AI-based simula ion model o
op imal placemen o mic o-
hubs and ca go bike pick-up
s a ions
Deli e able 2.3
Ve sion 2.0
P ojec i le:
Fos e ing sus ainable consume beha iou wi h inclusi e
bicycle logis ics in as uc u e in u ban ou ski s
P ojec ac onym:
SuCoLo
P ojec du a ion:
01/2024 – 06/2026
P ojec numbe :
F-DUT-2022-0007
Wo k package/Task:
WP2 / T2.3
P ojec websi e:
h ps://sucolo.eu/
Au ho s:
Benjamin Gauni z, Sil ia To es Landa e de, Viola Süß (ULEI)
This p ojec has been unded by he Aus ian Resea ch P omo ion Agency (FFG), Minis y o
En e p ises and Made in I aly (MIMIT), he Fede al Minis y o Resea ch, Technology and Space in
Ge many (BMFTR) and he Swedish unding agency (Vinno a) unde he D i ing U ban T ansi ions
Pa ne ship, which has been co- unded by he Eu opean Union unde g an ag eemen no. 905465.
D2.3 AI-based simula ion model o op imal placemen o mic o-hubs and ca go bike pick-up s a ions SuCoLo
2
Documen e sions
Ve sion
Da e
Changes
Au ho s
V0.1
14.01.2025
Ini ial documen
V. Süß (ULEI)
V0.2
05.03.2025
Documen a ion Simula ion Model
V. Süß (ULEI)
V0.3
16.04.2025
Documen a ion Simula ion Model
V. Süß (ULEI)
V0.4
25.04.2025
Documen a ion Simula ion Model
V. Süß (ULEI)
V0.5
28.04.2025
Documen e isions & inaliza ion
S. To es Landa e de, B.
Gauni z (ULEI)
V0.6
30.04.2025
Re ision
V. Süß (ULEI)
V0.7
12.06.2025
P oo eading
M. Thelen (SRFG)
V1.0
04.07.2025
Final d a
V. Süß (ULEI), M. Thelen
(SRFG)
V2.0
10.10.2025
Upda es Implemen ed, 2nd App Ve sion
V. Süß (ULEI)
Lis o abb e ia ions
AI
A i icial In elligence
D
Deli e able
ETL
Ex ac , T ans o m, Load
FLP
Facili y Loca ion P oblem
GIS
Geog aphic In o ma ion Sys em
GUI
G aphical Use In e ace
LIS
Leipzig In o ma ion Sys em
ML
Machine Lea ning
OSM
Open S ee Map
POI
Poin o In e es
T
Task
D2.3 AI-based simula ion model o op imal placemen o mic o-hubs and ca go bike pick-up s a ions SuCoLo
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Table o con en s
Adminis a i e in o ma ion ..................................................................................................... 5
Pu pose o he documen ...................................................................................................... 6
Execu i e Summa y .............................................................................................................. 6
1. Mo i a ion and backg ound ............................................................................................ 7
2. P oblem desc ip ion and model o mula ion .................................................................... 7
2.1. Model assump ions, da a and pa ame e s o Leipzig ................................................. 8
2.2. Inpu da a o Leipzig .................................................................................................13
2.3. Inpu da a o Me ano .................................................................................................13
3. Simula ion Model ...........................................................................................................14
3.1. Da a p epa a ion ........................................................................................................14
3.2. Model F amewo k ......................................................................................................15
4. Use in e ace o he “Loca ion Finde App” ...................................................................16
4.1. Model E alua ion and u he implemen a ion .......................................................21
4.2. Case S udy in Ge many, Leipzig ...........................................................................21
5. Discussion and u he wo k ..........................................................................................22
Re e ences ...........................................................................................................................23
D2.3 AI-based simula ion model o op imal placemen o mic o-hubs and ca go bike pick-up s a ions SuCoLo
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Lis o Tables
Table 1 Example o Digi al Pe sonas o Model Use .............................................................. 9
Table 2 Use s o ies o bike cou ie company use s o he app ...........................................11
Table 3 Lis o po en ial Fea u es .........................................................................................12
Table 4 Inpu Da a om LIS (5) ............................................................................................13
Table 5 GUI unc ions ...........................................................................................................18
Lis o Figu es
Figu e 1 Th ee pe sonas based on a ge g oups .................................................................. 8
Figu e 2 Simula ion Model F amewo k .................................................................................15
Figu e 3 Simula ion model amewo k ..................................................................................16
Figu e 4 Sc eensho o he app’s s a sc een ......................................................................16
Figu e 5 Demons a ion o he simula ion model esul s based on se p e e ences ...............17
Figu e 6 Sc eensho o he app cen ed in Leipzig ................................................................21
D2.3 AI-based simula ion model o op imal placemen o mic o-hubs and ca go bike pick-up s a ions SuCoLo
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Adminis a i e in o ma ion
Basic in o ma ion on he SuCoLo p ojec and his deli e able:
P ojec i le
SuCoLo: Fos e ing sus ainable consume beha iou wi h inclusi e
bicycle logis ics in as uc u e in u ban ou ski s
P ojec
coo dina o
Salzbu g Resea ch Fo schungsgesellscha mbH (SRFG),
Salzbu g, Aus ia; p ojec coo dina o : Michael Thelen
P ojec pa ne s
Independen L. ONLUS (IND), I aly
Sus ainabili y InnoCen e (SIC), Sweden
VIABIRDS Technologies GmbH (VIA), Aus ia
Uni e si ä Leipzig (ULEI), Ge many
Süd i ole T anspo s uk u en AG – G een Mobili y Depa men
(STA), I aly
Funding
DUT Call 2022 – Eu opean Commission unde he Ho izon
Eu ope Pa ne ship scheme
Funding is being p o ided by he Aus ian Resea ch P omo ion
Agency (FFG), Minis y o En e p ises and Made in I aly (MIMIT),
he he Fede al Minis y o Resea ch, Technology and Space in
Ge many (BMFTR), and he Swedish unding agency (Vinno a)
P ojec n .
F-DUT-2022-0007
Du a ion
01/2024 – 06/2026
Websi e
h ps://sucolo.eu/
Deli e able n .
D2.3
Deli e able i le
AI-based simula ion model o op imal placemen o mic o-hubs and
ca go bike pick-up s a ions
Au ho s
Benjamin Gauni z, Sil ia To es Landa e de, Viola Süß (ULEI)
Ve sion & s a us
Ve sion 2.0
Da e
10.10.2025
D2.3 AI-based simula ion model o op imal placemen o mic o-hubs and ca go bike pick-up s a ions SuCoLo
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Pu pose o he documen
This documen explains he indings om Task 2.3 wi h he aim o c ea e an AI-based
simula ion model o he op imal placemen o mic o-hubs and ca go bike pick-up s a ions as
a case s udy in he ci y o Leipzig, Ge many. The objec i e o his ask is o use a ailable open
da a (see da a ca alogue om Deli e able 2.2) o de elop his model and simula e he bes
possible loca ion o mic o-hubs and s a iona y ca go bike pick-up s a ions. Rega ding he
challenges delinea ed in Deli e able 2.1 Re iew o challenges o sus ainable goods logis ics
and deli e y solu ions in u ban ou ski s, he p oposed loca ions conside inclusi i y, ba ie -
ee and social aspec s. Al hough he simula ion model is ained p ima ily om da a om
Leipzig, i would s ill be able o be ex ended o use in municipali ies ou side o hese
geog aphic a eas. Addi ionally, in Task 2.4, a so wa e p o o ype o bike cou ie s o deli e y
scheduling and ou ing is de eloped and can be used as a supplemen o a holis ic logis ics
concep o ou ski s. The model will be u he e ined and de eloped du ing he pilo p ojec
phase. A u he ci y, Me ano, I aly is included in he model.
Execu i e Summa y
This deli e able ou lines he backg ound and de elopmen o a simula ion model ha iden i ies
op imal loca ions o pick-up s a ions o pa cels, ca go bike en als and mic o-hubs in
subu ban o ou ski a eas. These a o emen ioned s a ions a e designed o imp o e he
e iciency o las -mile logis ics by in eg a ing communi y aspec s and deli e y demands. The
ool p ima ily a ge s u ban deli e y companies, p omo ing no only ope a ional e iciency, bu
also he con ex -speci ic needs o ou ski esiden s. The simula ion model akes he o m as
an app and is based on indings om a ci izen su ey in he Lü zschena-S ahmeln dis ic in
Leipzig, Ge many conduc ed in 2025. Resul ing om his, h ee pe sonas and use s o ies
channeled he eal-wo ld equi emen s o he model. In e im esul s show ha u he e ining
o he model is necessi a ed, and u he i e a i e de elopmen s will be included in D4.3
Repo s on he esea ch pilo s’ design, implemen a ion and esul s. In he end, he simula ion
on end will be able o be ound open access unde he ollowing link:
h ps://gi hub.com/Logis ics-Li ing-Lab/sucolo-simula ion- on end
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1. Mo i a ion and backg ound
The e is a lack o shops and acili ies o e e yday goods and se ices on he ou ski s o
Leipzig (1). Especially olde people o en ely on ca s o hei daily asks, as walking dis ances
can be di icul o hem. In con as , many poin s o in e es (POIs) a e loca ed in he ci y
cen e , which makes d i ing essen ial o people li ing on he ou ski s. The SuCoLo p ojec
aims o p o ide mo e eco- iendly mobili y, shopping, and deli e y p ocesses o hese a eas
in o de o connec hem owa ds he 15-minu e ci y ideal. The e o e, he de elopmen o
simula ion app oaches is he subjec o case s udies in Leipzig, Ge many and Me ano, I aly.
Fo he ci y o Leipzig, a new deli e y concep o goods o he ou ski s is de eloped. The
concep in ol es home deli e y ia a ca go bike cou ie , u ilizing a mobile mic o-hub o las -
mile pa cel deli e y. Howe e , he model can also iden i y sui able bikesha ing loca ions and
pa cel pick-up s a ions. The pick-up s a ion loca ion is based on POIs and de ailed popula ion
da a o he ci izens in he a ea. The simula ion model con ains dynamic, social ac o s and
p e e ences o he esiden s, such as ba ie - ee access o acili ies, a e age age s uc u e,
a e age income, e c.
In Me ano, he e a e cu en ly no decen alized sel -se ice bicycle en al sys ems ha would
allow esiden s and ou is s o easily use bicycles o ca go bikes o sho ips. The simula ion
model can de e mine sui able loca ions o decen alized, s a ion-based en al sys ems,
conside ing geog aphic and u ban cha ac e is ics.
The SuCoLo Da a ca alogue o sui able and a ailable (local) da a sou ces/da a se s
(Deli e able 2.2) o ms he da abase o his ask (2). Open da a om he municipal pla o ms
o Leipzig and Me ano a e used o iden i y a ailable popula ion da a. In addi ion, geoda a om
Open S ee Map (OSM) is used o iden i y po en ial POIs.
Based on his, he simula ion model indica es he bes possible loca ion o mic o-hubs o sel -
se ice bike pick-up s a ions in u ban en i onmen s and ou ski s. This is p esen ed as a
hea map, since mul iple loca ions may be sui able unde di e en ci cums ances. To e alua e
he model, he ci ies o Leipzig and Me ano a e chosen as case s udies in SuCoLo.
2. P oblem desc ip ion and model o mula ion
U ban ou ski s a e gene ally no e y well p o ided wi h in as uc u e o e e yday li e as hey
lack ixed se ice acili ies. As a esul , people li ing in hese subu bs ha e di e en needs
om hose li ing in he ci y cen e . Mobili y, shopping, and consume beha io equi e ei he
a el o o de ing online. These a eas a e gene ally spa sely popula ed, o en wi h an olde
popula ion and ewe comme cial es ablishmen s. This is why people who li e on he ou ski s
o he ci y p oduce signi ican ly mo e emissions.
Mos o he pick-up s a ions, especially pa cel locke s, a e loca ed s a egically wi hin walking
dis ance o esiden ial a eas, which makes hem easily accessible and encou ages hei use.
They a e usually loca ed nea public anspo s a ions, business cen e s, inancial a eas,
wo kplaces, gas s a ions, shopping s o es, o cul u al cen e s. Any place whe e he e is a high
concen a ion o people wi h high in e ne shopping equency is a ac i e. These condi ions
a e me by densely popula ed, inne -ci y a eas.
D2.3 AI-based simula ion model o op imal placemen o mic o-hubs and ca go bike pick-up s a ions SuCoLo
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Fo his eason, an AI-based simula ion model has been de eloped ha can conside social
ac o s and he needs o esiden s on he ou ski s. This allows o mo e sus ainable, inclusi e
and e icien deli e y o goods ou side he ci y cen e . The model suppo s de e mining a
sui able loca ion o an inclusi e pick-up s a ion o a bike en al s a ion.
2.1. Model assump ions, da a and pa ame e s o Leipzig
The e is a g owing demand o las -mile deli e y solu ions, especially in low-densi y ou ski s.
E icien ly placing pick-up s a ions in hese a eas equi es conside a ion o logis ics
pe o mance, social accessibili y, and demog aphic da a. The model uses logis ic eg ession
and loca ion knowledge o ecommend high-po en ial pick-up si es. I e alua es in as uc u e,
accessibili y, communi y needs and deli e y his o y o sugges adap able s a ion placemen s
ha a e op imized o ca e o s a ed p e e ences (see below).
Ci izen Pe sonas
To iden i y po en ial use g oups ha would use he de eloped solu ions, h ee di e en ci izen
pe sonas we e gene a ed ha would depic a ypical ci izen li ing in ha a ea along wi h hei
wan s, needs, alues and ea s. These pe sonas a e based on a ci izen su ey in 2025 in
Lü zschena-S ahmeln, Leipzig, Ge many (n = 158). The h ee a ge g oups ha e been
iden i ied include an elde ly e i ed pe son, a amily-o ien ed pe son who wo ks om home and
li es wi h his amily, and a young s uden who p e e s spo s and en e ainmen .
Figu e 1 Th ee pe sonas based on a ge g oups
These indings can be ans e ed o he simula ion model app as eady-made use p o iles.
Acco ding o hei assumed equi emen s, ea u es, demog aphics and p e e ences, di e ing
weigh ings a e ans e ed ac oss he h ee di e en scena ios. Each use p o ile o pe sona
hen s ands o a possible a ge g oup ha can use he pick-up s a ions ( able 1).
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Table 1 Example o Digi al Pe sonas o Model Use
Pe sona
Demog aphic
P e e ences and Weigh ings (example)
Implica ion
Pe sona
01
Olde pe son,
possibly e i ed
o has limi ed
mobili y
• "ca e"= 6
• "ca e_wheelchai "= 8
• "communi y_cen e"= 8
• "communi y_cen e_wheelchai "=
10
• "educa ion_wheelchai "= 6
• "en e ainmen "= 8
• "en e ainmen _wheelchai "= 10
• "heal hca e"= 6
• "heal hca e_wheelchai "= 8
• "hospi al"= 4
• "hospi al_wheelchai "= 6
• "lib a y"= 10
• "lib a y_wheelchai "= 10
• "local_business"= 8
• "local_business_wheelchai "= 10
• "ma ke place"= 10
• "ma ke place_wheelchai "= 10
• "pa cel_locke "= 5
• "pa cel_locke _wheelchai "= 5
• "pos _box"= 10
• "pos _box_wheelchai "= 10
• "pos _o ice"= 10
• "pos _o ice_wheelchai "= 10
• " es au an "= 8
• " es au an _wheelchai "= 10
• "s a ion"= 10
• "s a ion_wheelchai "= 10
• "supe ma ke "= 8
• "supe ma ke _wheelchai "= 10
A socially ac i e,
accessibili y-sensi i e
use . Pick-up s a ions in
he neighbo hood
should be highly
accessible and
in eg a ed in o
communi y-o ien ed
en i onmen s.
Pe sona
02
Middle-aged
amily-o ien ed
pe son,
employed
• "gas_s a ion"= 10
• "pa cel_locke "= 10
• "pos _o ice"= 10
• " es au an "=10
• "bicycle_ en al"= 4
• "pos _box"= 8
• "s a ion"= 6
• "shopping_cen e"= 10
• "local_business"= 10
• " en al_se ice"= 4
• "ma ke place"= 6
• "supe ma ke "= 10
• "en e ainmen "= 10
• "kiosk"= 6
• "ca e"= 10
This use alues
logis ical e iciency.
Ideal pick-up s a ion
loca ions should
minimize de ou s, be
close o anspo
in as uc u e, and
acili a e quick pa cel
access.
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Figu e 3 Simula ion model amewo k
4. Use in e ace o he “Loca ion Finde App”
The g aphical use in e ace (GUI) o he simula ion model, e med “Loca ion Finde App” is
di ided in o wo pa s. On he le side is he con ol panel and on he igh side is he map.
Figu e 4 Sc eensho o he app’s s a sc een
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The use can selec ea u es (e.g., p oximi y o a pos o ice), assign dis ances and op ional
penal ies, and adjus he weigh ing slide s om -10 o +10 based on impo ance gi en o he
lis ed ea u es. This which di ec ly a ec s he model ou pu .
Figu e 5 Demons a ion o he simula ion model esul s based on se p e e ences
D2.3 AI-based simula ion model o op imal placemen o mic o-hubs and ca go bike pick-up s a ions SuCoLo
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Table 5 GUI unc ions
Sc eensho
Func ion
Desc ip ion
Loca ion Finde App
App Name
Logo
SuCoLo Logo; Leads o
h ps://sucolo.eu/
Radio Bu on
Ci y Selec ion
By selec ing a ci y, he
map jumps o he chosen
ci y.
Resolu ion
p ope ies
The e can be h ee
di e en esolu ions be
selec ed om 300m o
4.8km.
D op Down
Menu Type o
Fea u e
Fo selec ing a Type o
Fea u e, which can be
Nea es Ameni y, Ameni y
Coun , Ameni y P esen
and Dis ic Fea u e.
Checkbox
Wheelchai
Accessible
Only shown a e
choosing he Type o
Fea u e.
Nea es
Ameni y Menu
Only shown a e
choosing he “Nea es
Ameni y”. Choose
Ameni y. Op ions: selec
"Wheelchai Accessible”
o ba ie - ee ea u es,
selec a dis ance la ge
han 200 me e s, and
selec a penal y o
in luencing he model.
Ameni y Coun
Menu
Only shown a e
choosing he “Ameni y
Coun ”. Choose Ameni y.
Op ions: selec
"Wheelchai Accessible”
o ba ie - ee ea u es
and selec a dis ance
la ge han 200 me e s.
D2.3 AI-based simula ion model o op imal placemen o mic o-hubs and ca go bike pick-up s a ions SuCoLo
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Ameni y
P esen Menu
Only shown a e
choosing he “Ameni y
P esen ”. Choose
Ameni y. Op ions: selec
"Wheelchai Accessible”
o ba ie - ee ea u es
and selec a dis ance
la ge han 200 me e s.
Dis ic
Fea u e Menu
Only shown a e
choosing he “Dis ic
Fea u e”. Choose a
ea u e.
D op Down
Menu “Selec
Ameni y” o
Nea es
Ameni y,
Ameni y Coun
and Ameni y
P esen
Fo adding one ameni y o
he model.
D op Down
Menu “Selec
Dis ic
Fea u e” o
Dis ic
Fea u e
Fo adding one dis ic
ea u e o he model.
D2.3 AI-based simula ion model o op imal placemen o mic o-hubs and ca go bike pick-up s a ions SuCoLo
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Apply Bu on
By p essing he bu on,
he Type o Fea u e,
Ameni y, Dis ance and
Penal y can be chosen.
Weigh Slide ;
Dele e he
Selec ion
The menu opens a e
p essing he Apply bu on.
Use s assign weigh s o
ea u es, adjus ing
impo ance and in luence
dynamically.
Build Model
Bu on
By p essing he bu on,
he calcula ions o he
model will s a .
Model is
shown on he
map
The model is buil .
Popup by
clicking on a
Hexagon
Shows he calcula ed
model sco es.
Rese Bu on
Reload he page.
Scena io
Bu ons
Reloads p ede ined
Scena ios (Pe sonas).
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Legend Sco e
Scale
Shows Sco e Scale o he
model. Posi ion on he
bo om o he page.
Map Zoom in
(+) o ou (-)
Zoom unc ion o he
map, Posi ion on op o
he page.
4.1. Model E alua ion and u he implemen a ion
The model is assessed h ough a simula ion case s udy and use pe sona-d i en p o iles.
4.2. Case S udy in Ge many, Leipzig
The model was es ed using open da a om Leipzig, pa icula ly he Lü zschena-S ahmeln
dis ic . As s a ed ea lie , ci izen su eys we e used o build use pe sonas, inco po a ing hei
ameni y p e e ences and demog aphic p o iles.
Findings show ha he model can adap i ely sugges pick-up poin s in unde se ed subu ban
a eas wi h bo h logis ical and social bene i s. S a ions also se e as communi y hubs,
encou aging in e ac ion among esiden s and cou ie s.
Figu e 6 Sc eensho o he app cen ed in Leipzig
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5. Discussion and u he wo k
The simula ion model de eloped o he op imal placemen o mic o-hub and ca go bike pick-
up s a ions on u ban ou ski s demons a es he po en ial o combining da a-d i en logis ics
wi h communi y- ocused u ban planning. By in eg a ing open spa ial da a, demog aphic
p o iles, and deli e y analy ics, he model o e s a dynamic and adap able solu ion i ing o he
unique cha ac e is ics o less densely popula ed a eas.
The case s udy in Leipzig illus a es how such a model can be e ec i ely applied in eal-wo ld
se ings. Inco po a ing use pe sonas de i ed om ci izen su eys enables he sys em o align
logis ical p io i ies wi h local social p e e ences, ensu ing ha p oposed loca ions a e no only
ope a ionally e icien bu also socially inclusi e. This dual ocus enhances he model's
ele ance o s akeholde s aiming o balance economic goals wi h communi y engagemen .
One o he model’s uniqueness is i s in e ac i i y and lexibili y. Use s can adjus weigh s and
pa ame e s o simula e a ious scena ios and business objec i es. The abili y o connec eal-
ime da a sou ces and use eedback ensu es ha he model emains esponsi e o changes
in u ban dynamics, such as popula ion shi s o e ol ing deli e y pa e ns.
Howe e , some challenges emain. The quali y and g anula i y o open da a sou ces can a ec
model accu acy. As said, a ailable open da a sou ces o Leipzig and Me ano we e used.
The e a e some gaps in he his o ical da a, which ha e been illed in wi h supplemen a y da a.
Fu he da a a ailabili y, such as cycle pa hs, popula ion igu es in smalle uni s, e c., would
signi ican ly en ich he model. Mo eo e , i has been ound ha social aspec s a e ha de o
quan i y and in eg a e sys ema ically. Fu u e de elopmen could inco po a e addi ional
machine lea ning echniques o mo e ad anced p edic ion, deepe in eg a ion o beha io al
da a, and b oade es ing ac oss di e en ci ies o enhance gene alizabili y.
Fu u e de elopmen s o he simula ion model will be ou lined in D4.3 Repo s on he esea ch
pilo s’ design, implemen a ion and esul s. Mo e po en ial ea u es will be possibly added o
he app in he u u e, including:
• In eg a ing o he Eu opean ci ies
• P edic i e modeling o u u e deli e y demand on he ou ski s
• Au oma ed ETL pipeline implemen a ion wi h eal- ime da a
• Allow use s o isualize sugges ed loca ions on a ci y map and use i o model
calcula ion
• In eg a e co-c ea ion ea u es, such as use eedback on loca ion sugges ions,
in eg a ing occasional communi y e en s, e c.
• Highligh loca ions wi h po en ial o social in e ac ion (e.g., pa ks, ca és, local ma ke s)
In summa y, his model p o ides a new ool o mode n u ban logis ics planning, especially in
he con ex o g owing demand o sus ainable las -mile deli e y solu ions. By combining
echnical p ecision wi h social awa eness, i se s a p omising di ec ion o he u u e o mobili y
and u ban se ice in as uc u e. In he end, he simula ion on end will be able o be ound
open access unde he ollowing link:
h ps://gi hub.com/Logis ics-Li ing-Lab/sucolo-simula ion- on end
D2.3 AI-based simula ion model o op imal placemen o mic o-hubs and ca go bike pick-up s a ions SuCoLo
23
Re e ences
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2023. Re ie ed Ap il 24, 2025, om
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ommunale_B%C3%BC ge um age_2023_-_E gebnisbe ich .pd
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(3) S ad Leipzig. (n.d.-a). O s eile und S ad bezi ke - Leipzig-In o ma ionssys em. Re ie ed
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h ps://openda a.leipzig.de/
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h ps://www.opens ee map.o g/
(7) Gemeinde e o dnung übe die S ad ie el (2023). Gemeinde Me an. Re ie ed Oc obe
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