision partner object 4.582 <0.0001 bicycle pedestrian truck multiple mot. two-wheeler 2.473 0.520 2.138 1.905 0.656 0.1315 0.2360 0.2953 0.7044 0.3647 gender female 1.247 0.9681 helmet without 1.107 0.7649 not significant influence in question -44-
Conclusion! Protective Effect of Helmet is Clearly! 40% of bicyclists without helmet (30 % with helmet) suffer head injuries 70%.at impact speed v >40 kph 5.4% of bicyclists with head injuries are AIS>2 (0.9% with helmet) byciclists with helmet are more young people, seniors are rare byciclists with helmet more often use street 57% vs. 42% without helmet racing biker more often use helmet and are driving on the street usage is low rural, by night, age of bicyclist >50 years -45-
Effectiveness of Bicycle Helmet Verifiable by Accident Studies protection from soft tissue injuries soft tissue injuries 35 % especially from severe injuries skull fractures 71 % brain injuries 82 % base of skull fractures 58 % -46-
Analysis of accident cause in on scene investigations ACAS Accident Causation Analysis System -47-
On scene investigation Show inside in accident occurence Show injury pattern and detailed injuries Explain injury mechanism Find accident causes and human behavior Probability of occurence of injuries Influence parameter of injuries 48-48-
HOW CAN KNOW-HOW BE USED? Interdisciplinary survey technical medical traffic psychology -49-
How can know-how be used? Interdisciplinary expertises Forensic Technique Biomechanics Medicine & other disciplins -50-
How can know-how be used? Interdisciplinary expertises -51-
How can know-how be used? Interdisciplinary expertises Sitting position in the car Usage of seatbelt Efficiency of helmet usage Injury mechanism Injury causation Walking direction Suicidal intent Injuries accident probability Correlation of damages Speed calculation Avoidance strategies Possibility of sight Possibility of visibility Hit or run Insurance fraud Roll over of human body -52-
Whiplash -53-
Difficulty of Whiplash diagnosis Practical case forensical surveys rear-end collision Situation of cars and accident severity Diagnosis: based on accident event Delta-v 4,5 kph up to 6 kphh 1,5 g up to 2,5 g -54-
Basis of assessment: accident severity Delta-v 4,5 kph up to 6 kph 1,5 g up to 2,5 g -55-
Academic basis is comprehensive but not completely enlightening yet! Probability of occurence No absolute values usable! At best guidance according to scientific literature Frontal-collision (flexion of cervical spine) Vehicle deceleration > 5 8 g ( v > 10 kph) Rear-end collision (hyperextension of cervical spine): Vehicle deceleration > 2 g ( v > 3 kph) Lateral collision (lateral flexion of cervical spine): Vehicle deceleration > 6 g ( v > 3 kph) -56-
How in-depth-accident surveys are shown Whiplash Car occupant with seatbelt in GIDAS 40 Frequency % of whiplash injuries 35 30 25 20 15 10 5 0 year of construction < 2005 (n=24.223) year of construction greater equal 2005 (n=3.071) 10,2 8,8 9,7 10,7 36,9 33,4 25,0 Front Side Rear-end multiple Impact car 27,8-57-
accidents 1999-2012 n=26.104 accidents reconstr. n=23.391 participants n=45.070 cars n=27.584 cars n=2.170 occupants front n=2.952 n=2.763 Occupants front seated Data basis: rear-end collisions excluded STATUS not completed n= 2.255 without reconstruction n= 458 participants truck n= 2.736 bus, tram n= 897 Motorized two-wheeler n= 3.540 bicycle n= 7.058 pedestrian n= 3.145 other n= 108 unknown n= 2 delta-v unknown n= 4.239 multiple collisions n= 2.478 Collision partner no car n= 9.440 No rear-end collision n= 9.002 coll. partner not frontal n= 80 mass car unkown n= 114 mass coll. partner unkn. n= 61 Injury severity MAIS unknown n= 66 age unknown n= 123-58-
Regression coefficient B Standard error ge Wald df Sig. Exp(B) 95% confidence interval for EXP(B) Lower value Superior value DELTAV,015,002 58,960 1,000 1,015 1,011 1,019 Age -,010,001 45,103 1,000,990,988,993 Kind of impact 871,262 2,000 Kind of impact (1) 1,758,060 858,333 1,000 5,801 5,158 6,525 Kind of impact (2),253,065 15,393 1,000 1,288 1,135 1,462 Sex (1),905,047 370,657 1,000 2,473 2,255 2,712 Mass coll. partner 23,769 2,000 Mass coll. partner (1),195,066 8,727 1,003 1,215 1,068 1,383 Step 1 a Mass coll. partner (2),310,064 23,666 1,000 1,363 1,203 1,544 Mass car 3,365 2,186 Mass car (1),104,057 3,341 1,068 1,109,993 1,240 Mass car (2),081,074 1,190 1,275 1,085,937 1,255 Direction of impact (1),295,053 30,783 1,000 1,344 1,210 1,491 Constant -2,435,102 567,022 1,000,088 a. In step 1 entered variables: DELTAV, age, kind of impact, sex, mass collision partner, mass car, direction of impact. -59-
Except for the mass of the car all parameter show a highly significant influence. This means, that delta-v solely shows influence but not alone! it can be seen a significant influence in interaction with other variables -60-
Amount of isolated whiplash injuries in rear-end collisions [%] 80 70 60 50 40 30 20 10 0 whiplash MAIS 1 MAIS 2+ Poly. (whiplash) Poly. (MAIS 1) Poly. (MAIS 2+) 1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728 Delta-v [kph] -61-
Amount of isolated whiplash injuries in lateral collisions [%] 100 90 80 70 60 50 40 30 20 10 0 whiplash MAIS 1 MAIS 2+ Poly. (whiplash) Poly. (MAIS 1) Poly. (MAIS 2+) 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Delta-v [kph] -62-
Amount of isolated whiplash injuries in frontal collisions [%] 80 70 60 50 40 30 20 10 0 whiplash MAIS 1 MAIS 2+ Poly. (whiplash) Poly. (MAIS 1) Poly. (MAIS 2+) 1 3 5 7 9 1113151719212325272931333537394143454749 Delta-v [kph] -63-
Whiplash injuries conclusion symptoms of whiplash injuries possible at all accident constellations and Delta-v values Duration and scope of complaints are independent from Delta-v values and medical finding of steep position of cervical spine -64-
Duration and scope of complaints correlate with physiologic parameters gender vigour / training health situation degenerative pre-existing defects -65-
100 90 80 70 60 50 40 30 20 10 0 81,4 64,4 SF 36: whiplash injuries 85 81,4 81,4 77,3 78,2 72,5 71,1 66,5 60,4 56,3 52,9 50,4 50,8 38,7 Correlates with chronic pains whiplash injury chronic pain german standard population -66-
pre-existing affection or injury of spine? What is accidental cause? malposition, stiff segments? Does the pain correlate with: malposition,instability? Degeneration and influence? -67-
Surveys: Diagnostic approach anamnesis: afflictions statics / functional examination nerve examination x-ray, CT, MRT progression -68-
How a Whiplash case can be handled? Can only be answered in interdisciplinary surveys! Investigation of accident collision sequences Investigation of occupant kinematics and biomechanical stress Assessment of injuries and symptomatology Inclusion of additional experts (neurosurgery, psychological, ) if necessary Interdisciplinary report -69-
Examples -70-
Causation of plunge in staircase Elderly lady declares, that she tumbled over the defect banister after leaving her apartment. She was found lying in front of the door one floor downstairs -71-
Causation of plunge in staircase Metodology of expertises: Preparing a true to scale drawing Reconstruction of accident with motion analysis and assessment of injuries -72-
Plunge in staircase profile of staircase from point cloud Top floor apartment of complainant banister, over which she tumbled (according to her own statement) Final position of complainant -73-
Plunge in staircase - Simulation with PC-Crash Different motion sequences can be simulated this way: Plunge from stairs (final position reached) -74-
Plunge in staircase - Walk over stairs Different motion sequences can be simulated this way: Plunge over banister (final position not reached) Conclusion Only possible Falling on stairs Lower stairs level No influnce from fender -75-
Example -76-
Visibility of a person in a run over Accident: In the morning hours (darkness) a person lying on the road surface was run over by a car in a right-hand bend. Question: preventability of the accident by the car driver? Photos from the official photo report -77-
Run over a person True to scale sketch : Final position of the person (claimant) and location of the collision approx. 3 m in front of the final position -78-
Run over a person Approach: From experimental run overs: collision position approx. 3 to 4 m in front of the final position of the person Quelle Otte Dipl.arb. 1975-79-
Run over a person Approach: investigation of possible influence of the light towers with known light beam include light beam of car in the simulation Road trials on accident scene with dummy (darkness) -80-
Run over a person Dummy Die Sicht auf den Dummy mit Abblendlicht: -81-
Example -82-
Injury of a person in an isolated braking maneuver? Event: Sternum fracture with or without seatbelted? A car driver indicates, that he was forced to an emergency braking maneuver Approach: Investigation of occurred force with seatbelt 1. approximation: balloon between person and seat belt 2. approximation: measure the load with a pressure indicating film -83-
Injury of a person in an isolated braking maneuver? 1. approximation: balloon between person and seat belt for illustration of the occuring forces -84-
Injury of a person in an isolated braking maneuver? 2. approximation: measure the pressure / forces with a pressure indicating film for driver and passenger -85-
2. approximation: measure the pressure / forces with a pressure indicating film Injury of a person in an isolated braking maneuver? max. pressure 0,0005 MPa to 0,0013 MPa equal to 500 Pa to 1300 Pa or 5,0 g/cm² to 13,0 g/cm². max. force between 0,3 N and 1,9 N in static view approx. 30 gram to 190 gram Only very low pressures present. -86-
Other Parameter useful for reconstrution Throw distance of peds, bics Injury severity parameter for safety devices (helmet, seatbelt..) Injury probability functions AIS = f(speed, delta-v, EES, rel. Speed) -87-
throw distances of pedestrians 40 throw distance pedestrian [m] 35 30 25 20 15 10 5 0 0 20 40 60 80 100 impact speed car [kph] -88-
impact speed vs. injury severity of bicyclists injury severtiy grade AIS head 7 6 5 4 3 2 1 0 no impact windscreen area windscreen impact A-pillar impact 0 20 40 60 80 100 120 impact speed car [kph] -89-
throw distances of bicyclists throw distance bicyclist [m] 20 18 16 14 12 10 8 6 4 2 0 central car edge 0 10 20 30 40 50 60 impact speed car [kph] -90-
bicyclists 35 Fahrradfahrer y=(.164285)*x+(.396e-3)*x*x 30 25 throw distance Wurfweite [m] 20 15 10 5 0-5 0 20 40 60 80 100 VAUK impact speed -91-
pedestrians 90 Fussgänger y=(-.01499)*x+(.006025)*x*x 80 70 WWEITFGM throw distance 60 50 40 30 20 10 0-10 0 10 20 30 40 50 60 70 80 90 VAUK impact speed -92-
functional variable: throw distance[m] source overall linear modell (Varianz analysis) square sum of type III df mean of squares F Sig. corrected modell 2954,596 a 9 328,288 42,295,000 constant term 10,010 1 10,010 1,290,257 Walking direction 126,392 3 42,131 5,428,001 type of car,000 0... front collision 30,661 2 15,330 1,975,140 car braking,950 1,950,122,727 impact speed 2530,227 1 2530,227 325,980,000 body height cm,060 1,060,008,930 first registration 9,486 1 9,486 1,222,270 failure 2701,146 348 7,762 total 11314,115 358 corrected total variation 5655,742 357 a. R-square =,522 (corrected R-square =,510) -93-
Technical Parameters for Determination of Impact Speed for Motorcycle Accidents and the Importance of Relative Speed on Injury Severity SAE Paper 06B-422 2006 Injury correlation of Relative speed Throw distance -94-
Conclusion Experiences of experts are needed Data of accident research is needed Interdisciplinary cooperation of experts has benefits Adoption of an interdisciplinary apporach of biomechanics is important Education sills of experts would be useful -95-
Thank you very much for your attention! -96-