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Urban Mobility Scaling:Lessons from 'Little Data':

Developing a Science of Cities

Galen J. Wilkerson

ec!nisc!e Universit"t # $erling%&ilkersongmail.com

mailto:gjwilkerson@gmail.commailto:gjwilkerson@gmail.com

8/12/2019 Urban Mobility Scaling: Lessons from 'Little Data'

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Motivation

Science of cities:

Un(erstan(ing ma%or factors) statistical la&s of!o& people c!oose to live toget!er.

*specially) scaling an( salient parameters an(t!eir relations!ips:

Scaling + scale#invariant system p!enomenon

*.g. ,op-lation) area) (ensity patterns) energy

availabilty) transportation mo(e s!are/erke!rsmittelanteil0) c-lt-ral parameters

S-stainability

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Motivation

1n or(er to (evelop science of cities) $igMobility0 Data is very interesting an( -sef-l2

3ere &e

el-ci(ate c!allenges of t!ese ne& (ata so-rces

give some compelling preliminary res-lts fromconventional (ata.

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4vervie&

$ackgro-n(: Urban Scaling) Comple5 Systems) $ig Mobility0 Data

4-r preliminary fin(ings

Categories matter2

3-man#po&ere( mo(es are (ifferent2

Urban Scale 678km0 is revealing

Mobility scaling confirms previo-s res-lts

Distance vs. intervening opport-nity mec!anisms) someres-lts

ime matters + aggregation is (angero-s

9-t-re &ork

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$ackgro-n(

Large#scale -rban p!enomena

e&man an( ;en&ort!y 7

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$ackgro-n(

Urban Scaling

L-is $ettenco-rt) Dirk 3elbing)Geoffrey West 88>0statistical p!ysics0

allometric scalingE of -rbanp!enomena &it! city pop-lation

Similar to non#linear scaling of metabolism

&it! mass of animal mo-se vs. &!ale0 Compare patents to gasoline sales

Sante 9e 1nstit-teS-stainability)*3F 3elbing et al.0 9-t-r1C

@,S 88>A

http://www.sfi.edu/http://www.futurict.eu/http://www.futurict.eu/http://www.sfi.edu/

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$ackgro-n(

Comple5 systems

Self#organiHing 'big' systems

bacteria colony) cro&( of people I 67888 78Kparts0 # (escribe( statistically

9ormalism comes from Statistical ,!ysics

e.g. !ermo(ynamics of &ater +$oltHmann) late 7

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$ackgro-n(

Comple5 systems

Ban(om processes + $ro&nian motion) (iff-sion

Universality classes) (ifferent types of large#scalep!enomena t!at seem to !ave similarc!aracteristics. e.g. rate of (iff-sion n-mber of

frien(s0

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$ackgro-n(

Comple5 systems

po&er la&s

'!eavy tail' # rare important events do actually happen)'more often' t!an &e may e5pect.

*.g. a fe& black s&ans) 3UG* airports) /*B ric! people)a fe& &or(s t!at are -se( /*B BB*L etc.

5

p50

'!eavy tail' +converges slo&ly

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$ackgro-n(

Comple5 systems a little mat!20

po&er la&s one of many '!eavy#taile(' (istrib-tions0

5

p50 '!eavy tail' logp500

log50

linear tail) slope is #N

log#log

@&ikipe(ia.orgA

scaling e5ponent

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$ackgro-n(

Comple5 systems

po&er la&s

Scaling e5ponent N (escribes universality classof p!enomenon

capt-res certain salient large#scale feat-res of -n(erlyingprocess0

i.e. system &it! O N O K is f-n(amentally an( mat!ematically0(ifferent from system &it! 7 O N O ) or K O N O P...

Mean e5ists only if N I ) variance only if N I K) etc.

log50

logp500

Scaling e5ponent) slope is #N

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$ackgro-n(

Slope N0 7.Q

"eneral ba#$ground on %ople& ystes and %ople& (et)or$s*

Mitc!ell) Melanie. Complexity: A uided tour45for( University ,ress) 88 88>0: >K87#>K8R.

$atty) Mic!ael. Cities an( comple5ity: -n(erstan(ing cities &it! cell-lar a-tomata) agent#base( mo(els) an( fractals.!e M1 press) 88>.

M-neepeerak-l) B.) [-bba%) M. B. 870. !e effect of scaling an( connection on t!e s-stainability of a socio#economicreso-rce system. *cological *conomics) >>C0

obility s#aling*

$rockmann) Dirk) Lars 3-fnagel) an( !eo Geisel. Z!e scaling la&s of !-man travel.Z at-re PK8>Q 88R0: PR#PRQ.GonHaleH) Marta C.) Cesar . 3i(algo) an( lbert#LasHlo $arabasi. ZUn(erstan(ing in(ivi(-al !-man mobility patterns.Z at-rePQK.>7>=.

o-las) nastasios) et al. Z tale of many cities: -niversal patterns in !-man -rban mobility.Z ,loS one >.Q 870: eK>8>.

C!o) *-n%oon) Set! . Myers) an( J-re Leskovec. Z9rien(s!ip an( mobility: -ser movement in location#base( socialnet&orks.Z ,rocee(ings of t!e 7>t! CM S1G;DD international conference on ;no&le(ge (iscovery an( (ata mining. CM)877.

mailto:gjwilkerson@gmail.comhttp://arxiv.org/abs/1401.0207http://arxiv.org/abs/1401.0207mailto:gjwilkerson@gmail.com

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9-t-re Work

,-rely geometric mec!anisms

Distance (istrib-tion bet&een points ) $c!osen ran(omly in a (iscV

\ in a #D Ga-ssianV

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9-t-re Work

Comple5 et&orks

*.g. 1nfrastr-ct-re) social net&orks

not!er vie& of systems: interactions bet&een parts.

lso big # (escribe( statistically e.g. n-mber of connections per no(e0

Manye5amples of real-world networ"s:metabolic net&orks) co#a-t!or net&orks) airport connections) etc.

S!are( &it! t!eoretical comp-ter science grap!s0

4ften n-mber of neig!bors (egree0 follo&s a !eavy#tail

/ery large literat-re an( recent &ork2

@&iki.esipfe(.orgA

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9-t-re Work

1nfrastr-ct-re net&orks

3ig!&ays as 'small#&orl('

connections vs. 'lattice' of city BeT-ires energy to b-il( an( -se

t!em a-tos0 2 (-e to timeconstraints0

Belation to transportation mo(es!areV