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Transport and Telecommunication Vol. 15, no. 3, 2014
Transport and Telecommunication, 2014, volume 15, no. 3, 227–232
Transport and Telecommunication Institute, Lomonosova 1, Ria, LV!101", Latvia
#$I 10.247%&tt'!2014!0020
ANALYSIS OF INTRA-URBAN TRAFFIC ACCIDENTS USING
SPATIOTEMPORAL VISUALIZATION TECHNIQUES
Ali Soltani 1,2
, Sajad Askari 1
1 Department of Urban Planning, Shiraz University, Iran, Goldasht St., Maaliabad, Shiraz Phone:
!"#11$%&'()&. *+mail: soltanishiraz-.a.ir
%Urban /esearh program, Griffith University, 0D, ('', 2-stralia Phone: $1#&)#''&. *+mail:
a.soltanigriffith.ed-.a-
Road tra((ic accidents )RT*s+ ran in t-e top ten causes o( t-e loal urden o( disease and in'ur/, and Iran -as one o( t-e -i-est
road tra((ic mortalit/ rates in t-e orld. T-is paper presents a spatiotemporal anal/sis o( intra!uran tra((ic accidents data in
metropolitan -ira, Iran durin t-e period 2011–2012. It is tried to identi(/ t-e accident prone ones and sensitive -ours usin
eorap-ic In(ormation /stems )I+!ased spatio!temporal visualiation tec-niues. T-e anal/sis aimed at t-e identi(ication o(
-i-!rate accident locations and sa(et/ de(icient area usin ernel 6stimation #ensit/ )6#+ met-od. T-e investiation indicates
t-at t-e ma'orit/ o( occurrences o( tra((ic accidents ere on t-e main roads, -ic- pla/ a meta!reion (unctional role and act as alinae eteen main destinations it- -i- trip eneration rate. *ccordin to t-e temporal distriution o( car cras-es, t-e pea o(
tra((ic accidents incident is simultaneous it- t-e tra((ic conestion pea -ours on arterial roads. T-e accident!prone locations are
mostl/ located in districts it- -i-er speed and tra((ic volume, t-ere(ore, t-e/ s-ould e considered as t-e priorit/ investiation
locations to sa(et/ promotion prorams.
Keyword! *ccident Tra((ic patio!temporal *nal/sis -ira
"# I$%rod&'%(o$
Road Tra((ic *ccidents )RT*s+ -ave een and are continuin to e a ma'or contriutor o( -uman and
economic costs to reuirin concerted multi!disciplinar/ e((orts (or sustainale e((ective prevention. RT*s
ran in t-e top ten causes o( t-e loal urden o( disease and in'ur/, and ill proal/ e in t-ird place /
2020, -en measured in disailit/!ad'usted li(e /ears lost )89$, 2013+. 8it- onl/ 25 percent o( all
motoried ve-icles, developin countries account (or %: percent o( all road tra((ic deat-s )Laarde, 2011+.
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*ppro;imatel/ 1.24 million people die ever/ /ear on t-e orldorton, ? @u, 200%+ and anot-er 20 to 50 million sustain non!
(atal in'uries as a result o( RT*s. 6arl/ in t-is decade, some 20 to 50 million people in t-e orld ecame
totall/ or partiall/ incapacitated due to in'uries caused / tra((ic accidents. In'ured and trauma victims
too 10 per cent o( all -ospital eds t-at /ear )Ivers, tevenson, >orton, ? @u, 200%+. Aurrent trends
suest t-at / 2030 road tra((ic deat-s ill ecome t-e (i(t- leadin cause o( deat- unless urent action
is taen )89$, 2013+. * reat numer o( patients are transported to t-e emerenc/ ard due to tra((ic
accident in'uries. T-ese cases are a dail/ c-allene (or t-e teams orin in pre and intra!-ospital
settins, especiall/ due to t-e severit/ o( t-e in'uries and to t-e time it taes to reac- t-e -ospital and
(orard patients to surer/ )Aalil et al., 200"+. Bnless appropriate action is taen urentl/, t-e prolem
ill orsen loall/. T-is ill particularl/ e t-e case in t-ose developin countries -ere rapid
motoriation is liel/ to occur over t-e ne;t to decades )Co-ammadi, 2013+. T-e main reasons e-ind
t-e dramatic increases o( t-e numer o( RT*s can e listed as an insu((icient road s/stem, a rapid increase
in t-e numer o( motoried ve-icles, inadeuac/ o( road sa(et/ policies, recless drivin and poor
emerenc/ services )*DnEr, 2007+.
Iran -as one o( t-e -i-est road tra((ic mortalit/ rates in t-e orld. Cotor ve-icle–related accidents account (or
more t-an 1
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Transport and Telecommunication Vol. 15, no. 3, 2014
)# L(%er*%&re Re+(ew
RT*s result in in'uries and deat-, ut man/ are preventale, -oever t-e/ are commonl/ anticipated to
(orm clusters in t-e eorap-ic space and over time (or t-e reason t-at t-eir occurrence is tied to tra((ic
volumes )@amada ? T-ill, 2004+. To developin strateies to prevent t-em, reducin tra((ic accidents, and
improvin road sa(et/, an imperative need to understand -o, -ere and -en RT*s occurred and
distriuted across space and time )Frunsdon, Aocoran, ? 9is, 2007 Gie ? @an, 200% Hlu, Gia, ?
Aaul(ield, 2011+, and utilie spatiotemporal patterns in road sa(et/ polic/ capturin. T-e importance o(
-avin a compre-ensive cras- map -as een -i-li-ted as a sini(icant component o( sa(et/ data
manaement in strateic -i-a/ sa(et/ plans )in, Harer, Liu, raettiner, ? Jorde, 2013+. In'uries due
to RT* depend upon a numer o( (actors!-uman, ve-icle and environmental (actors pla/ vital roles
e(ore, durin and a(ter a serious RT*. T-e sini(icant (actors are -uman errors, driver (atiue, poor
tra((ic sense, poor condition o( ve-icle, speedin and overtain violation o( tra((ic rules, poor road
in(rastructure, tra((ic conestion, and road encroac-ment. In terms o( severit/ o( accident, drivin speeds
are o( ma'or importance as ell. 6nvironmental (actors include t-e condition o( t-e road netor, road
t/pe and desin, spatial conte;t )e.. densit/ and land!use plantation etc.+, temporal conte;t )e..,
darness+ and transport conte;t )tra((ic densit/, speed and e-aviour o( ot-er transport users+. ocial and
ps/c-oloical (actors include socio!demorap-ic and socio!economic structures, ris attitudes, li(est/les
and Kmoilit/ st/lesK and associated e-aviour )9ol!Rau and c-einer, 2013+.
Identi(/in accident -otspots and appendin value added data to understand t-e processes -appenin int-ese -otspots are important (or t-e appropriate allocation o( resources (or sa(et/ improvements. F/
identi(/in road accident, a more roust understandin can e ained, it- reards to indicators o( casual
e((ects )*nderson, 200"+. In order to conduct a reliale anal/sis o( t-e RT*s develop control strateies, it
is reuired to investiate (irstl/ -o t-e accidents are eorap-icall/ distriuted, secondl/ reions -ere
accident is oserved more dense, and t-irdl/ t-eir eo!statistical aspects )$an, Tar-an, 6ser, @aut, ?
a/in, 2013+. *n improved understandin o( t-e spatial patterns o( RT*s can mae accident reduction
e((orts more e((ective )Gie ? @an, 200%+. patiotemporal I anal/sis complements and adds value to t-e
traditional met-ods o( identi(/in accidents patterns in time and space )*sar/, -a((ari, ? Lev/, 2010+.
T-ere are some important (actors t-at ma/ impact t-e distriution o( tra((ic accidents, includin natural
and environmental c-aracteristics suc- as p-/sical environment )steep slope, s-arp turn+, eat-er )rain,
sno, ind, and (o+, con(iuration o( -i-a/ netors suc- as t-e locations o( access and eress
points, de(icient desin and maintenance o( -i-a/s, etc. *ll o( t-ese (actors more or less are associated
it- distinct spatial patterns as ell )Gie ? @an, 200%+.
Aurrentl/, t-ree ma'or spatiotemporal pattern anal/ses and visualiation tec-niues -ave een applied in
ve-icle cras- researc- map animation, iso!sur(ace met-od and co!map )*sar/, -a((ari, ? Lev/, 2010+.
T-e co!map met-od is use(ul (or -i-li-tin di((erences in a cras- pattern usin Msmall multiples< o(
diarams )Frunsdon, Aocoran, ? 9is, 2007+. * time period, as a t-ird dimension, is roen don into a
series o( time intervals and a spatial pattern can t-en e anal/ed and illustrated (or eac- time interval
)Hlu, Gia, ? Aaul(ield, 2011+. T-is paper ampli(ied one o( t-e visualiation tec-niues to investiate
spatiotemporal structures o( RT*s. Jirst, (or spatial anal/sis o( RT*s, t-e ernel #ensit/ 6stimation
)#6+ in a I environment is used to determinate critical areas it- -i- RT*s ris.
T-ere are a variet/ o( spatial tools developed to assist t-e understandin o( t-e c-anin eorap-ies o(
point patterns. T-e most promisin o( t-ese tools is #6. T-e #6 is one o( t-e most common and ell!
estalis-ed met-ods in identi(/in spatial patterns, and a non!parametric met-od t-at involves introducin
a s/mmetrical sur(ace over eac- point (eature, assessin t-e distance (rom t-e point to a re(erence location
ased on a mat-ematical (unction, and suseuentl/, addin t-e value o( all t-e sur(aces (or t-at re(erence
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location )Flaue ? Aelis, 2013+. T-e main ene(it o( t-is approac- lies in reconiin t-e ris spread o(
an accident )*nderson, 200"+. #6 calculates t-e densit/ o( events in a nei-our-ood around t-ose
events. #6 allos some events to ei- more -eavil/ t-an ot-ers, dependin on t-eir meanin, or to
allo one event to represent several oservations )*sar/, -a((ari, ? Lev/, 2010+.
T-e spread o( ris can e de(ined as t-e area around a de(ined cluster in -ic- t-ere is an increased
proailit/ (or an accident to -appen ased on spatial dependenc/. econdl/ / usin t-is densit/
measure, an aritrar/ spatial unit o( anal/sis can e de(ined and e -omoenous (or t-e -ole area -ic-
maes comparison and ultimatel/ a ta;onom/ possile )*nderson, 200"+.
#6 includes placin a s/mmetrical sur(ace over eac- point and t-en measurin t-e distance (rom t-e
point to a re(erence location ased on a mat-ematical (unction and t-en summin t-e value (or all t-e
sur(aces (or t-at re(erence location. T-is procedure is repeated (or successive points. T-is t-ere(ore allos
us to place a ernel over eac- oservation, and summin t-ese individual ernels ives us t-e densit/
estimate (or t-e distriution o( accident points )6. 1+ )Jot-erin-am, Frunsdon, ? A-arlton, 2000
*nderson, 200"+.
22%
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Transport and Telecommunication
Vol. 15, no. 3, 2014
6. 1
1
n
d i
f ) 3, y+ =
∑4
,
nh
2
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i =
1
h
-ere f ) 3, y+ is t-e densit/ estimate at t-e location );, /+ n is t-e numer o( oservations, - is t-e andidt-
or ernel sie, is t-e ernel (unction, and di is t-e distance eteen t-e location );, /+ and t-e location o(t-e it- oservation. T-e e((ect o( placin t-ese -umps or ernels over t-e points is to create a smoot- and
continuous sur(ace. T-e met-od is non as #6 ecause around eac- point at -ic- t-e indicator is
oserved a circular area )t-e ernel+ o( de(ined andidt- is created. T-is taes t-e value o( t-e indicator at
t-at point spread into it accordin to some appropriate (unction. ummin all o( t-ese values at all places,
includin t-ose at -ic- no incidences o( t-e indicator variale ere recorded, ives a sur(ace o( densit/
estimates )ilverman, 1"%:+.
ernel #ensit/ ma/ also e used (or calculatin t-e densit/ o( linear (eatures in t-e nei-our-ood o( eac-
output cell. * smoot-l/ curved sur(ace is conceptuall/ (itted over eac- line. Its value is iest on t-e line
and diminis-es as /ou move aa/ (rom t-e line, reac-in ero at t-e speci(ied searc- radius distance (rom
t-e line. T-e sur(ace is de(ined so t-e volume under t-e sur(ace euals t-e product o( line lent- and t-e
population (ield value. T-e densit/ at eac- output raster cell is calculated / addin t-e values o( all t-e
ernel sur(aces -ere t-e/ overla/ t-e raster cell centre )ilverman, 1"%:+.
,# Te S%&dy Are* *$d D*%*
Cetropolitan -ira located in t-e sout-est o( Iran and is t-e capital cit/ o( Jars Hrovince. *ccordin to t-e
report (rom Iranian Fureau o( tatistics )IF, 2013+, t-e population o( t-e metropolitan area is aout
1
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T*./e "# T-e distriution o( t-e intra!uran tra((ic accidents ased on t-e t/pe o( cras-
Cr*- Ty0e
D*1*2ed
I$3&red
De*%
To%*/ A''(de$%
S*re
Aar it- motorc/cle
403
2414
11
2%2%
10O
Aar it- ic/cle
1:
3:
0
52
0.2O
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Aar it- anot-er car
1"0"1
"47
"
20047
73O
Aar it- ot-er cars
"27
1:%
"
1104
4.0O
Aar -ittin a pared car
5:
23
2
%1
0.3O
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Aar -ittin a pedestrian
1%
11"%
1%
1234
5O
Aar -ittin an o'ect
1150
144
5
12""
5O
Rollover
117
:"
3
1%"
0.7O
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Cotorc/cle -ittin a pedestrian
1
:3
1
:5
0.2O
Cotorc/cle it- motorc/cle
1
:3
1
:5
0.2O
Cotorc/cle -ittin a ic/clin
5
"
0
14
0.1O
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$t-er
330
32
1
3:3
1O
Total
22115
51::
:0
27341
100O
22"
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Transport and Telecommunicati on Vol. 15, no. 3 , 2014
4# R e&/% *$d D('&(o$
T-e results o( t-is stud/ could ive an insi-t into t-e present s enario o( t-e tra((ic condition o( t-e m
etropolitan and s-os out t-e most potentiall/ acci dent prone roads in t-e district. It ould also descr ie
some caus es o( accident.
*ccordin to t-e literature o( accident anal/sis, tim e is an impo rtant (actor -ic- contriutes to road t
ra((ic acciden ts. T-e temp oral anal/sis aims to disco ver t-e relative ris pattern temporall/ and can e
us ed as prereuisite (or spatial anal/sis taretin spatial patterns in di (erent time p eriods
T-is stud/ (ocuses on ur an areas at a speci(ic time o( da/ demonstrates spatiotemporal variations in RT*s
incidents. Jiure 1 illustrates -o t-e numer o( RT*s across Cetropolitan -ira areas varied (rom 200" to
2010 t-rou -out t-e da/. T-is s-os t-at a (e RT*s occurred durin earl/ mor nin particularl/ t-e/ dipped
eteen 4 a nd : *C - en tra((ic volu me is uiet l and drivers are less lie l/ to -it anot- er car. $n t-e
ot-er -and, t-e numer o ( tra((ic acci dents sini(ic antl/ increased a(ter % *C coincidin it- t-e einnin
o( activities durin a t/pical da/. T-is is consistent it- t-e (indins o( )9e/dari et al., 2013+ t-e ti me
distriutio n o( (atal tra((ic accidents in Jars Hro vince o( Iran. T-e/ (ound t-at tra((ic a ccident
deat-s o( students, clers, orers and -ouse!eepers increased dramaticall/ at %–12 *C.
Jor t-e sp atial anal/sis o( RT*s, t-is stud/ e mplo/ed # 6 met-od to enerate maps to
deter minin RT* -otspots in -ira appl/in linear anal/sis supported / I. T-e patial *nal/st
#6 tool in 6RI
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5ig-re 1. 9ourl/ pattern s o( RT*s incid ents in -ira, 200"–2010
5ig-re %. Hatterns / da/ o( t-e ee
230
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5ig-re &. RT *s patterns / m ont- o( t-e /ear
Jiure 4 dis pla/s t-e results t-e #6 anal/sis (or RT*s durin t-e stud/ period in -ira . Lie t-e temporal
patte rns, t-e spati al patterns o( RT*s incid ents o( di((er ent causes s-o some variations acros s t-e metropo
litan reions. RT*s incide nts ere mo re (reuent in main arterie s -ere more uran activities are tain
place and c lustered in t- e areas o( uran t-at -ave -i- tra((ic v olume and provided more accessiilit/ to
ot-er road. T-ere are a ( e -otspots in donton area and some on t-e ma'or streets and roads in t-e > ort-!
estern and out-!eastern parts, o( t-e metro politan. T-is map -i-li- ts, t-e -i-est RT*s incident intensit/
is (ound in t-e >ort- !estern parts o( t-e metrop olitan. T-ese areas repre sent nei-our-oods it- lo
populatio n densities, ne er develop ments, and -i -er ualit/.
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5ig-re (. Intra!u ran tra((ic acci dents densit/ usi n 2 m andidt- o( main streets
5#
C o$'/&(o$
T-e anal/sis o( spatiote mporal distri ution o( accidents in Cetropolitan -ira, (ocuses on t-e
total
numer o( a ccidents as ell as accide nts -appened durin ni-t and da/ -ours )tempora l+ and
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accid ents in areas it- -i- tra((ic conestio n )spatial+. T- e advantaes o( suc- to dimensional -
otspot sur(ac e representations, especiall/ on intr a!uran tra((ic accidents, can provid e a more r ealistic
231
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continuous model o( accident -otspot patterns, over space and time. T-e (indins o( t-is paper proposet-at RT*s trends di((er accordin to incident t/pe and can provide important e;plorator/ anal/sis prior to
more detailed investiations includin t-e use o( conte;tual data )e.., land use, t/pe o( road+ . T-e results
o( t-is paper presumal/ -ave important implications (or RT*s prevention plannin, and RT*s
intervention policies, includin t-e identi(ication o( -otspots, -ic- eorap-icall/ de(ine acute prolem
areas. 8it-in t-ese -otspots, tra((ic and police departments could (ocus on reions t-at are statisticall/
liel/ to -ave -i-er levels o( t-e repeated road tra((ic accidents. T-is stud/ can e developed (urt-er /
investiatin t-e potential causes o( tra((ic occurrence t-rou-out t-e metropolitan area.
Re6ere$'e
*DnEr, *. )2007+ Road tra((ic accidents and sa(et/ proramme in Ture/. International 6o-rnal of
In7-ry 8ontrol and Safety Promotion, 14)2+, 11"–121.
*nderson, T.. )200"+. ernel densit/ estimation and !means clusterin to pro(ile road accident
-otspots. 2ident 2nalysis and Prevention, 41)3+, 35"–3:4.
*sar/, *., -a((ari, *. ? Lev/, P. )2010+ patial and temporal anal/ses o( structural (ire incidents and
t-eir causes * case o( Toronto, Aanada. 5ire Safety 6o-rnal, 45)1+, 44–57.
Fa-adorimon(ared, *., oori, 9., Ce-rai, @., #elpis-e-, *., 6smaili, *., ale-i, C. et al. )2013+ Trends
o( Jatal Road Tra((ic In'uries in Iran )2004–2011+. PoS 9*, %)5 e:51"%+.
Flaue , A. ? Aelis, C. )2013+ * spatial and temporal anal/sis o( c-ild pedestrian cras-es in antiao,
A-ile. 2ident 2nalysis ; Prevention, 50, 304–311.
:. Frunsdon, A., Aocoran, P. ? 9is, . )2007+ Visualisin space and time in crime patterns *
comparison o( met-ods. 8omp-ters, *nvironment and Urban Systems, 31)1+, 52–75.
AalilI, *., 6lias, C., allum, *., *lencar, A., >oueira, . )200"+ Cappin in'uries in tra((ic accident
victims a literature revie, Revie o( Latino!*merica, 6n(ermaem, 17 )1+.
Jot-erin-am, *., Frunsdon, A. ? A-arlton, C. )2000+ 0-antitative Geography: Perspetives on Spatial Data 2nalysis. ae Hulications, Ltd.
9e/dari, ., 9oseinade-, *., ari-ani, @., *r/a, 9., Co-ammad, N., -asem, C. et al. )2013+ Time
anal/sis o( (atal tra((ic accidents in Jars Hrovince o( Iran. 8hinese 6o-rnal of
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9ol!Rau, A. and c-einer, P. )2013+ eorap-ical Hatterns in Road a(et/ Literature Revie and a Aase
tud/ (rom erman/, 6uropean Pournal o( Transport and In(rastructure Researc- 13)2+, ""–122.
Ivers, R., tevenson, C., >orton, R. ? @u, P. )200%+ Road Tra((ic In'uries. International *nylopedia of
P-bli =ealth, :15–:23.
Laarde, 6. )2011+ Road Tra((ic In'uries. *nylopedia of *nvironmental =ealth, %"2–"00.
Co-ammadi, . )2013+ Road tra((ic cras- in'uries and (atalities in t-e cit/ o( erman, Iran.
International 6o-rnal of In7-ry 8ontrol and Safety Promotion, 20)2+, 1%4–1"1.
$an, ., Tar-an, A., 6ser, ., @aut, A. ? a/in, $. )2013+ patial point pattern anal/sis o( lun cancer
in an uran area. In A. 6llul, . Nlatanov, C. Rumor, ? R. Laurini )6ds.+, Urban and /egional Data
Management )pp. 77–%%+. London ARA Hress.
Hlu, A., Gia, P. ? Aaul(ield, A. )2011+ patial and temporal visualisation tec-niues (or cras- anal/sis.
2ident 2nalysis and Prevention, 43):+, 1"37–1"4:.
Hrasannaumar, V., Vi'it-, 9., A-arut-a, R., ? eet-a, >. )2011+ patio!Temporal Alusterin o( Road
*ccidents I Fased *nal/sis and *ssessment. International 8onferene: Spatial
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