GIDAS German In-Depth Accident Study...Hannover Medical School, Germany. GIDAS German In-Depth...

GIDAS German In-Depth Accident Study

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Injury Severity and Causation Factors of Motorcyclists in Traffic Accidents in

comparing Drivers of Motorcycle and All Kinds of Motorized Two-wheelers

Otte, D.*, Jänsch, M.*, Wiese, B.**

Accident Research Unit* Biometric Institute**,

Hannover Medical School, Germany


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content

• Introduction of research methodology• Analysis frame and data• Accident and Injury situation• Accident Causation• Conclusions• Improvements for more safety


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Technical University Dresden

2000accidents

annual

1000 accident 1000 accident

Medical University Hannover

By order of Federal Highway Research Institute BASTAutomotive Research Association FAT

2000 accident

methodology


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Description of sampling

HELIOS

Representative Data Sampling on Scene

random selectionSelection criteriaWeigthing process

No personal decision for selection of case !All kind of traffic accidents with injured person !Comparison to national or regional statistics !

Police reported accidentsmethodology


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What to do on scene ?

Description of samplingmethodology


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MAIS 2AIS-Head 2

AIS-Arms 2

AIS-Legs 2

Commotio Cerebri AIS 2

Laceration Head right frontal AIS 1

Fracture of head of radius right AIS 2

Rupture left crucial ligament AIS 2

Kind + Locaton + Severity AIS 2005

Injury documentation

methodology

Abbreviated Injury Scale


- 7 -

3020100207


- 8 -

Kompression fracture 5th thorax vertebra

Luxation Daumen right

PASSAT VK 20 km/hDUCATI VK 40 km/hVrel 46 km/h

MAIS 2Motorcycle driver38 y. m.

3020100207


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Human # Machine # Environment

• "Human“ Group 1, human cause factors (Seven Steps)

• „Machine“ Group 2, factors from the technical nature of the vehicle

• "Environment“ Group 3, factors from the range of the infrastructure and nature

ACASSmethodology


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Erkennen

Einschätzen

Beobachten

Informationszugang

Planen

(6) Selection

(7) Operation

The causes of traffic accidents can be found in three different areas: Human factors, technical factors form the vehicle and factors from the infrastructure or environment presented in three groups of the system.

The human factors consist of seven categories (7 Steps)Chronological sequence of basic human functions from the perception, the judgment of the perceived situation to the resulting operation.

(1) Wrong expectation

(2) Misjudgement of others

(3) Misjudgement of own vehicle

Each category consists of specific criteria which specifies the factor within the category.

Group

1:

Hum

an fa

ctors

(3) Recognition

(4) Evaluation

(2) Observation

(1) Information access

(5) Planning

(1) Own speed

(3) Braking, Accelerating

(2) Veh.‐dynamics/behaviour

Solely the human factors allow to further categorize the chosen criteria with

specific indicators.

Code of 4 numbers

ACASS methodology


- 11 - Recording of accident causation data in GIDAS

x Comments box

Comments box

Multiple causation-codes for each accident participant are possible:

Causation factors

codes possible per accident participant

Source of informationNumbers 1 to 9 how the information was obtained

Doubts concerning the reliability of the coded information

Comments to explain the selected code

. . .

1st Code:

2nd Code:

Comments box 5th Code:

ACASS methodology


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The analysis !

• Data selection• Kind of injuries• Frequency of injured body areas and

severity grades• Impact loads• Accident situation and causation factors


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Motorized Two Wheelers

• Mofa, Moped, Mokick, light motorcycle• Motorcycle, Scooter


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Passive Safety Sample Frame Active SafetyGIDAS 1999-2011

n=24.013

casesn=23.033

participantsn=44.348

motorcyclen=3.474

Fahrer mot. Zweirädern= 2.864

passive Sicherheit

STATUSnot complete n= 715no reconstruction n= 265

participationcar n=27.209truck n= 2.690coach, tram n= 890bicycle n= 6.897pedestrian n= 3.074others n= 114

excluded

Zweiradunknown, quad n= 29no cyclist n= 2

motorcyclistn=3.443 unknown

MAIS n= 162head injuries n= 31helmet n= 386

Hannover 2008-2012 n=4.798

casesn=4.314

participantsn=8.324

cars n=4.939motocycles n=629

drivercar n= 4.569motorcycle < 125 cm³ n= 260motorcycle > 125 cm³ n= 285

active safety


participationtruck n= 504coach, tram n= 116bicycle n= 1.598pedestrian n= 512others n= 26

excluded

driverno cyclist, quad n= 454

motorcyclistn=5.114

all motorcyclistsn= 2.864

motorcyclist (> 125 ccm)n=1.406

passive safety


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The situation of Injury Severity in Germany forMotorcyclists (n=2864)

5,2

57,3

25,6

8,2

1,6 1,3 0,80

10

20

30

40

50

60

70

MAIS 0 MAIS 1 MAIS 2 MAIS 3 MAIS 4 MAIS 5 MAIS 6

%

11,9 % MAIS 3 + Severely injured

GIDAS 2013, Unfälle von 2000 bis 2012


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61,0

31,5

5,61,0 0,4 0,3 0,2

0

10

20

30

40

50

60

70

MAIS 0 MAIS 1 MAIS 2 MAIS 3 MAIS 4 MAIS 5 MAIS 6

[%]

Belted Car Occupants (n=21.668)

1,8% MAIS 3+

GIDAS 2013, Unfälle von 2000 bis 2012

For Comparison!


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Relative Speed in motorcycle accidents

0102030405060708090

100

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140> 140

% c

umul

ativ

e

Relative speed [km/h]

alle mot. Zweiräder (n=2501) Motorräder (n=1277)


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maximum injury severity grades

4,4 4,1 4,6 6,1

64,8 65,1 60,3 50,8

27,5 23,3 26,326,8

3,3 7,5 8,816,3

0

10

20

30

40

50

60

70

80

90

100

moped 25 (n=91) moped (n=943) up to 125 ccm(n=415)

> 125 ccm (1415)

%

type of motorcycle

MAIS 3+MAIS 2MAIS 1MAIS 0


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injury severity and power-weight ratio

4,8 7,3 5,7 6,0 4,2 4,2

48,755,0 57,6 61,9 58,6

68,4

25,327,2 25,3 23,1 25,6

22,321,2

10,5 11,4 9,0 11,6 5,1

0

10

20

30

40

50

60

70

80

90

100

0-3 (n=376) 4-8 (n=600) 9-12(n=158)

13-20(n=268)

21-30(n=355)

>30 (n=215)

%

power-weight ratio [kg/kW]



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collision types of all motorcycles (n=2,848)

5,49,9

6,8

21,1

8,23,9

44,7

0

10

20

30

40

50

60

type 1 type 2 type 3 type 4 type 5 type 6 type 7

%

collision types

all types of motorcycles


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coll.types and injury severity grade of all motorcyclists

0,7 1,4 2,6 2,2 1,7 4,5 9,0

58,8 52,158,5 63,8 60,5

68,7 53,5

30,128,7

24,622,6 25,3

20,526,7

10,417,8 14,3 11,4 12,5 6,3 10,8

0

10

20

30

40

50

60

70

80

90

100

type 1(n=153)

type 2(n=282)

type 3(n=195)

type 4(n=602)

type 5(n=233)

type 6(n=112)

Typ 7(n=1271)

%

collision types


all types of motorcycles


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collision types motorcycles > 125 ccm (n=1,406)

3,99,1

6,4

20,3

7,93,6

48,8

0

10

20

30

40

50

60

type 1 type 2 type 3 type 4 type 5 type 6 type 7

%

collision types

motorcycles > 125 ccm


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Collision types and injury severity motorcyclists

0,0 1,6 2,2 1,7 1,8 8,0 10,3

67,346 48,9

59,1 52,3

70

45,5

29,1

29,7 28,923,8

26,1

16

28,3

3,6

22,7 20,0 15,4 19,86,0

15,9

0

10

20

30

40

50

60

70

80

90

100

type 1(n=55)

type 2(n=128)

type 3(n=90)

type 4(n=286)

type 5(n=111)

type 6(n=50)

type 7(n=686)

%

Kollisionstypen


motorcycles > 125 ccm


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injury severity head with and without helmet

80,0

7,6 9,03,4

72,7

11,5 11,54,3

0

10

20

30

40

50

60

70

80

90

AIS 0 AIS 1 AIS 2 AIS 3+

%

injury severity grade of head

with helmet (n=2725) without helmet (n=139)

34% 22% 21%

reduction of injury severity


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injured body regions of drivers vs. type of motorcyclefrequencies of injured body regions

moped25 mopedn=91 n=943

33,05,5

29,71,1

23,19,9

22,04,4

16,5

3,331,915,4

6,6

44,0

53,8

21,58,0

22,94,316,39,724,95,712,0

7,439,017,115,3

47,3

72,0

16,19,9

26,73,6

18,311,326,0

4,813,3

10,139,322,923,6

47,5

73,5

19,99,8

35,54,912,212,322,98,614,3

10,729,318,320,7

44,1

67,2

frequencies of injured body regions

up to 125 ccm > 125 ccmn=415 n=1415


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injured body regions vs. protective clothingfrequenies of injured

body regions

protective clothingwith without

19,9-

33,05,4

12,410,921,4

6,312,6

12,329,717,218,4

42,7

66,6

27,39,1

27,43,716,711,525,87,715,0

7,736,419,219,1

48,0

70,7

with protective clothing without protective clothingAIS 1 AIS 2 AIS 3+ AIS 1 AIS 2 AIS 3+

head 37,6% 46,4% 16,0% 42,1% 42,1% 15,8%neck - - - 81,2% 8,8% 10,0%thorax 58,6% 24,7% 16,7% 65,7% 22,5% 11,8%upper extr. total 75,8% 20,9% 3,3% 81,8% 16,4% 1,8%upper arm 47,8% 42,0% 10,1% 56,9% 43,1% -elbow 99,4% 0,6% - 99,2% 0,8% -lower arm 42,9% 49,3% 7,9% 58,6% 34,8% 6,6%hand,-joint 87,9% 12,1% - 86,8% 13,0% 0,2%abdomen 55,8% 25,0% 19,2% 67,4% 24,2% 8,4%pelvis 75,3% 16,7% 8,0% 86,0% 11,5% 2,5%lower extr. total 70,8% 16,8% 12,4% 78,4% 14,0% 7,6%upper leg 41,5% 6,5% 52,0% 50,3% 4,2% 45,5%knee 86,2% 13,4% 0,3% 90,4% 9,2% 0,4%lower eg 59,9% 29,7% 10,4% 66,9% 22,7% 10,4%foot, ankle joint 69,9% 27,8% 2,3% 77,9% 20,6% 1,5%

inujured body regions only

100% 100%

keine

100%


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trend of injury severity grades of all motorcyclists

8,1

44,6

26,121,2

4,8

54,3

26,1

14,8

4,5

64,0

23,1

8,4

0

10

20

30

40

50

60

70

MAIS 0 MAIS 1 MAIS 2 MAIS 3+

%

maximum injury severity grade

1985-1993 (n=655) 1994-2002 (n=866) 2003-2011 (n=1196)


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injury severity grades of motorcyclists (cycle > 125 cm³)

9,4

42,1

26,921,6

5,6

50,7

26,9

16,8

4,7

58,2

23,9

13,1

0

10

20

30

40

50

60

70

MAIS 0 MAIS 1 MAIS 2 MAIS 3+

%

maximum injury severity grade

1985-1993 (n=416) 1994-2002 (n=554) 2003-2011 (n=548)


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Passive Safety Sample Frame Active SafetyGIDAS 1999-2011

n=24.013 Used for active safetyanalysis

Hannover 2008-2012 n=4.798

casesn=4.314

participantsn=8.324

cars n=4.939motocycles n=629

drivercar n= 4.569motorcycle < 125 cm³ n=260motorcycle > 125 cm³ n=285

active safety


participationtruck n= 504coach, tram n= 116bicycle n= 1.598pedestrian n= 512others n= 26

excluded

driverno cyclist, quad n= 454

motorcyclistn=5.114


- 30 - Destatis 2010

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

18‐21 21‐25 25‐30 30‐35 35‐40 40‐45 45‐50 50‐55 55‐60 60‐65 65‐70 70‐75 75+Driver‘s Age [years]

Quotient of „causers of accidents“ and „all accident participants“ for different types of age groups

All road users (n=503590) Riders of poweres two‐wheelers (n=24039)


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97,7%

1,4%6,4%

91,1%

2,8%

19,6%

91,7%

2,6%

14,0%

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

90,0%

100,0%

Human Machine Environment

Distribution of accident causation groupsComparing passenger cars with light and heavy motorized two‐wheelers

Car(n=3012)Motorcycle <125ccm(n=179)Motorcycle >125ccm(n=193)

GIDAS Hannover 2008‐2012


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Composition of ACAS-codeexemplarily for Group 1 (human factors)


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15,5%

51,1%

20,0%

17,5%

7,2%

7,4%

25,8%

29,4%

18,4% 23,3%

5,6%

16,9%

33,3%

45,8%

17,5%

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

Information access Informationadmission

Informationevaluation

Planning Operation

Distribution of human causation categoriesComparing passenger cars with light and heavy motorized two‐wheelers

Car(n=2942)

Motorcycle <125ccm(n=163)

Motorcycle >125ccm(n=177)

GIDAS Hannover 2008‐2012


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Beschreibung des Einflussfaktors

ACAS-Code

Häufig-keit %-Anteil

Überhöhte Geschwindigkeit 14022 34 68%Falsches Überholen 14023 10 20%Falsches Abbiegen 14024 1 2%Abstandsunterschreitung 14025 2 4%Regelwidrige Benutzung des Verkehrsweges 14027 1 2%Andere 14028 2 4%

Beispiel Überhöhte Geschwindigkeit (14022) (30110683)

Motorrad: Suzuki GSX-R750Fahrer: Männl., 29 Jahre, Schwerverletzt MAIS 3

Der Motorradfahrer befuhr die Straße "Hermann-Ehlers-Allee" mit hoher Geschwindigkeit. Er wollte bremsen, da die LZA auf Rot stand, dabei verlor er die Kontrolle über sein Krad und rutschte gegen die LZA und verletzte sich schwer

Verteilung der bewussten Regelverstöße bei mot. Zw. > 125 ccm

Vzul = 50 km/hV0 = 124 km/h


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4,7% 10,0% 4,3% 5,9% 7,0% 1,5%

63,1% 55,0%

47,8%

61,4%53,0% 68,7%

23,5% 30,0%

36,2%

23,8%29,0%

23,9%

8,7% 5,0%11,6% 8,9% 11,0% 6,0%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

No causationfactor(n=173)

Informationaccess (n=22)

Informationadmission(n=72)

Informationevaluation(n=107)

Planning(n=111)

Operation(n=69)

Injury severity distribution for different categories of human causation factors of PTW riders



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4,9%12,5% 7,5% 2,8%

62,2%

62,5%

39,3%

54,7%52,8% 56,7%

19,5%

25,0%

50,0%

24,5%29,2%

36,7%

13,4% 10,7% 13,2% 15,3%6,7%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

No causationfactor (n=92)

Informationaccess (n=10)

Informationadmission(n=30)

Informationevaluation(n=59)

Planning(n=81)

Operation(n=31)

Injury severity distribution for different categories of human causation factors for riders of motorcycles (>=125 ccm)

MAIS 3+

MAIS 2

MAIS 1

MAIS 0


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Conclusions• Motorcyclists highly protected • MAIS 1 of 60 to 65%• Wearing helmets motorcyclists only 19.9%

suffered head injuries.• effectiveness of the helmet confirmed• reduction of head injuries AIS 1 to minus

34% and AIS 2 to minus 22% and severe head injuries AIS 3+ to minus 21%.


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Conclusions• Severe injuries AIS 3+ are particularly often in

association with a high risk of bone injuries of the cervical spine and the lower extremities.

useful solution • usage of protective clothing with protectors

use of padded machines• development of special leg protectors (Otte, 2002)


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• reduction of severely injured motorcyclists of nearly 50% over the time period of more than 20 years

Accidents caused by a failure of information admission (e.g. the rider misses to see a relevant road user due to a wrong focus of attention) of the rider of a PTW resulted in visibly higher shares of MAIS 2 had MAIS 3+ injuries than failures from the other categories


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• failures in the Information evaluation related to a misjudgment of the behavior or speed of the own vehicle (in about 20% of the cases).

• PTW have a high incidence of accident causes from the subcategory of intentional breach of rules.

• riders of motorcycles (≥ 125 ccm) have an incidence of over 40% from the subcategory which is mostly related to excessive driving speed.

• Another source of accident causes which is specifically high with PTW (23.3% for light motorcycles, 17.5% for motorcycles but only 7.2% for cars) is the handling failures, in wrong braking or over braking


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Parameter analysisInfluence on injury severity AIS

Analysis of EffectsEffect DF Wald

Chi-SquarePr > ChiSq

Relative speed 1 50.9341 <.0001age 1 8.8486 0.0029

Crash weight 1 3.9641 0.0465Driving kilometer 8 7.4723 0.4866

Information access 1 4.5625 0.0327Information adaption 1 6.2102 0.0127Information process 1 0.0822 0.7743

Task of driving 1 0.0369 0.8477handling 1 0.3300 0.5657

Kind of cycle 1 4.9166 0.0266


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Improvements• Speed reduction helps avoidance of

accidents and reduction of injury severity!• Earlier Information of oncoming confict-

situation helps for avoidance stategies


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• High safety standard is given formotorcyclists

• The acceptance of safety measures isnot so much exsisting for others PTW

• Helmet is shown high effectiveness, ifusing the integral helmet design

• Protective clothes gives effectivenessagainst soft tissue injuries, higherusing rate shouldbe realized


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• motorcycle drivers should be bettereducated and traineed

• More attention for driving assistanceespecially for older drivers

• Information on special behavior of PTW as education of other trafficparticipants i.e. car-dtruck-drivers

••


- 45 -

• Thank you very muchfor your attention

GIDAS German In-Depth Accident Study...Hannover Medical School, Germany. GIDAS German In-Depth...

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