Ci a ion: Fedo ko, G.; Molná , V.;
S ohmandl, J.; Ho á ho á, P.;
S nad, D.; Cech, V. Resea ch on
Using he Tecnoma ix Plan
Simula ion o Simula ion and
Visualiza ion o T a ic P ocesses a
he T a ic Node. Appl. Sci. 2022,12,
12131. h ps://doi.o g/10.3390/
app122312131
Academic Edi o : Ca la Ra aelli
Recei ed: 28 Oc obe 2022
Accep ed: 24 No embe 2022
Published: 27 No embe 2022
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applied
sciences
A icle
Resea ch on Using he Tecnoma ix Plan Simula ion o
Simula ion and Visualiza ion o T a ic P ocesses a he
T a ic Node
Gab iel Fedo ko 1,* , Vie osla Molná 2, Jan S ohmandl 3, Pe a Ho á ho á1, Da id S nad 1
and Vlas imil Cech 1
1Facul y o Mining, Ecology, P ocess Con ol and Geo echnologies, Technical Uni e si y o Košice,
Pa k Komenského 14, 040 01 Košice, Slo akia
2Facul y o Manu ac u ing Technologies, Technical Uni e si y o Košice wi h a Sea in P ešo , Baye o a 1,
080 01 P ešo , Slo akia
3Facul y o Logis ics and C isis Managemen , Tomas Ba a Uni e si y in Zlín, S uden skénám. 1532,
686 01 Uhe skéH adiš ˇe, Czech Republic
*Co espondence: [email p o ec ed]; Tel./Fax: +421-55-602-3143
Abs ac :
Simula ion so wa e Tecnoma ix Plan Simula ion was o iginally c ea ed o a modelling
and subsequen simula ion o p oduc ion and logis ics p ocesses. I s a iabili y, howe e , opens
i s use also in o he a eas such as anspo in u ban agglome a ions. Based on ha , esea ch was
implemen ed o e i y he p og am’s applica ion in u ban anspo , speci ically o isualize and
simula e a ic p ocesses a he a ic node. The pape desc ibes a me hodology which made i
possible o c ea e a simula ion p og am o a ic ligh in e sec ions, and p esen s examples o he
simula ion model applica ion. The p oposed me hodology will enable he applica ion o Tecnoma ix
Plan Simula ion o c ea e a complex simula ion model o he logis ics p ocess. I will mainly enable
o simula e he ield o p oduc ion logis ics and ci y logis ics wi hin one simula ion model.
Keywo ds: a ic node; simula ion; modelling; isualiza ion; Tecnoma ix Plan Simula ion
1. In oduc ion
Simula ion and isualiza ion o anspo p ocess a anspo nodes is o g ea impo -
ance as i p o ides a wide ange o in o ma ion on a ic and i s be e unde s anding [
1
].
Compu e simula ion is one o he main ools in anspo enginee ing nowadays. I helps
o examine a ic p ocesses in he smalles de ails, op imize hem and sea ch o new
solu ions [
2
]. Wi h he help o isualiza ion and simula ion, he s a egy o anspo
de elopmen in speci ic a eas o egions can be de ined [
3
]. A anspo nodes, simula ion
and isualiza ion enable anspo elema ics assessmen [
4
], anspo low analysis [
5
] o
a de ailed assessmen o a ic conges ions [
5
]. Va ious ypes o classic simula ion ools can
be used o hese ac i i ies such as SUMO [
3
] and PTV Vissim [
6
] o , o he modeling and
simula ion o a ic p ocesses, non- adi ional so wa e such as Ma lab [
7
] o Anylogic [
8
].
These ac s lead us o conclude ha di e en ypes o simula ion so wa e can be applied
o modeling and isualiza ion o anspo p ocesses.
Tecnoma ix Plan Simula ion is a simula ion so wa e ha is p ima ily in ended o
logis ics and p oduc ion p ocesses. I is a obus analy ical ool ha is being widely used in
scien i ic esea ch. I is mainly used o c ea e disc e e simula ed models [
9
]. I allows o
simula e a wide ange o p oduc ion p ocesses, e.g., assembly [
10
] o p oduc ion lines [
11
].
I s success ul applica ion is also possible in he ield o e gonomics [
12
]. In addi ion o i s
adi ional use, scien i ic wo ks a e being p esen ed on applica ion o his simula ion ool
in o he non- adi ional a eas, such as mining [13] o c i ical in as uc u e secu i y [14].
Tecnoma ix Plan Simula ion has a wide ange o ools ha allow analyzing di e en
anspo sys ems, including in a-company anspo , whe e AGV sys ems a e p ima ily
Appl. Sci. 2022,12, 12131. h ps://doi.o g/10.3390/app122312131 h ps://www.mdpi.com/jou nal/applsci
Appl. Sci. 2022,12, 12131 2 o 17
conce ned [
15
]. I is used as an analy ical and p edic i e ool o iden i ying p oblems
associa ed wi h, e.g., in a-company anspo [
16
]. The p og am makes i possible o assess
e iciency o anspo p ocesses and e alua e hem [17].
Tools a ailable in Tecnoma ix Plan Simula ion o anspo and anspo sys ems a e
no only in ended o a na ow ange o issues associa ed wi h in a-company and in e -
ope a ional anspo ; qui e he opposi e, as he p og am has a g ea po en ial c ea ing a
p e equisi e o i s wide use in a ious anspo sys ems, anspo elema ics and anspo
s uc u es. This ac can be p esen ed, e.g., based on he wo k o Sebes yeno a and Ku del [
18
],
who deal wi h he use o Tecnoma ix Plan Simula ion o de e mining he sho es ou e o
an ambulance ca . Howe e , his is no he only use in he ield o anspo o Tecnoma ix
p og am. Since he p og am ea u es a Sim alk so wa e ool [
19
], allowing p og amming o
unlimi ed p og am unc ionali ies, possibili ies open o a esea ch hypo hesis whe he he
Tecnoma ix Plan Simula ion can be used o c ea e mic oscopic models o anspo p ocesses
a anspo nodes. This hypo hesis is suppo ed by he ac ha he p og am is highly
a iable no only in addi ional p og amming o simula ion unc ionali ies, bu also in he a ea
o isualiza ion o simula ion models and expe imen s.
The goal o p esen ed esea ch is a esul o an e o o c ea e a simula ion model
o a complex logis ics p ocess, speci ically a model consis ing o wo pa s, he i s one
dedica ed o p oduc ion logis ics and he second one o ci y logis ics. In e ms o c ea ing a
simula ion model o bo h pa s, a su icien numbe o simula ion ools is a ailable.
Wi hin p oduc ion logis ics, he in en ion is o model e e y hing om he ma e ial
en y in o he logis ics p ocess, i s handling and he cou se o p oduc ion o c ea ion o
a inal p oduc and i s sale using oad eigh anspo , o which he Tecnoma ix Plan
Simula ion is a sui able so wa e ool.
In ci y logis ics, he aim is o esea ch he way in which eigh anspo , esul ing
om p oduc ion logis ics ac i i ies, will a ec he a ic a he anspo node, as well as i
and how ehicles anspo ing manu ac u ed p oduc s will a ec he a ic a he anspo
hub. Once again, we can conclude ha o he needs o ci y logis ics, specialized simula ion
ools o c ea e a ic models exis . Howe e , a his poin , we un in o a connec ion
p oblem o en i y ou pu s ( ehicles om he pa o p oduc ion logis ics simula ion model
o he second pa o he ci y logis ics simula ion model) in o de o ind ou and analyze
he way p oduc ion p ocesses (sales o p oduc ion) will a ec public anspo and ci y
mobili y. Fo his eason, wi hin p esen ed esea ch, a possibili y o using Tecnoma ix Plan
Simula ion p og am o simula e anspo p ocesses a he anspo node was e i ied and
a me hodological p ocedu e was p oposed o implemen i .
The a icle p esen s a d a me hodology and i s e i ica ion in he condi ions o a
eal a ic node, demons a ing he op ions o Tecnoma ix Plan Simula ion when c ea ing
a ic mic oscopic simula ion models o p ocesses aking place a a anspo hub. This
is an issue ha , om such a poin o iew, has no ye been p esen ed anywhe e in he
a ailable li e a u e. The ob ained esul s will hus ex end he po olio o a eas in which
he p og am can be used and e i y i s abili y o isualize a ic p ocesses.
2. Ma e ials and Me hods
O en, complex a ic nodes in ol ing no only d i e s bu also pedes ians and
cyclis s can igge complica ions in a ic and i s managemen . The mode n imes enable
o model and simula e such a ic nodes. The ou pu o such a simula ion, which con ains
collec ed da a om speci ic places, is an accu a e speci ica ion o a ic si ua ions. Real
sys em is being eplaced wi h a simula ion—a compu e model. I allows us o pe o m
a ious expe imen s wi h changing oads, a ic lows, a ic densi y, c ea ing pedes ian
c ossings ac oss he oads and many o he s. I can eplay complex p ocesses ha ake
hou s, days and weeks o eal ime in minu es. The esul s o such simula ions can be
compa ed be ween each o he , he eby p o iding in o ma ion needed o cons uc ion o
new oads and anspo hubs in a sho ime and wi h minimal cos . Ano he a ea o
ad an ageous applica ion o a ic modeling and simula ion is a ic conges ions.
Appl. Sci. 2022,12, 12131 3 o 17
T a ic conges ion is a complex dynamic p oblem in ol ing many complica ed and
in e ac ing elemen s. These elemen s a e ehicles, d i e beha io , oad and i s geome y,
a ic signs and o he s. In such a complex p oblem si ua ion, he use o compu e simu-
la ion can be e y e ec i e by p o iding assessmen o di e en a ic condi ions. I can
help c ea o s unde s and and analyze a ic, assess cu en issues, and p opose he bes
solu ion. Simula ion can suppo a ic managemen planning and decision-making o a
long- e m sus ainable u ban de elopmen . New solu ions and echniques can be e ec i ely
es ed in a i ual eali y en i onmen wi hou in e e ing wi h eal a ic. E ec i e a ic
managemen and con ol s a egies need up- o-da e alid simula ion es esul s. In all
cases men ioned, isualiza ion and simula ion a e playing an impo an ole.
T a ic simula ion sys ems as specialized ools used o analyze a ic conges ion ha e
played a undamen al ole in a ic model de elopmen . In he exis ing lines o esea ch,
e en -d i en o ime-d i en de elopmen o models has been conside ed along wi h he
de e minis ic o s ochas ic na u e o p ocesses. Unde speci ic condi ions, o many a ic
models, we ocused on wo possible app oaches so as o ealize e ec i e models in a single
amewo k. The heo y o a ic modeling ocused on wo main di ec ions: ying o
implemen e ec i e models and a uni ied amewo k [20].
2.1. Visualiza ion and Simula ion o T a ic P ocesses
Visualiza ion and simula ion o a ic p ocesses is a highly e ec i e app oach in
sol ing a wide ange o anspo asks and p oblems. T a ic enginee s use i o a be e
unde s anding o he esea ched p ocesses, ob aining in o ma ion and sea ching o new
solu ions. Wi h ega d o de ail, mic oscopic (Figu e 1), mesoscopic and mac oscopic
anspo models a e dis inguished.
Appl. Sci. 2022, 12, 12131 4 o 19
Figu e 1. The ma e ial weighing and eeding o ma e ial in o he con eyo .
Mic oscopic models p o ide a de ailed iew o he cou se o anspo p ocesses and
help o isualize hem. Va ious specially c ea ed simula ion ools a e used o implemen
hem. Howe e , o a ic modeling, no only special so wa e is needed. Ve y o en sim-
ula ion so wa e no p ima ily in ended o a ic modeling can be deployed as a ic
models can be c ea ed and used due o hei unc ionali ies.
Simula ion so wa e, p ima ily in ended o use in anspo , is nowadays a wide-
sp ead ool o analysis and p edic ion o a ious anspo asks and p oblems. I belongs
o a la ge g oup o simula ion ools ha a e now a ailable and being used. In mos cases,
hei use is s ic ly limi ed o anspo . On he o he hand, he e a e so wa e ools a ail-
able in he ma ke ha a e no in ended o anspo , bu due o hei o e all concep and
unc ionali ies, he ques ion a ises whe he hey can be applied in sol ing anspo p ob-
lems.
This ques ion is o impo ance since i his is he case, use s al eady owning such a
so wa e ool do no ha e o acqui e ano he simula ion ool o sol e a ic p oblems.
They can use hei p e ious expe ience and compe ences o c ea e simula ion models and
implemen a wide ange o expe imen s. The Tecnoma ix Plan Simula ion is among he
simula ion ools no p ima ily in ended o anspo , wi h he excep ion o in e -company
ones.
2.2. Tecnoma ix Plan Simula ion
Tecnoma ix Plan Simula ion was p ima ily c ea ed o p oduc ion modeling and i s
subsequen simula ion. Howe e , i is a highly a iable simula ion so wa e ha allows
ull cus omiza ion o i s applica ion in di e en a eas. Based on hese ac s, a esea ch hy-
po hesis was s ipula ed whe he he men ioned simula ion p og am can also be used in
simula ion and isualiza ion o a ic p ocesses o an u ban agglome a ion.
The esea ch aim was o e i y he use o simula ion p og am in an a ea o which i was
no c ea ed, bu can be used o unde ce ain ci cums ances. The goal was o design and
c ea e a me hodology o be used o u ban a ic simula ion and isualiza ion, and
Figu e 1. The ma e ial weighing and eeding o ma e ial in o he con eyo .
Mic oscopic models p o ide a de ailed iew o he cou se o anspo p ocesses and
help o isualize hem. Va ious specially c ea ed simula ion ools a e used o implemen
hem. Howe e , o a ic modeling, no only special so wa e is needed. Ve y o en
Appl. Sci. 2022,12, 12131 4 o 17
simula ion so wa e no p ima ily in ended o a ic modeling can be deployed as a ic
models can be c ea ed and used due o hei unc ionali ies.
Simula ion so wa e, p ima ily in ended o use in anspo , is nowadays a widesp ead
ool o analysis and p edic ion o a ious anspo asks and p oblems. I belongs o a la ge
g oup o simula ion ools ha a e now a ailable and being used. In mos cases, hei use
is s ic ly limi ed o anspo . On he o he hand, he e a e so wa e ools a ailable in he
ma ke ha a e no in ended o anspo , bu due o hei o e all concep and unc ionali ies,
he ques ion a ises whe he hey can be applied in sol ing anspo p oblems.
This ques ion is o impo ance since i his is he case, use s al eady owning such a
so wa e ool do no ha e o acqui e ano he simula ion ool o sol e a ic p oblems. They
can use hei p e ious expe ience and compe ences o c ea e simula ion models and implemen
a wide ange o expe imen s. The Tecnoma ix Plan Simula ion is among he simula ion ools
no p ima ily in ended o anspo , wi h he excep ion o in e -company ones.
2.2. Tecnoma ix Plan Simula ion
Tecnoma ix Plan Simula ion was p ima ily c ea ed o p oduc ion modeling and i s
subsequen simula ion. Howe e , i is a highly a iable simula ion so wa e ha allows
ull cus omiza ion o i s applica ion in di e en a eas. Based on hese ac s, a esea ch
hypo hesis was s ipula ed whe he he men ioned simula ion p og am can also be used in
simula ion and isualiza ion o a ic p ocesses o an u ban agglome a ion.
The esea ch aim was o e i y he use o simula ion p og am in an a ea o which i
was no c ea ed, bu can be used o unde ce ain ci cums ances. The goal was o design
and c ea e a me hodology o be used o u ban a ic simula ion and isualiza ion, and
he eby expand possible simula ion p og am’s applica ion o c ea e mic omodels ha can
be used o a ic node analysis.
2.3. Resea ch Hypo hesis
Based on he knowledge om c ea ion o simula ion models by Tecnoma ix Plan
Simula ion, a me hodology was p oposed, shown in Figu e 2.
The d a o o iginal me hodology is based on a g adual implemen a ion o indi idual
s eps, while he SimTalk so wa e is ac i ely being used o p og am missing unc ions
along wi h g aphic ools enabling he c ea ion o a disc e e a ic node mic omodel. The
p oposed me hodology is gene ally alid om he poin o iew o a ic, bu i s applica ion
is designed only o Tecnoma ix Plan Simula ion so wa e.
As pa o he me hodology, he use o exis ing blocks o c ea ion o anspo ou es
and oads is conside ed. A e wa ds, pedes ian c ossings, o e passes o unde passes o
o he a ic componen s on he ou es using he SimTalk so wa e mus be added, as his is
no a de aul ea u e o he simula ion ool.
In he nex s ep, he blocks in he lib a y o Tecnoma ix Plan Simula ion need o be
used, ep esen ing he means o anspo . Since he so wa e is p ima ily in ended only
o use in in a-company logis ics, he blocks need o be modi ied and adap ed o he new
equi emen s needed o disc e e mic o anspo models. Speci ically, blocks need o be
c ea ed in he lib a y ha ep esen indi idual means o anspo and oad use s. In his
ac i i y, ac i e use o he SimTalk is assumed, as well as g aphic edi ing ools.
In he inal phase o he p oposed me hodology, he ules o mo emen o oad use s
a he a ic node need o be de ined by ac i e p og amming as well as by unc ioning o
a ic ligh s signaling and o he ules o p ope unc ioning o he simula ion model. A
he end o his phase begins a inal g aphic edi ing o he simula ion model. Bo h 2D and
3D g aphic objec s and elemen s can be used.
Due o a possible occu ence o ul ima e ac s (as he p oposed p ocedu e is a logical
sequence o s eps, bu he simula ion p og am is no in ended o he a ea o anspo )
which could make i impossible o c ea e a simula ion model, he desc ibed me hodology
had o be e i ied.
Appl. Sci. 2022,12, 12131 5 o 17
Appl. Sci. 2022, 12, 12131 5 o 19
he eby expand possible simula ion p og am’s applica ion o c ea e mic omodels ha can
be used o a ic node analysis.
2.3. Resea ch Hypo hesis
Based on he knowledge om c ea ion o simula ion models by Tecnoma ix Plan
Simula ion, a me hodology was p oposed, shown in Figu e 2.
Figu e 2. D a me hodology o c ea ion o a ic p ocesses simula ion and isualiza ion by Tecn-
oma ix Plan Simula ion.
The d a o o iginal me hodology is based on a g adual implemen a ion o indi id-
ual s eps, while he SimTalk so wa e is ac i ely being used o p og am missing unc ions
along wi h g aphic ools enabling he c ea ion o a disc e e a ic node mic omodel. The
p oposed me hodology is gene ally alid om he poin o iew o a ic, bu i s applica-
ion is designed only o Tecnoma ix Plan Simula ion so wa e.
As pa o he me hodology, he use o exis ing blocks o c ea ion o anspo ou es
and oads is conside ed. A e wa ds, pedes ian c ossings, o e passes o unde passes o
o he a ic componen s on he ou es using he SimTalk so wa e mus be added, as his
is no a de aul ea u e o he simula ion ool.
In he nex s ep, he blocks in he lib a y o Tecnoma ix Plan Simula ion need o be
used, ep esen ing he means o anspo . Since he so wa e is p ima ily in ended only
o use in in a-company logis ics, he blocks need o be modi ied and adap ed o he new
equi emen s needed o disc e e mic o anspo models. Speci ically, blocks need o be
c ea ed in he lib a y ha ep esen indi idual means o anspo and oad use s. In his
ac i i y, ac i e use o he SimTalk is assumed, as well as g aphic edi ing ools.
In he inal phase o he p oposed me hodology, he ules o mo emen o oad use s
a he a ic node need o be de ined by ac i e p og amming as well as by unc ioning o
a ic ligh s signaling and o he ules o p ope unc ioning o he simula ion model. A
Figu e 2.
D a me hodology o c ea ion o a ic p ocesses simula ion and isualiza ion by Tecno-
ma ix Plan Simula ion.
3. Resul s
To e i y a possibili y o simula ing and isualizing a ic p ocesses by Tecnoma ix
Plan Simula ion, a speci ic in e sec ion was chosen in Figu e 3. As pa o me hodology
e i ica ion, he e o was o c ea e he mos genuine model o he anspo node wi h he
de ini ion o all ules and con ol sys ems including anspo elema ics.
Appl. Sci. 2022, 12, 12131 6 o 19
he end o his phase begins a inal g aphic edi ing o he simula ion model. Bo h 2D and
3D g aphic objec s and elemen s can be used.
Due o a possible occu ence o ul ima e ac s (as he p oposed p ocedu e is a logical
sequence o s eps, bu he simula ion p og am is no in ended o he a ea o anspo )
which could make i impossible o c ea e a simula ion model, he desc ibed me hodology
had o be e i ied.
3. Resul s
To e i y a possibili y o simula ing and isualizing a ic p ocesses by Tecnoma ix
Plan Simula ion, a speci ic in e sec ion was chosen in Figu e 3. As pa o me hodology
e i ica ion, he e o was o c ea e he mos genuine model o he anspo node wi h
he de ini ion o all ules and con ol sys ems including anspo elema ics.
Figu e 3. In e sec ion o Lud ík S oboda S ee and Ma šal Kone S ee .
3.1. C ea ion o a Simula ion Model D i ing Lanes
The i s s ep in c ea ing a simula ion model o a h ee-a m in e sec ion acco ding o
he p oposed o iginal me hodology was he implemen a ion o lanes (Figu e 4). In i , he
basic cha ac e is ics o he in e sec ion had o be aken in o accoun . I is con olled by
oad ligh signaling, which con ols no only ehicles, bu also pedes ians.
The lanes in his simula ion model we e c ea ed using blocks o iginally mean in he
p og am o connec p oduc ion p ocesses. La e on, he lanes will be made in isible o a
isual e ec (Figu e 4).
Figu e 3. In e sec ion o Lud ík S oboda S ee and Ma šal Kone S ee .
3.1. C ea ion o a Simula ion Model D i ing Lanes
The i s s ep in c ea ing a simula ion model o a h ee-a m in e sec ion acco ding o
he p oposed o iginal me hodology was he implemen a ion o lanes (Figu e 4). In i , he

Appl. Sci. 2022,12, 12131 6 o 17
basic cha ac e is ics o he in e sec ion had o be aken in o accoun . I is con olled by oad
ligh signaling, which con ols no only ehicles, bu also pedes ians.
The lanes in his simula ion model we e c ea ed using blocks o iginally mean in he
p og am o connec p oduc ion p ocesses. La e on, he lanes will be made in isible o a
isual e ec (Figu e 4).
Appl. Sci. 2022, 12, 12131 6 o 19
he end o his phase begins a inal g aphic edi ing o he simula ion model. Bo h 2D and
3D g aphic objec s and elemen s can be used.
Due o a possible occu ence o ul ima e ac s (as he p oposed p ocedu e is a logical
sequence o s eps, bu he simula ion p og am is no in ended o he a ea o anspo )
which could make i impossible o c ea e a simula ion model, he desc ibed me hodology
had o be e i ied.
3. Resul s
To e i y a possibili y o simula ing and isualizing a ic p ocesses by Tecnoma ix
Plan Simula ion, a speci ic in e sec ion was chosen in Figu e 3. As pa o me hodology
e i ica ion, he e o was o c ea e he mos genuine model o he anspo node wi h
he de ini ion o all ules and con ol sys ems including anspo elema ics.
Figu e 3. In e sec ion o Lud ík S oboda S ee and Ma šal Kone S ee .
3.1. C ea ion o a Simula ion Model D i ing Lanes
The i s s ep in c ea ing a simula ion model o a h ee-a m in e sec ion acco ding o
he p oposed o iginal me hodology was he implemen a ion o lanes (Figu e 4). In i , he
basic cha ac e is ics o he in e sec ion had o be aken in o accoun . I is con olled by
oad ligh signaling, which con ols no only ehicles, bu also pedes ians.
The lanes in his simula ion model we e c ea ed using blocks o iginally mean in he
p og am o connec p oduc ion p ocesses. La e on, he lanes will be made in isible o a
isual e ec (Figu e 4).
Figu e 4. C ea ion o lanes in a simula ed in e sec ion.
3.2. C ea ion o Objec Lib a y
P og am’s lib a y se es as a ile ha g oups in o ma ion lows, ma e ial lows, e-
sou ces, use in e ace, ools and, las bu no leas , use objec s. I makes he p og amme ’s
wo k easie by o e ing p e-de ined a ibu es needed when c ea ing a model. When c e-
a ing he model, only he T anspo e objec was used (Figu e 5). The objec se es as a
ehicle mo ing along designa ed ou es. Six anspo e s we e c ea ed, h ee o which,
named AUTA_11, AUTA_22 and AUTA_33, ep esen passenge ca s. The anspo e
AUTOBUS_15 is c ea ed o bus line 15. A dense in e al is se o AUTOBUS_, as his
anspo e ep esen s he emaining bus lines passing he in e sec ion, i.e., line 17, 54, 55,
71, 72. The las anspo e used in he model, Pedes ians, shows he pedes ians c ossing
he c ossings and is g aphically dis inguished om passenge ca s and buses.
In Figu e 6, Pa and Con aine objec s can be seen. Howe e , hese objec s we e no
used in he simula ion model ( hey a e used o c ea e p oduc ion simula ion models). The
Con aine ep esen s a handling uni and he Pa ep esen s an objec ha can be placed
on he Con aine o T anspo e .
3.3. Including Vehicles in o he Model
P og ams di ec ly in ended o modeling and a ic simula ion ha e andom ehicle
gene a ion included. They gene a e ehicles o di e en sizes, colo s and speeds. Howe e ,
in case o modeling he in e sec ion in Tecnoma ix Plan Simula ion, he ehicles a e
gene a ed by using inpu s.
Ano he a ibu e en e ed a e he inpu and be o e he lane is called Bu e . I s job
is o hold back and di ide ehicles be ween lanes as needed. The e a e se e al ways o
dis ibu e ehicles in he se ings, bu o his model, a andom and pe cen age s a egy
was chosen.
In case o es ic ing ehicles en e ing he ce ain lane o hei guidance, he me hod
c ea ed in SimTalk p og am was used.
A e y impo an ope a ion is a co ec alignmen no only o inpu s and ou pu s,
bu also o he lanes hemsel es in he model. I o en happens ha an inco ec objec s
alignmen pa alyzes he whole model. The connec o s as shown in Figu e 6can also be
hidden in se ings.
Appl. Sci. 2022,12, 12131 7 o 17
Appl. Sci. 2022, 12, 12131 7 o 19
Figu e 4. C ea ion o lanes in a simula ed in e sec ion.
3.2. C ea ion o Objec Lib a y
P og am’s lib a y se es as a ile ha g oups in o ma ion lows, ma e ial lows, e-
sou ces, use in e ace, ools and, las bu no leas , use objec s. I makes he p og am-
me ’s wo k easie by o e ing p e-de ined a ibu es needed when c ea ing a model. When
c ea ing he model, only he T anspo e objec was used (Figu e 5). The objec se es as
a ehicle mo ing along designa ed ou es. Six anspo e s we e c ea ed, h ee o which,
named AUTA_11, AUTA_22 and AUTA_33, ep esen passenge ca s. The anspo e
AUTOBUS_15 is c ea ed o bus line 15. A dense in e al is se o AUTOBUS_, as his
anspo e ep esen s he emaining bus lines passing he in e sec ion, i.e., line 17, 54, 55,
71, 72. The las anspo e used in he model, Pedes ians, shows he pedes ians c ossing
he c ossings and is g aphically dis inguished om passenge ca s and buses.
Figu e 5. Example o a lib a y in Tecnoma ix Plan Simula ion.
In Figu e 6, Pa and Con aine objec s can be seen. Howe e , hese objec s we e no
used in he simula ion model ( hey a e used o c ea e p oduc ion simula ion models). The
Con aine ep esen s a handling uni and he Pa ep esen s an objec ha can be placed
on he Con aine o T anspo e .
Figu e 5. Example o a lib a y in Tecnoma ix Plan Simula ion.
Appl. Sci. 2022, 12, 12131 7 o 19
Figu e 4. C ea ion o lanes in a simula ed in e sec ion.
3.2. C ea ion o Objec Lib a y
P og am’s lib a y se es as a ile ha g oups in o ma ion lows, ma e ial lows, e-
sou ces, use in e ace, ools and, las bu no leas , use objec s. I makes he p og am-
me ’s wo k easie by o e ing p e-de ined a ibu es needed when c ea ing a model. When
c ea ing he model, only he T anspo e objec was used (Figu e 5). The objec se es as
a ehicle mo ing along designa ed ou es. Six anspo e s we e c ea ed, h ee o which,
named AUTA_11, AUTA_22 and AUTA_33, ep esen passenge ca s. The anspo e
AUTOBUS_15 is c ea ed o bus line 15. A dense in e al is se o AUTOBUS_, as his
anspo e ep esen s he emaining bus lines passing he in e sec ion, i.e., line 17, 54, 55,
71, 72. The las anspo e used in he model, Pedes ians, shows he pedes ians c ossing
he c ossings and is g aphically dis inguished om passenge ca s and buses.
Figu e 5. Example o a lib a y in Tecnoma ix Plan Simula ion.
In Figu e 6, Pa and Con aine objec s can be seen. Howe e , hese objec s we e no
used in he simula ion model ( hey a e used o c ea e p oduc ion simula ion models). The
Con aine ep esen s a handling uni and he Pa ep esen s an objec ha can be placed
on he Con aine o T anspo e .
Figu e 6. Objec s alignmen ia connec o s.
3.4. Se ing o Vehicle and Pedes ian G aphics
The anspo e in he lib a y, he main pa o he model, is displayed in ec o
g aphics in he basic se ing. The basic colo combina ion o he anspo e is a g ay
ec angle amed in o ange. Fo he anspo e s o di e , hei colo can be changed and
combined in di e en ways. The anspo e ec o g aphics a e shown in Figu e 7.
Tecnoma ix Plan Simula ion, a e u ning o ec o g aphics, o e s se e al al e na-
i es o anspo e displaying. I o e s, o example, an abo e iew o he anspo e , he
connec o , bu also he wo ke . The p og am also ea u es a unc ion o adding you own
anspo e design. G aphic ep esen a ion o mo ing objec s in he model is needed no
only isually, bu also o he o e all imp ession o he simula ion.
3.5. C ea ion o Road Ligh Signaling
Ligh signaling de e mines ehicles p io i y acco ding o a p e-de ined cycle ha
con ols i . Each ligh signal a he in e sec ion has i s own cycle, when STOP, WAIT and
GO ligh signals al e na e. I is e y impo an o consis en ly adjus he cycle o all ligh
signals o a oid collisions in he in e sec ion.
Appl. Sci. 2022,12, 12131 8 o 17
Appl. Sci. 2022, 12, 12131 8 o 19
Figu e 6. Objec s alignmen ia connec o s.
3.3. Including Vehicles in o he Model
P og ams di ec ly in ended o modeling and a ic simula ion ha e andom ehicle
gene a ion included. They gene a e ehicles o di e en sizes, colo s and speeds. How-
e e , in case o modeling he in e sec ion in Tecnoma ix Plan Simula ion, he ehicles a e
gene a ed by using inpu s.
Ano he a ibu e en e ed a e he inpu and be o e he lane is called Bu e . I s job
is o hold back and di ide ehicles be ween lanes as needed. The e a e se e al ways o
dis ibu e ehicles in he se ings, bu o his model, a andom and pe cen age s a egy
was chosen.
In case o es ic ing ehicles en e ing he ce ain lane o hei guidance, he me hod
c ea ed in SimTalk p og am was used.
A e y impo an ope a ion is a co ec alignmen no only o inpu s and ou pu s, bu
also o he lanes hemsel es in he model. I o en happens ha an inco ec objec s align-
men pa alyzes he whole model. The connec o s as shown in Figu e 6 can also be hidden
in se ings.
3.4. Se ing o Vehicle and Pedes ian G aphics
The anspo e in he lib a y, he main pa o he model, is displayed in ec o
g aphics in he basic se ing. The basic colo combina ion o he anspo e is a g ay ec-
angle amed in o ange. Fo he anspo e s o di e , hei colo can be changed and
combined in di e en ways. The anspo e ec o g aphics a e shown in Figu e 7.
Figu e 7. Vec o ep esen a ion o he anspo e s.
Tecnoma ix Plan Simula ion, a e u ning o ec o g aphics, o e s se e al al e na-
i es o anspo e displaying. I o e s, o example, an abo e iew o he anspo e , he
connec o , bu also he wo ke . The p og am also ea u es a unc ion o adding you own
anspo e design. G aphic ep esen a ion o mo ing objec s in he model is needed no
only isually, bu also o he o e all imp ession o he simula ion.
Figu e 7. Vec o ep esen a ion o he anspo e s.
In p og ams simula ing only a ic, he p io i y a he in e sec ion can be se using
p e e ences o he a o emen ioned TLS. The p og ams o e a module enabling se ing
o signaling and i s cycle wi h simple mo es. The e a e se e al op ions o he ways o
p og am he ligh signaling. The simples me hod was chosen o his model including he
a ibu es S a ion, Gene a o , a me hod–Me hod and a a iable–Va iable.
An a ibu e om he lib a y called S a ion was placed in he model and enamed o
Sema o _1. This Sema o _1 was, h ough Edi Icons op ion, g aphically modi ied in h ee
phases. The phases we e named phase 1–RED, phase 2–ORANGE, phase 3–GREEN.
P ope naming o each elemen is e y impo an when w i ing a sou ce code. Addi-
ional se ings in his a ibu e we e no equi ed. When en e ing addi ional ligh signals
in o he model, he i s c ea ed objec was used, which was hen copied. I s se ings ha e
no changed.
Ano he elemen om he lib a y needed o c ea e ligh signaling is he a o emen ioned
Gene a o . I was enamed o Gen_Sema o _1, hen se acco ding o a colo gene a ion
in e al. Each semapho e has i s own gene a o , which is subsequen ly e e ed o by a
me hod–Me hod elemen . The me hod was named Me _Sema o _1 (Figu e 8) and was also
unique o each ligh signaling, de ining he unc ionali y o Sema o _1 a ibu e. This is
whe e he p inciple— he b ain o he en i e ligh signaling—is embedded. I indica es ha
i he signaling s a us is equal o 1, he colo o Sema o _1 should change o ed. I i s s a e
is se o 2, i should change o o ange, and when i is se o 3, o g een. S a e 4 was added
o a epea ing cycle which includes o ange colo be ween he g een and ed signals. In
his me hod, he Gen_Sema o _1 in e al is included, ollowed by he nex signal.
The las and e y impo an elemen in he c ea ion o oad ligh signaling by Tec-
noma ix Plan Simula ion is he de ini ion o ou Va iables. These a iables a e used o
o e all se ing o he ligh signaling, i.e., i s cycle. The a iable S a _Sema o _1 de ines
he ini ial s a e o signaling. Tha is, i S a _Sema o _1 = 1, he a ic ligh u ns ed when
he simula ion s a s. I S a _Sema o _1 = 2, he semapho e displays an o ange signal, i
S a _Sema o _1 = 3, he semapho e u ns g een. S a _Sema o _1 = 4 shows he o ange colo
on he ligh signaling.
Appl. Sci. 2022,12, 12131 9 o 17
Appl. Sci. 2022, 12, 12131 10 o 19
Figu e 8. Road ligh signaling me hod o ehicles and de ining TLS a iables o ehicles.
As pa o hypo hesis e i ica ion, he e a e a o al o eigh independen ligh signals
in he model, wo o which a e signals o con ol pedes ians a he c ossing. Tecnoma ix
Plan Simula ion use only wo ks wi h he las s ep when se ing up he a ic ligh s in
he modeled in e sec ion. As needed, TLS cycle can be a ied, hus a ic si ua ion in he
in e sec ion can be a ec ed.
O he ype o ligh signaling used in he model is signaling a he pedes ian c ossing.
I is modeled simila ly o TLS o a ehicle con ol. The S a ion a ibu e is enamed o
Sema o _7 and also by Edi Icons g aphically modi ied in o wo phases, phase 1: RED and
phase 2: GREEN
Simila o he p e ious se up, wo a ibu es we e used om he lib a y, namely
Me hod and Gene a o . A me hod was en e ed in he gene a o ha signals o he S a ion
a ibu e (Sema o _7) o change i s g aphics. Figu e 9 shows he pedes ian c ossing
me hod.
Figu e 9. Me hod o oad ligh signaling o pedes ians and de ining TLS a iables o pedes ians.
This me hod indica es: i he s a e o he a iable S a _Sema o _7 = 1, he signal
g aphic should be changed o ed and numbe 1 added o i . I he s a e o he a iable
S a _Sema o _7 = 2, he a ibu e g aphic should be changed o g een and he a iable se
o numbe 1.
Figu e 8. Road ligh signaling me hod o ehicles and de ining TLS a iables o ehicles.
The o he h ee a iables (Figu e 8) a e used o se he ligh signaling cycle. The
Red_Sema o _1 a iable is ese ed o se ing he STOP signal ime. In his case, i is
20 s
in his posi ion. The hi d a iable named O ange_Sema o _1 is in ended o he WAIT
signal and las s o 5 s. The las a iable is G een_Sema o _1, which is ma ked wi h a GO
signal and las s o 40 s.
As pa o hypo hesis e i ica ion, he e a e a o al o eigh independen ligh signals
in he model, wo o which a e signals o con ol pedes ians a he c ossing. Tecnoma ix
Plan Simula ion use only wo ks wi h he las s ep when se ing up he a ic ligh s in
he modeled in e sec ion. As needed, TLS cycle can be a ied, hus a ic si ua ion in he
in e sec ion can be a ec ed.
O he ype o ligh signaling used in he model is signaling a he pedes ian c ossing.
I is modeled simila ly o TLS o a ehicle con ol. The S a ion a ibu e is enamed o
Sema o _7 and also by Edi Icons g aphically modi ied in o wo phases, phase 1: RED and
phase 2: GREEN.
Simila o he p e ious se up, wo a ibu es we e used om he lib a y, namely Me hod
and Gene a o . A me hod was en e ed in he gene a o ha signals o he S a ion a ibu e
(Sema o _7) o change i s g aphics. Figu e 9shows he pedes ian c ossing me hod.
Appl. Sci. 2022, 12, 12131 10 o 19
Figu e 8. Road ligh signaling me hod o ehicles and de ining TLS a iables o ehicles.
As pa o hypo hesis e i ica ion, he e a e a o al o eigh independen ligh signals
in he model, wo o which a e signals o con ol pedes ians a he c ossing. Tecnoma ix
Plan Simula ion use only wo ks wi h he las s ep when se ing up he a ic ligh s in
he modeled in e sec ion. As needed, TLS cycle can be a ied, hus a ic si ua ion in he
in e sec ion can be a ec ed.
O he ype o ligh signaling used in he model is signaling a he pedes ian c ossing.
I is modeled simila ly o TLS o a ehicle con ol. The S a ion a ibu e is enamed o
Sema o _7 and also by Edi Icons g aphically modi ied in o wo phases, phase 1: RED and
phase 2: GREEN
Simila o he p e ious se up, wo a ibu es we e used om he lib a y, namely
Me hod and Gene a o . A me hod was en e ed in he gene a o ha signals o he S a ion
a ibu e (Sema o _7) o change i s g aphics. Figu e 9 shows he pedes ian c ossing
me hod.
Figu e 9. Me hod o oad ligh signaling o pedes ians and de ining TLS a iables o pedes ians.
This me hod indica es: i he s a e o he a iable S a _Sema o _7 = 1, he signal
g aphic should be changed o ed and numbe 1 added o i . I he s a e o he a iable
S a _Sema o _7 = 2, he a ibu e g aphic should be changed o g een and he a iable se
o numbe 1.
Figu e 9.
Me hod o oad ligh signaling o pedes ians and de ining TLS a iables o pedes ians.
Appl. Sci. 2022,12, 12131 16 o 17
e iciency a a a ic node o nodes. The esea ch can mean a s a ing poin o longe - e m
esea ch and a subjec o u he esea ch pu poses de o ed o he impac o indus ial
p oduc ion and p oduc ion in mic o-mobili y and sus ainable ci ies.
In conclusion, we can s a e ha Tecnoma ix Plan Simula ion enables a ull-scale
c ea ion o mic oscopic a ic models. I is sui able o a ic modeling and simula ion,
and allows o su icien ly isualize all ypes o a ic p ocesses.
Au ho Con ibu ions:
Concep ualiza ion, G.F.; me hodology, P.H. and V.M.; in es iga ion, D.S. and
J.S.; da a analysis, G.F. and D.S.; w i ing—o iginal d a p epa a ion, V.M. and V.C.; w i ing— e iew
and edi ing, P.H and J.S. All au ho s ha e ead and ag eed o he published e sion o he manusc ip .
Funding:
This wo k is a pa o hese p ojec s VEGA 1/0101/22, VEGA 1/0600/20, KEGA 005TUKE-
4/2022, KEGA 018TUKE-4/2022, APVV-21-0195, ITMS: 313011T567, IGA/FLK ˇ
R/2022/001 and
RVO/FLK ˇ
R/2022/03.
Ins i u ional Re iew Boa d S a emen : No applicable.
In o med Consen S a emen : No applicable.
Con lic s o In e es : The au ho s decla e no con lic o in e es .
Re e ences
1.
Zhao, Y.; Wang, X.; Li, H.; Zhu, T. S udy on Simula ion Me hod o In e sec ion Hyb id T a ic Flow. In P oceedings o he
2nd Con e ence on Logis ics, In o ma ics and Se ice Science (Liss 2012), Beijing, China, 12–15 July 2012; Zhang, Z., Zhang, J.,
Zhang, R., Eds.; Sp inge : Be lin/Heidelbe g, Ge many, 2013; Volumes 1–2, pp. 441–446.
2.
K au e , W.; Mans e en, D.; Schwab, T. T a ic simula ion o he de elopmen o a ic managemen sys ems. In T a ic and
Mobili y: Simula ion-Economics-En i onmen ; B ilon, W., Hube , F., Sch eckenbe g, M., Wallen owi z, H., Eds.; Sp inge : Be lin,
Ge many, 1999; pp. 193–204.
3.
Song, H.; Min, O. S a is ical T a ic Gene a ion Me hods o U ban T a ic Simula ion. In P oceedings o he 20 h In e na ional
Con e ence on Ad anced Communica ion Technology (Icac ), Chuncheon, Republic o Ko ea, 11–14 Feb ua y 2018; pp. 247–250.
4.
Qiao, J.; Xuan, H.Y.; Li, L. Simula ion based analysis o he capaci y o signalized in e sec ion. In P oceedings o he 2005 In e na-
ional Con e ence on Managemen Science and Enginee ing Managemen (12 h), Incheon, Republic o Ko ea,
20–21 July 2005
;
Lan, H., Ed.; Sp inge : Be lin, Ge many, 2005; Volumes 1–3, pp. 2505–2510.
5.
He, G.G.; Ma, S.F.; Wang, G.Z. A mic oscopic simula ion sys em o a ic low wi h unce ain y. In T a ic and T anspo a ion
S udies; Wang, K.C.P., Kiao, G., Ji, J., Eds.; Ame ican Socie y o Ci il Enginee s: Res on, VA, USA, 2000; pp. 636–641.
6.
Ramadhan, S.A.; Joelian o, E.; Su a o, H.Y. Simula ion o T a ic Con ol Using Vissim-COM In e ace. In e ne wo k Indones
2019
,
11, 55–61.
7.
Te aman i, T.; Va ga, I. De elopmen o oad a ic con ol by using in eg a ed VISSIM-MATLAB simula ion en i onmen .
Pe iod. Poly ech. Eng. 2012,56, 43–49. [C ossRe ]
8.
Me ku ye a, G.; Bolshako s, V. Vehicle Schedule Simula ion wi h AnyLogic. In P oceedings o he 12 h In e na ional Con e ence
on Compu e Modelling and Simula ion (UKSIM), Camb idge, UK, 24–26 Ma ch 2010; pp. 169–174.
9.
May , A.; Lechle , T.; Donhause , T.; Me zne , M.; Schae e , E.; Fische , E.; F anke, J. Ad ances in ene gy- ela ed plan simula ion
by conside ing load and empe a u e p o iles in disc e e e en simula ion. In P oceedings o he 52nd Ci p Con e ence on
Manu ac u ing Sys ems (CMS), Ljubljana, Slo enia, 12–14 June 2019; Bu ala, P., Go eka , E., V abic, R., Eds.; Else ie : Ams e dam,
The Ne he lands, 2019; Volume 81, pp. 1325–1330.
10.
Iskanda o , M.; Khisamu dino , R. Simula ion as a ool o suppo ing assembly sys ems. In P oceedings o he In e na ional
Scien i ic-Technical Con e ence on Inno a i e Enginee ing Technologies, Equipmen and Ma e ials 2018 (ISTC-IETEM-2018),
Kazan, Russia, 5–7 Decembe 2019; Volume 570.
11.
Hongxian, L.; Hua, L. The simula ion o he ope a ion o he p oduc ion line a s amping wo kshop based on Tecnoma ix. In
P oceedings o he 14 h In e na ional Con e ence on Indus ial Enginee ing and Enginee ing Managemen , Volume a and b:
Building Co e Compe encies Th ough IE&EM, Tianjin, China, 20-22 Oc obe 2007; Qi, E., Ed.; 2007; pp. 274–278.
12.
Ho anec, M.; Ko ba, P.; Solc, M. Tecnoma ix o success ul applica ion in he a ea o simula ion manu ac u ing and e gonomics.
In P oceedings o he In o ma ics, Geoin o ma ics and Remo e Sensing, Volume I (SGEM 2015), Albena, Bulga ia,
18–24 June 2015
;
pp. 347–352.
13.
Ne adilo a, H.; Lasko sky, V. The usage o Tecnoma ix plan simula ion o simula ion o mining ail anspo . In P oceedings
o he 16 h In e na ional Mul idisciplina y Scien i ic Con e ence SGEM2016, Albena, Bulga ia, 30 June–6 July 2016; Volume 2,
pp. 929–934.
14.
Hu s , W.; Me ab i, M.; Fe gus, P. Beha iou analysis echniques o suppo ing c i ical in as uc u e secu i y.
In . J. C i . In as uc .
2014,10, 267–287. [C ossRe ]

Appl. Sci. 2022,12, 12131 17 o 17
15.
Ne adilo a, H.; Fedo ko, G.; Bo soso a, V. Modelling o in a plan anspo a ion sys em using AGV. In P oceedings o he Thi d
In e na ional Con e ence on T a ic and T anspo Enginee ing (ICTTE), Belg ade, Se bia, 29–30 No embe 2012;
Coko ilo, O., Ed.
;
Scien i ic Resea ch Cen e L d.: Belg ade, Se bia, 2016; pp. 971–979.
16.
Fedo ko, G.; Molna , V.; Honus, S.; Ne adilo a, H.; Kamp , R. The applica ion o simula ion model o a milk un o iden i y he
occu ence o ailu es. In . J. Simul. Model. 2018,17, 444–457. [C ossRe ] [PubMed]
17.
Fedo ko, G.; Vasil, M.; Ba oso a, M. Use o simula ion model o measu emen o MilkRun sys em pe o mance. Open Eng.
2019
,
9, 600–605. [C ossRe ]
18.
Sebes yeno a, J.; Ku del, P. Ambulance Ca Logis ics using Sho es Pa h Achie emen T ee in Plan Simula ion. In P oceedings
o he 3 d In e na ional Con e ence on Compu e -Human In e ac ion Resea ch and Applica ions (CHIRA), Vienna, Aus ia,
20–21 Sep embe 2019; pp. 214–220.
19.
P ei e , D.; Val ano, J.; Ge s laue , A. SimConnec and SimTalk o dis ibu ed cybe -physical sys em simula ion. Simul.-T ans.
Soc. Model. Simul. In . 2013,89, 1254–1271. [C ossRe ]
20.
Valen e, E.; A am, C.; Machado, J.; As ilean, A. An Inno a i e App oach o Modelling U ban Road T a ic Using Timed
Au oma a and Fo mal Me hods. J. Ad . T ansp. 2018,2018, 6269526. [C ossRe ]
21.
Ba celó, J. Fundamen als o T a ic Simula ion (In e na ional Se ies in Ope a ions Resea ch & Managemen Science; Ba celó, J., Ed.;
Sp inge Science+Business Media: New Yo k, Ny, USA, 2010; ISBN 978-1-4419-6141-9.