IRC-15-52
IRCOBI Conference 2015
A Fittness Function for Vehiccle Front Opttimisation fo
or Pedestrian
n Protectionn, Accountingg for
Real‐world Collision Con
nfigurations
Guibing Li, Ji
G
kuang Yang, Ciaran Simm
ms* I. IINTRODUCT
TION
Th
he design o
of a vehicle front has significant s
innfluence on pedestrian injury risk in a vehicle
e collision [1]. Significant progress has been made in understaanding which
h features of o vehicle froont design are a crucial for f
mitigating ped
m
destrian inju
uries. However, real‐worlld accidents show that an optimal veehicle design
n has not been acchieved and current evaaluation stan
ndards only consider lim
mited impacct configurattions. The purpose of th
his sttudy is to develop a fittness functio
on for vehiccle front optimisation for pedestriaan protectio
on based on
n a multi‐body sim
m
mulation sam
mple that can
n represent rreal‐world acccident scenarios. I I. METHOD
DS
Pe
edestrian Acccident Scena
arios Ve
ehicle impact speed, pedestrian height, pedesstrian gait stance s
and walking speeed are the
e main facto
ors in
nfluencing seeverity of pedestrian in
njuries in a vehicle imp
pact [1‐2]. The distributtion of these four impaact paarameters w
was derived from previo
ous studies [2‐5] (Table I; Fig. 1) as the inputss of MADYM
MO multi‐body simulations off vehicle ped
destrian impa
acts, with a bbaseline mod
del from Ellio
ott et al. [6]. TABLE I IMPPACT PARAMETTERS Impact paraameter
Vehicle impac
V
ct speed Pedestrian h
height Pedestrian gai
P
it stance Pedestrian sspeed Source
IHRA
A accident datta [3]
Age groups in IHR
RA accident daata [3] and an
nthropometricc data of Britissh [4]
10 gait stancess during the w
walking cycle re
eported by Unntaroiu et al. [2]
Age group in IHRA acciddent data [3] and walking sp
a
peed distributtion from Hua
ang et al. [5]
Fig. 1. D
Distribution of f vehicle impact speed and pedestrian he
eight, gait stan
nce and walki ng speed in accidents. In
njury Cost Ass reported in
n ISO 13232‐‐5 [7], injury cost (includiing medical and auxiliaryy costs) can bbe calculated
d based on A
AIS in
njury levels iin the differrent body re
egions. Thesse were estimated by the t injury crriteria extraccted from the MADYMO M
sim
mulations. In
n the curren
nt study, injjury criteria of HIC (head), Nij (ne ck), sternum
m acceleratio
on (thorax), laterral impact fo
orce (pelvis),, bending m
moment (longg bones in lo
ower limbs) and bending angle (kneee) were used for
w
r calculating the overall p
pedestrian innjury cost in a collision. T
The limits of tthose injury criteria for A
AIS were adapted
w
d from previo
ous studies [8
8‐12]. Siimulation Teest Sample In
n order to reduce the computing tim
me of the opttimisation prrocess, a sim
mulation test sample with
h a reasonab
ble size was devveloped for predicting pedestrian iinjury risk in real‐word
d accidents. Preliminaryy investigatio
on in
ndicated thatt collisions o
of impact speed less thaan 20 km/h o
only accountt for about 22% of the to
otal injury co
ost an
nd pedestrian * G. Li is Ph.D. sstudent in Biom
mechanics at Trinity T
College D
Dublin, Ireland. J. Yang is Pro
ofessor of Biom
mechanics in th
he Departmentt of Ap
pplied Mechan
nics at Chalmers University of o Technology,, Sweden. C. Simms S
is Profe
essor of Biomeechanics in the Department of - 398 -
IRC-15-52
IRCOBI Conference 2015
Mechanical and Manufacturing Engineering,, Trinity Collegge Dublin, Ireland (tel: +353
3 1 896 3768; fax: +353 1 6795554; e‐mail: [email protected]). walking speed
w
d has no sign
nificant influ
uence on injuury cost whe
en impact sp
peeds are higgher than 20
0 km/h. So the im
mpact speed range of thee test sample is from 20 km/h to 70 km/h (only 2.4% pedesttrian acciden
nts occurred at im
mpact speeds above 70 kkm/h), and o
only the meaan walking speed of the correspondiing age grou
up was applied fo
or the pedesstrian models. The impacct speed wa s divided intto 10 groupss with an intterval of 5 km/h (Table II). Th
he pedestriaans’ heightss were mod
delled by sccaled MADYYMO pedesttrian model s [12] (Tab
ble II). All the pe
edestrian mo
odels were cconfigured in
nto 10 gait sttances [2]. In total, 800 (10*8*10=8000) impact sscenarios weere se
et as the sim
mulation testt sample forr assessing thhe safety pe
erformance of o a vehicle front design
n in real‐worrld pe
edestrian acccidents (Tab
ble II). As sho
own in Eq. ( 1), the prop
portion of ea
ach impact s cenario ( ) in the samp
ple was w calculateed based on the normallised proporrtion of impaact parametters ( ‐imppact speed, ‐pedestrian he
eight and ‐pedestrian
n gait stance
e). The weig hted injury cost (
) of the simullation test sample (fitneess fu
unction for vvehicle frontt optimisatio
on) is the su m of the prroduct of injury cost ( ) and proportion of each im
mpact scenarrio. ∑
∑
∗
∗
∗
((1) ∗
To
o assess thee representativeness off the simulaation test sample, s
com
mparison waas made witth benchmaark simulation sam
mples of 10,000 random
mly selected iimpact scenaarios (minimum size for rrepeatable o
outputs) based on
n distributions of impactt parameterss in the acciddent data (Figg. 1) for a sed
dan model. TABLE II TEST SSIMULATION SAAMPLE Vehicle
V
impactt speed /simu
ulation speed (km/h)
(20‐24)//22, (25‐29)/2
27, (30‐34)/32
2, (35‐39)/37, (4
(
40‐44)/42, (45
5‐49)/47, (50‐5
54)/52, (55‐59)//57, (60‐64)/6
62, (65‐69)/67
7 Pedestriian height/mo
odel height (m
mm)
1125‐1435)/1170, (1435‐15575)/1530, (‐‐1125)/970, (1
(1575‐1625)/1600, (1
1625‐1675)/16650, (11675‐1725)/17
700, (1725‐17
775)/1750, (17775+)/1850 Gait stance
e
0%‐90%
(10 discrete cases) III. IINITIAL FIND
DINGS
Figure 2 show
ws proportion of injury ccost associatted with veh
hicle speed, pedestrian hheight and p
pedestrian gait an
nd pedestriaan body reggion for the simulation test sample
e (N=800) compared too the benchmark samplles (N
N=10,000). The results sh
how very sim
milar distributtions of injurry cost, with relative erroors always w
within 5%. Fig. 2. In
njury cost distributions as im
mpact parameeters and bod
dy region in the test samplee and benchmark samples.
IV
V. DISCUSSIO
ON
Th
he comparisson results show that the t simulatiion test sam
mple can represent thee prediction ability of the in be
enchmark saamples wherre the impacct parameteers were randomly selected accordinng to their distributions
d
th
he accident data. The weighted w
inju
ury cost fro m the simulation test sample s
(N=8800) could therefore bee a po
otential fitneess function for vehicle front optimissation for ped
destrian injury mitigationn. V
V. REFERENCEES
Simms, C
C., et al. Sprin
nger, 2009. 2] Untaroiu C. D., et al. IIJ Impact Eng
g, 2009. [2
[3] Mizuno, Y
Y., et al. ESV
V, 2002. 4] Pheasantt, S., et al. Ta
aylor & Franccis, 2006. [4
[1]
et al. Safety SScience, 2008
8. Huang, S., e
hE, 2012. [6] Elliott, J. R., et al. Imech
5. [7] ISO: 13232‐‐5, ISO, 2005
A, 2001. [8] Payne, A. R., et al. MIRA
[5]
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IRC-15-52
[9]
[10]
Eppinger, R., et al. NHTSA, 1999. Cavanaugh, J. M., et al. STAPP, 1993. IRCOBI Conference 2015
[11]
[12]
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Mo, F., et al. Traffic Inj Prev, 2013. MADYMO, TNO, 2012.