ArticlePDF Available

Analyzing Carsharing “Public” (Scraped) Data to Study Urban Traffic Patterns

Authors:

Abstract

During the second half of the twentieth century pollution became a relevant problem, but after the seventies many governments began legislating against emissions. From then on, air pollution decreased as new technologies replaced older ones and now transportation, both private and public, is no longer the main source of pollution in modern countries (it still is in third world areas). Today urban trafficper se is the main problem. The pollution traffic component being relegated in the background, many governments and local administrations address the “congestion factor” by introducing regulations to reduce private traffic, considered the main source of congestion: access tolls and (public transport/car pools) dedicated lanes and odd measures such as narrowing lanes (and/or reducing their number), lowering speed limits, reducing parking availability, etc. Geolocation and road navigation technologies, combined with widespread mobile connectivity infrastructures have enabled researchers to study the evolution of traffic at a great depth. To the extent that some vendor, namely TomTom, uses collected customer navigators’ data to publish annual reports - the “TomTom Traffic Index” - about the state of congestion in major cities around the world. One proposed solution to congestion or, better, to the underusage of private vehicles, is the so called “carsharing”, i.e., pools of vehicles to be rented for short periods of time (minutes, hours), usually at higher costs (per day) than standard car rental prices. In many urban areas, such as Milan, where the authors live, measures against congestion are combinedly applied, e.g., tolls to enter a particular area, carsharing (with access to the paying area included), dedicated lanes, ban for certain types (older ones) of vehicles. Carsharing vendors “publish” (not entirely/easily accessible) data about the state of their vehicle pool... Can this data be used to analyze these services’ effect, efficiency, usefulness, social cost, etc.? The authors scraped carsharing vendors’ websites for a year, made this huge amount of data uniform, fed it into a mongodb database and then “played” with queries and graphed results. An interesting finding is that even on the carsharing pool a “lung effect” (people moving-in in the morning, moving-out in the evening) is evident, i.e., the common notion that carsharing is not for commuters can be argued. Another interesting behaviour is the evening peak usage, i.e., probably, caused by people using carsharing instead of taxicabs to go out at night (leisure). Moreover, the data show that vehicle usage (the total number of “busy” vehicles at any time) never goes beyond 70%, i.e., there is always a 30% pool of “free” vehicles. Throughout the paper interesting statistical data and graphs will be shown and discussed.
Procedia Environmental Sciences 37 ( 2017 ) 594 603
1878-0296 © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of the organizing committee of GU 2016
doi: 10.1016/j.proenv.2017.03.046
Available online at www.sciencedirect.com
ScienceDirect
,QWHUQDWLRQDO&RQIHUHQFH±*UHHQ8UEDQLVP*8
$QDO\]LQJ&DUVKDULQJ³3XEOLF´6FUDSHG'DWDWR6WXG\8UEDQ
7UDIILF3DWWHUQV
$QGUHD7UHQWLQL)HGHULFR/RVDFFR
Dip.to Informatica -Universit`a degli Studi di Milano via Comelico 39, 20135 MILANO - Italy
$EVWUDFW
'XULQJWKHVHFRQGKDOIRIWKHWZHQWLHWKFHQWXU\SROOXWLRQ EHFDPHD UHOHYDQWSUREOHPEXWDIWHUWKHVHYHQWLHVPDQ\ JRYHUQPHQWV
EHJDQ OHJLVODWLQJ DJDLQVW HPLVVLRQV )URP WKHQ RQ DLU SROOXWLRQ GHFUHDVHG DV QHZ WHFKQRORJLHV UHSODFHGROGHU RQHV DQG QRZ
WUDQVSRUWDWLRQERWKSULYDWHDQGSXEOLFLVQRORQJHUWKHPDLQVRXUFHRISROOXWLRQLQPRGHUQFRXQWULHVLWVWLOOLVLQWKLUGZRUOGDUHDV
7RGD\ XUEDQ WUDIILFper se LV WKH PDLQ SUREOHP 7KH SROOXWLRQ WUDIILF FRPSRQHQW EHLQJ UHOHJDWHG LQ WKH EDFNJURXQG PDQ\
JRYHUQPHQWV DQG ORFDO DGPLQLVWUDWLRQV DGGUHVV WKH ³FRQJHVWLRQ IDFWRU´ E\ LQWURGXFLQJ UHJXODWLRQV WR UHGXFH SULYDWH WUDIILF
FRQVLGHUHGWKHPDLQVRXUFHRIFRQJHVWLRQDFFHVV WROOVDQGSXEOLFWUDQVSRUWFDUSRROVGHGLFDWHGODQHVDQGRGGPHDVXUHVVXFKDV
QDUURZLQJODQHV DQGRUUHGXFLQJWKHLUQXPEHUORZHULQJ VSHHGOLPLWV UHGXFLQJSDUNLQJDYDLODELOLW\HWF*HRORFDWLRQDQGURDG
QDYLJDWLRQ WHFKQRORJLHV FRPELQHG ZLWK ZLGHVSUHDG PRELOH FRQQHFWLYLW\LQIUDVWUXFWXUHV KDYH HQDEOHG UHVHDUFKHUV WR VWXG\ WKH
HYROXWLRQRIWUDIILFDWDJUHDWGHSWK7RWKHH[WHQWWKDWVRPHYHQGRUQDPHO\7RP7RPXVHVFROOHFWHGFXVWRPHUQDYLJDWRUV¶GDWDWR
SXEOLVKDQQXDOUHSRUWVWKH³7RP7RP7UDIILF,QGH[´DERXWWKHVWDWHRIFRQJHVWLRQLQPDMRUFLWLHVDURXQGWKHZRUOG2QHSURSRVHG
VROXWLRQWRFRQJHVWLRQRUEHWWHU WRWKHXQGHUXVDJHRISULYDWH YHKLFOHVLVWKHVRFDOOHG ³FDUVKDULQJ´LHSRROVRIYHKLFOHVWREH
UHQWHGIRUVKRUWSHULRGVRIWLPH PLQXWHVKRXUVXVXDOO\ DWKLJKHUFRVWV SHUGD\WKDQVWDQGDUGFDUUHQWDOSULFHV,QPDQ\XUEDQ
DUHDVVXFKDV 0LODQZKHUHWKHDXWKRUVOLYHPHDVXUHVDJDLQVWFRQJHVWLRQDUHFRPELQHGO\DSSOLHGHJWROOVWRHQWHUDSDUWLFXODU
DUHDFDUVKDULQJZLWKDFFHVVWRWKHSD\LQJDUHDLQFOXGHGGHGLFDWHGODQHVEDQIRUFHUWDLQW\SHVROGHURQHVRIYHKLFOHV&DUVKDULQJ
YHQGRUV³SXEOLVK´ QRWHQWLUHO\HDVLO\DFFHVVLEOH GDWDDERXW WKHVWDWH RIWKHLUYHKLFOH SRRO&DQ WKLVGDWDEH XVHGWRDQDO\]H
WKHVHVHUYLFHV¶HIIHFWHIILFLHQF\XVHIXOQHVVVRFLDOFRVWHWF"7KHDXWKRUVVFUDSHGFDUVKDULQJYHQGRUV¶ZHEVLWHVIRUD\HDUPDGH
WKLVKXJHDPRXQWRIGDWDXQLIRUPIHGLWLQWRDPRQJRGEGDWDEDVHDQGWKHQ³SOD\HG´ZLWKTXHULHVDQGJUDSKHGUHVXOWV$QLQWHUHVWLQJ
ILQGLQJLVWKDWHYHQRQWKHFDUVKDULQJSRROD³OXQJHIIHFW´SHRSOHPRYLQJLQLQWKHPRUQLQJPRYLQJRXWLQWKHHYHQLQJLVHYLGHQW
LHWKH FRPPRQ QRWLRQWKDW FDUVKDULQJLVQRW IRU FRPPXWHUVFDQ EH DUJXHG$QRWKHU LQWHUHVWLQJEHKDYLRXULV WKHHYHQLQJSHDN
XVDJHLHSUREDEO\FDXVHGE\ SHRSOHXVLQJFDUVKDULQJLQVWHDGRI WD[LFDEVWRJRRXWDW QLJKWOHLVXUH0RUHRYHUWKHGDWDVKRZ
WKDWYHKLFOHXVDJHWKHWRWDOQXPEHURI³EXV\´YHKLFOHVDW DQ\WLPHQHYHU JRHVEH\RQG LHWKHUHLVDOZD\VD SRRORI
³IUHH´ YHKLFOHV 7KURXJKRXW WKH SDSHU LQWHUHVWLQJ VWDWLVWLFDO GDWD DQG JUDSKV ZLOO EH VKRZQ DQG GLVFXVVHG .H\ZRUGV XUEDQ
FRQJHVWLRQRSHQGDWDSXEOLFDFFRXQWDQF\SROOXWLRQDQWLSROOXWLRQSROLFLHVZHEVFUDSLQJ

&RUUHVSRQGLQJDXWKRU7HO
E-mail address:DQGUHDWUHQWLQL#XQLPLLW
595
Andrea Trentini and Federico Losacco / Procedia Environmental Sciences 37 ( 2017 ) 594 – 603
)LJXUH+LVWRULFDOWUHQGRISO2VRXUFH$53$/RPEDUGLD
7KH$XWKRUV3XEOLVKHGE\(OVHYLHU%9
3HHUUHYLHZXQGHUUHVSRQVLELOLW\RIWKHRUJDQL]LQJFRPPLWWHHRI*8
Keywords:XUEDQFRQJHVWLRQRSHQGDWDSXEOLFDFFRXQWDQF\SROOXWLRQDQWLSROOXWLRQSROLFLHVZHEVFUDSLQJ
,QWURGXFWLRQ
$LUSROOXWLRQ VWDUWHGWREHFRPH DSUREOHPIRU KXPDQEHLQJVZLWK WKHLQGXVWULDOUHYROXWLRQ> @$IWHUWKH
VHYHQWLHVPDQ\JRYHUQPHQWVVWDUWHGWROHJLVODWH>@WR WU\ DQG UHGXFH LQGXVWULDO SODQWV PDWHULDOV WUDQVSRUWDWLRQ
SRZHU JHQHUDWLRQ HWF HPLVVLRQV )URP WKHQ RQ DLU SROOXWLRQ VORZO\ EHJDQ WR GHFUHDVH DV QHZ JHQHUDWLRQV RI
WHFKQRORJLHV UHSODFHG ROGHU RQHV VHH )LJXUH  DQG DOO WKH JUDSKV UHWULHYDEOH IURP $53$
KWWSZZZDUSDORPEDUGLDLWTDULDILOHVYDULH0,B62SQJMXVWUHSODFH0,ZLWKRWKHU/RPEDUG\]RQHVDQG62ZLWK
RWKHUSROOXWDQWV
1RZDGD\VXUEDQWUDIILFSHUVHLVSHUFHLYHGWREHWKHPDLQSUREOHPRIPRGHUQFRXQWULHVFLWLHV7KHSROOXWLRQWUDIILF
FRPSRQHQW EHLQJ UHOHJDWHG LQ WKH EDFNJURXQG PDQ\ JRYHUQPHQWV DQG ORFDO DGPLQLVWUDWLRQV DUH DGGUHVVLQJ WKH
³FRQJHVWLRQIDFWRU´E\LQWURGXFLQJUHJXODWLRQV>@WRUHGXFHSULYDWHWUDIILFFRQVLGHUHGWKHPDLQVRXUFHRIFRQJHVWLRQ
VXFKDV
 ,PSRVLQJDFFHVVWROOVIRUSDUWLFXODUO\SULYDWHFDUFURZGHG]RQHV
 'HGLFDWHODQHVWRSXEOLFWUDQVSRUWFDUSRROV
 1DUURZLQJWKHODQHVWRPDNHFDUVJRVORZHU
 5HGXFLQJWKHQXPEHURIODQHVWR³GLVHQFRXUDJH´E\DFWXDOO\LQFUHDVLQJFRQJHVWLRQ&DURZQHUVDQGSXVKWKHP
WRZDUGVSXEOLFWUDQVSRUW
 /RZHULQJVSHHGOLPLWVDJDLQ³GLVHQFRXUDJH´
 5HGXFLQJSDUNLQJDYDLODELOLW\DJDLQ³GLVHQFRXUDJH´
$ORQJVLGHWKHVH ³EDUULQJ´ LQLWLDWLYHVDIHZ \HDUV DJRYHQGRUVVWDUWHG SURYLGLQJWKHVR FDOOHG ³FDUVKDULQJ´LH
SRROVRIVKDUHGDPRQJPDQ\XVHUVYHKLFOHVWREHUHQWHGIRUVKRUWSHULRGVRIWLPHPLQXWHVKRXUVXVXDOO\DWKLJKHU
FRVWVSHUGD\WKDQVWDQGDUGFDUUHQWDOSULFHV7KHUDWLRQDOHEHKLQGFDUVKDULQJLVWKDWSDUNLQJVSDFHLVVDYHGVLQFH
DVLQJOHSDUNHGYHKLFOHVHUYHVDORWRIXVHUVQRWDVLQJOHRQHDVLVWKHFDVHRIDSULYDWHFDUVLQFHLWFRVWVSHUXVH
PRUHWKDQ DSULYDWH FDUEXWOHVVWKDQD WD[LFDEPDQ\XVHUVHYHQLIVXEVFULEHGWRWKHVHUYLFH ZRXOGXVH LWZLVHO\
PD\EHPL[LQJLWZLWKVWDQGDUGSXEOLFWUDQVSRUWWKXVUHGXFLQJWKHRYHUDOOFDU PLOHDJHORDG RQWKH FLW\ LWPD\
KHOSLQIXUWKHUSROOXWLRQORZHULQJ>@,QPDQ\XUEDQDUHDVVXFKDV0LODQZKHUHWKHDXWKRUVOLYHPHDVXUHVDJDLQVW
FRQJHVWLRQDUHFRPELQHGO\DSSOLHGHJWROOVWRHQWHUDSDUWLFXODUDUHD FDUVKDULQJ ZLWK DFFHVV WR WKH SD\LQJ DUHD
LQFOXGHGGHGLFDWHGODQHVEDQIRUFHUWDLQW\SHVROGHURQHVRIYHKLFOHV
)LUVWFDUVKDULQJV\VWHPVZHUH FRQILQHGWR GHVLJQDWHGVSRWVLQWRZQZKHUHDXVHUFRXOGWDNHRXWDQG JLYHEDFN D
FDU 1RZDGD\V JHRORFDWLRQ DQG URDG QDYLJDWLRQ WHFKQRORJLHV FRPELQHG ZLWK ZLGHVSUHDG PRELOH FRQQHFWLYLW\
LQIUDVWUXFWXUHVKDYHHQDEOHGYHQGRUVWROHWXVHUVOHDYHDQGILQGFDUVZKHUHYHUWKH\ZDQW*HRORFDWLRQDQGQDYLJDWLRQ
© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of the organizing committee of GU 2016
596 Andrea Trentini and Federico Losacco / Procedia Environmental Sciences 37 ( 2017 ) 594 – 603
DSSOLFDWLRQVLQ JHQHUDOLHQRWQHFHVVDULO\UHODWHG WRFDUVKDULQJOHW ³PDUNHWSOD\HUV´VWXG\XVHUVEHKDYLRXUWRWKH
H[WHQWWKDW VRPHYHQGRU QDPHO\7RP7RPXVHVFROOHFWHGFXVWRPHU QDYLJDWRUV¶GDWDWR SXEOLVK DQQXDOUHSRUWV WKH
³7RP7RP7UDIILF,QGH[´DERXWWKHVWDWHRIFRQJHVWLRQLQPDMRUFLWLHVDURXQGWKHZRUOG>@
)RUFDUVKDULQJ DVPDUWSKRQHDSSOLFDWLRQFDQWUDFNGRZQWKH SRVLWLRQRIDYDLODEOHFDUVDQG OHDGXVHUVWR SUHFLVH
SDUNLQJORFDWLRQV/RFDWLRQGDWDLVRIFRXUVHVWRUHGDQGVHFXUHGLQWRYHQGRUV¶V\VWHPVEXWVRPHGDWDLVQRQHWKHOHVV
DYDLODEOHRQWKHZHEEHFDXVHVPDUWSKRQHDSSVPXVWJHWDWOHDVWWKHJHRORFDWHGOLVWRIDYDLODEOHFDUV
&DQ WKLVGDWD EH XVHG WR DQDO\]H WKHVHVHUYLFHV¶ HIIHFWHIILFLHQF\
XVHIXOQHVVVRFLDOFRVWHWF"7KLVSDSHU
UHSUHVHQWVDQDIILUPDWLYH DQVZHU
DQG VKRZV WKH LQLWLDO ILQGLQJV RI D \HDU HIIRUW LQ FDUVKDULQJ GDWD JDWKHULQJ
XQGHUWDNHQE\WKHDXWKRUV
$VLPLODUZRUNKDVEHHQGHVFULEHGLQ>@EXWLQWKDWFDVHWKHIRFXVZDVGLIIHUHQWWKH\ZDQWHGWRLGHQWLI\FODVVRI
XVHUVDQGWKH\KDGDFFHVVWRWKHLQWHUQDO
DQGFRPSOHWHFDUVKDULQJYHQGRUGDWDEDVH7KHZRUNGHVFULEHGKHUHLVLQVWHDG
EDVHGVROHO\RQGDWDREWDLQDEOHZLWKRXWGLUHFWO\DVNLQJWKHYHQGRU6WDWLVWLFDODQDO\VHVSUHVHQWHGKHUHUHSUHVHQWPDVV
EHKDYLRXURUVLQJOHFDUEHKDYLRXUEXWGHFRXSOHGIURPWKHXVHUGULYLQJLW
1.1. Carsharing Systems in Milan (Italy)
,Q0LODQFXUUHQWO\ILYHPLQXVRQHZKRZHQWEDQNUXSWLQFDUVKDULQJYHQGRUVDUHDYDLODEOHVHH6HFWLRQIRU
FRPSOHWHOLVWDQG85/V7KH\DUHDOOVLPLODULQKRZWKH\RIIHUWKHLUVHUYLFHDXVHUPXVWVXEVFULEHWRWKHVHUYLFH
IRUDQ DQQXDOIHH HXURIRUVRPHYHQGRULV VRPHLQFOXGHXVDJHPLQXWHVDV D ³ZHOFRPHSDFNDJH´ WKH
QHZO\VXEVFULEHGXVHUPXVWGRZQORDGDQGLQVWDOO DVSHFLILFVPDUWSKRQHDSSOLFDWLRQXVXDOO\ $SSOHRU$QGURLGQRW
HDV\WRILQGVXSSRUWIRURWKHURSHUDWLQJHQYLURQPHQWVWKHDSSOLFDWLRQZRUNVXVLQJ*36QRSULYDF\DQGPRELOH
GDWDSRVVLEOHDGGHGIHHVWKHXVHUQHHGLQJDFDUFDQILQGLWRQWKHDSSOLFDWLRQUHDOWLPHXSGDWHGPDSDQGFDQHYHQ
SUHERRNLWDWDFRVWSHUPLQXWH^WKHDERYHWZRRSHUDWLRQVFDQEHGRQHYLDFDOOFHQWHULHZLWKRXWWKHQHHGIRU
DQ³DSS´ RIWHQZLWKVRPHDGGHGFRVW` WKHXVHU DSSURDFKHVWKH ERRNHGFDUDQGKHRSHQVLWZLWK D5),'5DGLR
)UHTXHQF\,'HQWLILFDWLRQVPDUWFDUGRUWKHSKRQHLWVHOIWKURXJK1)&1HDU)LHOG&RPPXQLFDWLRQRU53&5HPRWH
3URFHGXUH&DOO WKH FDU FDQ EH VWDUWHG DQG XVHG DW ZLOO XVXDOO\ ZLWKLQ WLPHVSDFH OLPLWV HJ NP  ZKHQ
ILQLVKHGLHSDUNHGWKHXVHUFRPPXQLFDWHVWKH³HQGRIVHUYLFH´WKURXJKWKHDSSRUFDOOFHQWHU8VDJHIHHVDUHXVXDOO\
E\WKHPLQXWHLQWKHQHLJKERUKRRGRIHXURFHQWVSHUPLQXWHLHHXURK6RPHYHQGRURIIHUVFRPELQDWLRQVDQG
SDFNDJHVEORFNVRIPLQXWHVSHUPRQWKHWF$VDFRPSDULVRQWD[LFDEIHHVKWWSWD[LEOXLWFPVWDULIIHWD[LDUHE\
NP׽HXURNPRUKRXU׽HXURKSOXVDQLQLWLDOIHHEHWZHHQHXURDQGHXUR&DUVKDULQJXVHUVGRQRW
KDYHWRSD\WKH$UHD&VHH6HFWLRQWROOWRHQWHUWKHFLW\FHQWHU9HQGRUVSD\IRUIDLWVDERXWHXUR\HDUSHU
YHKLFOHWRWKH0LODQ&LW\&RXQFLODQGWKHQWKH\VSUHDGWKLVFRVWRYHUWKHLUXVHUV
1.2. Opendata, “Obtorto Collo” Data and webscraping
2SHQ GDWD DQG FRQWHQW FDQ EH IUHHO\ XVHG PRGLILHG DQG VKDUHG E\ DQ\RQH IRU DQ\ SXUSRVH >IURP
KWWSRSHQGHILQLWLRQRUJ@
3XEOLFLW\LV MXVWO\ FRPPHQGHG DV D UHPHG\ IRU VRFLDO DQG LQGXVWULDOGLVHDVHV6XQOLJKWLVVDLGWREHWKHEHVWRI
GLVLQIHFWDQWVHOHFWULFOLJKWWKHPRVWHIILFLHQWSROLFHPDQ>DWWULEXWHGWR-XVWLFH/RXLV'%UDQGHLV@
2SHQGDWDLQLWVZLGH PHDQLQJLVDSROLWLFDOPRYHPHQWWKDWSXVKHVJRYHUQPHQWVILUPVSXEOLF DGPLQLVWUDWLRQV
HWFWRZDUGVLQIRUPDWLRQWUDQVSDUHQF\$FFRUGLQJWRWKLVPRYHPHQWRUJDQL]DWLRQDOHQWLWLHVDERYHDOOWKHSXEOLFIXQGHG
RQHVVKRXOGSXEOLVKLQIRUPDWLRQDERXWWKHLULQWHUQDOZRUNLQJV,QIRVXFKDVH[SHQVHVSHRSOHUROHVSXEOLFDFWLYLWLHV
ODZPDNLQJZRUNIORZLHQRWRQO\WKHILQDO³SURGXFW´WKHODZVSXEOLFXWLOLW\VWUXFWXUHVHJ EXVVWRSORFDWLRQV
SXEOLFRIILFHVWLPHWDEOHVDQGFRPPHUFLDOLQIRHJJHRORFDWHGOLVWVRIILUPVVKRSVHWFSHUW\SH:KHQDYDLODEOH
RSHQGDWDLVXVXDOO\DFFHVVLEOHYLDZHEVLWHV0DQ\RUJDQL]DWLRQVHYHQGHGLFDWHHQWLUHZHEVLWHVWRRSHQGDWDRQO\HJ
GDWDJRY 86$ GDWDJRYXN 8. GDWLJRYLW ,WDO\ LQVWHDG RI HPEHG GLQJ DQ RSHQGDWD VHFWLRQ LQWR WKHLU ZHEVLWHV
2SHQGDWD KDV EHHQ FDWHJRUL]HG LQWR FODVVHV EDVHG RQ IRUPDW DQG OLFHQFH>@ DQG RQ ZLGHU IXQFWLRQDO DVSHFWV >@
6RPHWLPHV RSHQGDWD LV GRZQORDGDEOHLQ EDWFK ELJ FRPSUHVVHG ILOHV DQG VRPHWLPHV LW¶V DFFHVVLEOH WKURXJK $3,
$SSOLFDWLRQ3URJUDPPLQJ,QWHUIDFH,QOXFNLO\UDUHFDVHVRUJDQL]DWLRQVGRSXEOLVKGDWDWKDWFDQEHGHILQHG³RSHQ´
EXWWKH\ DOVRDSSO\VRPHVRFDOOHG³ZHEVWDFOHV´ZHEREVWDFOHVWRUHGXFHWKH XVDELOLW\IRUWKHSXEOLF,QWKLVODWWHU
597
Andrea Trentini and Federico Losacco / Procedia Environmental Sciences 37 ( 2017 ) 594 – 603
FDVHVDWHFKQLTXHFDOOHG³ZHEVFUDSLQJ´SURJUDPPDWLYHO\DFFHVVLQJGDWDPHDQWIRUKXPDQVRQVWDQGDUGZHESDJHV
FDQEHXVHIXOO\DSSOLHG>@WRREWDLQGDWD³REWRUWRFROOR´ODWLQIRU³XQZLOOLQJO\´
1.3. “AreaC” city center toll
³$UHD&´LVD/RQGRQ&RQJHVWLRQ&KDUJHLQVSLUHGFHQWUDO]RQHRI0LODQLQZKLFKYHKLFOHVDUH³UHJXODWHG´VRPH
DUH SHUPDQHQWO\ EDQQHG ROGHU RQHV ZLWKRXW H[FHSWLRQV QRW HYHQ DQWLTXH FDUV VRPH FDQ HQWHU IRU IUHH
HOHFWULFK\EULG/3*FDUVPRWRUELNHVDQGPRSHGVDQGWKHUHVWPXVWSD\D WROO,W LVDFWLYH0RQGD\WR)ULGD\ IURP
$0WR3030RQ7KXUVGD\&RVWLVHXURIRUDVLQJOHGD\HXUR IRUUHVLGHQWVOLPLWHGWRWLFNHWV
GLVFRXQWVDYDLODEOHLISXEOLFSDUNLQJ LV ERXJKW FRPELQHGO\ :KLOHWKH0LODQ7RZQ &RXQFLO DVVHUWHG WKDW ³$UHD&´
FRQWULEXWHGWRSROOXWLRQUHGXFWLRQZLWKRXWSXEOLVKLQJYHULILDEOHWKLUGSDUW\GDWDWKH7UDQVSRUWIRU/RQGRQKDGDOUHDG\
FRQFOXGHG>@WKDWQRXVHIXOUHGXFWLRQKDGEHHQREWDLQHGLQ/RQGRQ0RUHRYHUDQLQGHSHQGHQW>@DQDO\VLVEDVHG
RQ$53$WKH,WDOLDQ(3$SXEOLFGDWDFRQILUPVWKLVQHJDWLYHFRQFOXVLRQLQWKH0LODQFRQWH[W7RP7RPGHILQHVWKH
³FRQJHVWLRQIDFWRU´DVWKHGLIIHUHQFHPHDVXUHGWKURXJKDUDWLRLQRYHUDOOVSHHGEHWZHHQWKHZRUVWWLPHDQGWKHEHVW
WLPHLHLWGRHVQRWPHDVXUHWKHDEVROXWHFRQJHVWLRQLQDFLW\1RQHWKHOHVV7RP7RPSXEOLVKHVDUDQNLQJFRPSDULQJ
ZRUOGFLWLHV $VIRU0LODQ 7RP7RPLQGH[>@FODLPVD VPDOOUHGXFWLRQ>ė @>ė @>ė
@> ė@>ė@Ā$UHD&´ LQWURGXFWLRQLQ-DQ >ė@>ė@,HD
GHFUHDVHLJQRULQJDSRVVLEOHWUHQGIURP0RUHRYHUQRWKLQJFDQEHVDLG DERXWWKH HYHQWVDQGFDXVHVIRUWKLV
FKDQJHLWFRXOGEHWKDWWKHEHVWWLPHRIGD\KDGZRUVHQHGRUYLFHYHUVD
0DLQWH[W
,Q 0LODQ ,7$/< WKHUH DUH ILYH FDUVKDULQJ YHQGRUV   6KDUH¶1*R  KWWSZZZVKDUHQJRLW  7ZLVW&DU
KWWSWZLVWFDULW GLVFRQWLQXHG VLQFH QRY  (QMR\ KWWSHQMR\HQLFRP  &DU*R KWWSZZZ
FDUJRFRP*XLGD0LKWWSZZZJXLGDPLQHW
*XLGD0LQRZ*LU$&,GRHVQRWSXEOLVKGDWDDERXWFDUVEXWLWLVDVPDOOHUFRQWHQGHULQWKHFDUVKDULQJXQLYHUVHLQ
0LODQ*XLGD0LRIIHUVD YHU\OLPLWHGVHWRIFDUVWKDWPXVW EHWDNHQDQGJLYHQEDFNIURPIHZVSHFLILHGFDUSDUNVLQ
WRZQ7KHRWKHUYHQGRUVGRSXEOLVKGDWDDERXWFDUSRVLWLRQVDQGDYDLODELOLW\VRPHRIWKHP&DUJRHYHQRIIHU$3,
$SSOLFDWLRQ3URJUDPPLQJ,QWHUIDFHWRTXHU\GDWDDOEHLWZLWKVRPHOLPLWDWLRQVORZTXHU\IUHTXHQF\QHHG IRU D
VHFXULW\NH\7RHDVHSURJUDPPLQJZRUNWKHDXWKRUVGHFLGHGWRVLPSO\VFUDSHZHEVLWHGDWDXVLQJZJHW >@LQVKHOO
VFULSWVRUVPDOOS\WKRQ>@SURJUDPVSHULRGLFDOO\UXQRQDDOZD\VRQPDFKLQH7KHVHVFULSWVUXQHYHU\PLQXWHWKH\
VDYHGDWDLQ&69&RPPD6HSDUDWHG9DOXHVRUGLUHFWO\ LQWRDPRQJRGE>@GDWDEDVH$OOWKHGDWDLQ &69ILOHV LV
HYHQWXDOO\IHGLQWRWKHVDPHGDWDEDVH
7KHVH DUH WKH 85/V 8QLIRUP 5HVRXUFH /RFDWRUV XVHG WR JHW FDU VWDWXV GDWD  6KDUH¶1*R
KWWSZZZVKDUHQJRLWFRUHSXEOLFFDUV7ZLVW&DUKWWSZZZWZLVWFDULWVWDUWBWZLVWMV(QMR\KWWSHQMR\
HQLFRPDMD[UHWULHYHBYHKLFOHV&DU*RKWWSZZZFDUJRFRPDSL
YYHKLFOHV"ORF PLODQRRDXWKBFRQVXPHUBNH\ FDUJRZHEVLWHIRUPDW MVRQ
6FUDSHGGDWDGHSHQGLQJRQWKHYHQGRUFDQEHLQWKHIRUPRIUHDG\GDWDHJ-621-DYD6FULSW2EMHFW1RWDWLRQRU
;0/ H;WHQVLEOH 0DUNXS /DQJXDJH WKDW MXVW QHHG WR EH FRQYHUWHG SDUVHU OLEUDULHVDUH UHDGLO\ DYDLODEOH LQWR D
VXLWDEOHVWUXFWXUH IRUWKHGDWDEDVHRULWFDQEHJDWKHUHG LQWKHIRUPRIDQ +70/+\SHU7H[W 0DUNXS/DQJXDJH
SDJHWKDWPXVWEHSURFHVVHGWRH[WUDFWVWUXFWXUHGGDWD,QWKHODWWHUFDVHILOWHUVVXFKDVKWPOWH[WFXWJUHSVHGDZN
HWFW\SLFDO*18/LQX[FRPPDQGVPXVW EH FRPELQHG WR H[WUDFW WKH LQWHUHVWLQJ GDWD IURPWKHIRUPDWWLQJ+70/
PHWDGDWD7KHGDWDDYDLODEOHDIWHUVFUDSLQJDQGFOHDQLQJIURPWKHYHQGRUVLVGHVFULEHGE\WKHIROORZLQJ
6KDUH¶1*R DFWLYH EDWWHU\ EXV\ FKDUJLQJ GDPDJHV H[W&OHDQOLQHVVILUPZDUH 9HUVLRQ IUDPH KLGGHQ LPHL
LQW&OHDQOLQHVVLV5HVHUYHG%\&XUUHQW8VHUNPODEHOODVW&RQWDFWODVW/RFDWLRQ7LPHODWLWXGHORFDWLRQORQJLWXGHPDF
PDQXIDFWXUHVPRGHOQRWHVREF,Q8VHREF:O6L]HSDUNLQJSODWHUSPUXQQLQJVRFVRIWZDUH9HUVLRQVSHHGVWDWXV
YLQ
7ZLVW&DUOLFHQVH3ODWHIXHO/HYHOLQVLGH6WDWXVRXWVLWH6WDWXV
598 Andrea Trentini and Federico Losacco / Procedia Environmental Sciences 37 ( 2017 ) 594 – 603
(QMR\FDU QDPHFDUSODWHIXHOODWLWXGH ORQJLWXGHDGGUHVV YLUWXDOUHQWDO W\SHLGYLUWXDOUHQWDOLGFDUFDWHJRU\
W\SHLGFDUFDWHJRU\LGRQFOLFNGLVDEOHGFDUPRGHOGDWD
&DU*R DGGUHVV FRRUGLQDWHVODWORQJ HQJLQH W\SH H[WHULRU FRQGLWLRQ LQWHUQDO FRQGLWLRQ FDU QDPH QHHG
VPDUWSKRQHYHKLFOHLG
$UHFRUGUHSUHVHQWVWKHFXUUHQWVWDWXVRIDFDU$VWKHUHDGHUFDQVHHWKH6KDUH¶1*RYHQGRULVWKHPRVWYHUERVH
DOEHLWQRWHYHU\ILHOGLVXVHIXOVLQFHWKHGDWDLVDYDLODEOHRQZHERQO\ZKHQWKHFDULVSDUNHGLHILHOGVVXFKDVVSHHG
LVDOZD\V]HURZKHQVFUDSHG
7KHVDPSOLQJIUHTXHQF\LVPLQLHZHEVLWHGDWDLVVFUDSHGHYHU\PLQXWHJHQHUDWLQJKכPK VDPSOHV
SHUGD\:KHQWKHV\VWHPZDVGHVLJQHGLWZDVIRUHVHHDEOHWKDWWKHVKRUWHVWUHQWZRXOGEHDWOHDVWDIHZPLQXWHVWKXV
VDPSOLQJDWPLQXWHLQWHUYDOVFRXOGEHFRQVLGHUHGRYHUVDPSOLQJEXWWKDWPLQLPXPXVHFDVHZDVDQDVVXPSWLRQWKH
DXWKRUVZDQWHGWRYHULI\H[DPLQLQJWKHDFWXDOGDWDE\ILQGLQJUHSHDWHGUHFRUGV
7KHKHWHURJHQHRXVJDWKHUHGGDWDLVWKHQLQWHUVHFWHGLQWRWKHIROORZLQJPRQJRGEGRFXPHQWVFKHPDLG LGHQWLILHU
HQJLQH W\SHRIHQJLQHHOHFWULFJDVROLQHHWFFDUSODWH SODWHVHUYLFHQDPH YHQGRU(QMR\7ZLVWHWFODWLWXGH
SRVLWLRQODWLWXGHORQJLWXGH SRVLWLRQORQJLWXGHGDWH ,62GDWHRIVDPSOHIXHO IXHOOHYHO2YHUWKLVGDWDEDVH
WKHDXWKRUVFUHDWHGTXHULHVWRH[WUDFWLQIRUPDWLRQDQGJHQHUDWHWKHJUDSKVVKRZQLQ6HFWLRQ
$QDO\VLV
,QWKHIROORZLQJVXEVHFWLRQVWZRDQDO\VHVXVDJHDQGDYHUDJHGLVWDQFHDUHVKRZQDQGFRPPHQWHG7KH\DUHEDVHG
RQGDWDJDWKHUHGEHWZHHQ6HSWHPEHUDQG0DUFK
7KHDXWKRUV DSSOLHGD VWUDLJKWIRUZDUGPHWKRGRORJ\WRH[WUDFWWKHILUVWILQGLQJVRQ WKHGDWD LHIRUHYHU\DVSHFW
XQGHULQYHVWLJDWLRQWKH\JHQHUDWHGJHQHUDO VWDWLVWLFVPLQ PD[DYHUDJHTXDQWLOHVHWFDQGFUHDWHGSORWVIRUHYHU\
GD\WRORRNIRUHYLGHQWSDWWHUQVLIDQ\
/XFNLO\IURPWKHDXWKRUV¶SRLQWRIYLHZWKHJUDSKVVKRZHGDQHYLGHQWGDLO\DQGZHHNO\SDWWHUQVVHH)LJXUH
IRUDQH[DPSOHVXFKDV
x(YHU\GD\LV³F\FOLFDO´HJQLJKWGLIIHUVIURPGD\RIILFHKRXUVUHSUHVHQWSHDNVHWF
x7KHUHDUH³VHDVRQDO´ZHHNO\HIIHFWV DGD\VIURP0RQGD\WR)ULGD\DUHVLPLODUWR RQHDQRWKHU E6DWXUGD\
DQG6XQGD\DUHVLPLODUF6DWXUGD\DQG6XQGD\GLIIHUVIURP0RQ)ULZRUNGD\V
x7KHUHDUHRIFRXUVHUDQGRPIOXFWXDWLRQV
7REHWWHUDQDO\]HWKHLQZHHNSDWWHUQVDPRUHWKRURXJKVWDWLVWLFDOLQVSHFWLRQZDVFDUULHGRQ'DWDZHUHGLYLGHGLQWR
ZHHNVDQGIRU HYHU\ ZHHN 44 SORWVZHUHFUHDWHG7KH 44 4XDQWLOH4XDQWLOH SORWVDUHXVHGWRFRPSDUHLIWZR
VDPSOHVDUH ³VWDWLVWLFDOO\ VLPLODU´ $44SORWIRU HYHU\ GD\ SDLU0RQ7XH0RQ:HG0RQ7KXHWFLQHYHU\
ZHHNZDVJHQHUDWHGRULJLQDWLQJ
 44SORWVSHUZHHNH[DPSOHVLQ)LJXUHDQG)LJXUH7KLVSURFHGXUH
VWDWLVWLFDOO\FRQILUPHGWKHHYLGHQWSDWWHUQGLIIHUHQFHEHWZHHQ0RQGD\)ULGD\DQG6DWXUGD\DQG6XQGD\
6RPH DEEUHYLDWLRQV XVHG LQ WKH UHVW RI WKLV SDSHU + +ROLGD\ 1+ 1RQ +ROLGD\ VWDWV FRPSXWDWLRQ RI
0LQLPXPVW4XDQWLOH0HGLDQ0HDQUG4XDQWLOH0D[LPXPILYHQXP FRPSXWDWLRQRI0LQLPXP/RZHUKLQJH
0HGLDQ8SSHUKLQJH0D[LPXP'DWDDQDO\VLVZDVFDUULHGRQXVLQJ5>@
3.1. Cars usage
/HW¶VGHILQHWKHIXQFWLRQ
ܥܽݎܣݒ݈ܾ݈ܽ݅ܽ݁ݐൌ൜
ͳǡ݂݅݌ܽݎ݇݁݀݅Ǥ݁Ǥܽݒ݈ܾ݈ܽ݅ܽ݁
Ͳǡ݋ݐ݄݁ݎݓ݅ݏ݁݅݊ݑݏ݁ 
PRGHOLQJWKHDYDLODELOLW\RIDVLQJOHFDUDWDJLYHQWLPHtWKHIXQFWLRQUHWXU QV
³WUXH´LIWKHFDULVIUHHWREH
ERRNHGE\DFXVWRPHU7KHQWKHWRWDOQXPEHU
RIIUHHFDUVDWDJLYHQWLPHt LV
ܥܽݎݏܣݒ݈ܾ݈ܽ݅ܽ݁ݐσܥܽݎݏܣݒ݈ܾ݈ܽ݅ܽ݁ሺݐሻ
௜א஼௔௥
599
Andrea Trentini and Federico Losacco / Procedia Environmental Sciences 37 ( 2017 ) 594 – 603
:KHQWKLVYDOXHLVORZLWPHDQVWKDWPDQ\FDUVDUH³WDNHQ´LHDUHLQXVH,Q)LJXUH0RQ)ULDQG)LJXUH6DW
6XQLVUHSUHVHQWHGDW\SLFDOZHHNXVDJHRWKHUZHHNVLQWKHGDWDDUHVLPLODUWRWKHRQHVKRZQ
1RWDEOHUHPDUNVLQ)LJXUH0RQ)ULDUHWKHIROORZLQJ
 1LJKWWLPHEHWZHHQ$0DQG$0UHSUHVHQWVDSHDNRIIUHHFDUV
 7KHXVDJHSHDNOHDVWQXPEHURIIUHHFDUVLVEHWZHHQ30DQG30
 0RUQLQJEHWZHHQ$0DQGQRRQXVDJHLVOHVVHUWKDQDIWHUQRRQQRRQWR30XVDJH
1RWDEOHUHPDUNVLQ)LJXUH6DWDQG6XQDUHWKHIROORZLQJ
 1LJKWWLPHSHDNVSRUWVDVKRUWHUWLPHVSDQEHWZHHQ$0DQG$0ZUWWKH0RQGD\WR)ULGD\QLJKWWLPH
SHDNV
 7KHUHLVDXVDJHSHDNEHWZHHQPLGQLJKWDQG$0RIWHQPRUHVXEVWDQWLDOWKDQWKHDIWHUQRRQSHDN
)LJXUH8VDJHRIIUHHFDUVDYHUDJHDW\SLFDOZHHN0RQ)UL
)LJXUH8VDJHRIIUHHFDUVDYHUDJHDW\SLFDOZHHNVDWVXQ
600 Andrea Trentini and Federico Losacco / Procedia Environmental Sciences 37 ( 2017 ) 594 – 603
7DEOH6WDWVIRUZHHNLQ)LJXUHDQG)LJXUHIUHHFDUV
'$<
'$7(
0LQ
VW4X
0HGLDQ
0HDQ
UG4X
0D[
0RQGD\







7XHVGD\







:HGQHVGD\







7KXUVGD\







)ULGD\







6DWXUGD\







6XQGD\







7DEOHVKRZVWKHstats IRUWKHVDPHZHHNWROHWWKHUHDGHUVHHWKHVLPLODULW\
EHWZHHQ0RQ)ULGD\V
DQGWKHHYLGHQWVWDWLVWLFDOGLIIHUHQFHIURP0RQ)UL DQG
6DWXUGD\6XQGD\
)LJXUHVKRZVDJUDSKRIWKHSDUWLDOstats RYHUWKHZKROHVHWRI XVDJH
GDWDWRYLVXDOO\IROORZ
WKHWUHQGRImin, mean, maxDORQJWKHWLPHIUDPHIURP
6HSWHPEHUWR'HFHPEHU
)LJXUHGHSLFWVWKHXVDJH44SORWVRIWZRGD\SDLUVWDNHQDVH[DPSOH
DJDLQVW
7XHDJDLQVW0RQQHDUWKHy x OLQHѧ VWDWLVWLFDOO\VLPLODUDJDLQVW6XQDJDLQVW
7XHIDUIURPWKHy x
OLQHѧ VWDWLVWLFDOO\GLIIHUHQW,HXVHUV¶EHKDYLRXURQ6XQGD\LVGLIIHUHQWIURP
D
ZHHNGD\
3.2. Average distance from city center: the “lung” effect
,QWKLV6HFWLRQZHDQDO\]HWKHRYHUDOOGLVWDQFHRIFDUVIURPWKHFLW\FHQWHU$WDQ\JLYHQWLPHtWKHGLVWDQFHRID
VLQJOHFDULVGHILQHGE\
ܥܽݎܦ݅ݏݐܽ݊ܿ݁ݐȁܥܽݎܲ݋ݏ݅ݐ݅݋݊ݐܥ݅ݐݕܥ݁݊ݐ݁ݎܲ݋ݏ݅ݐ݅݋݊ȁ
,HWKHPRGXOHRIWKHYHFWRULDOGLVWDQFHEHWZHHQFDUDQGFHQWHUODWLWXGHORQJLWXGH
)LJXUH8VDJH44SORWVW\SLFDO1+1+YHUVXVW\SLFDO+1+
)LJXUH
*UDSKRISDUWLDO
VWDWV
0LQ0HDQ0D[RQIUHHFDUV>$XJ
ĺ
0DU@
601
Andrea Trentini and Federico Losacco / Procedia Environmental Sciences 37 ( 2017 ) 594 – 603
7KHQZHGHILQHWKHDYHUDJHGLVWDQFHDWWLPHtE\
ܣݒ݁ݎܽ݃݁ܦ݅ݏݐܽ݊ܿ݁ݐൌ ܥܽݎܦ݅ݏݐܽ݊ܿ݁ሺݐሻ݅אܥܽݎݏ

,HZHFRPSXWHWKHDYHUDJHRIDOOFDUGLVWDQFHVIURPFLW\FHQWHUDWDJLYHQWLPH
1RWDEOHUHPDUNVLQ)LJXUH0RQWR)ULDUHWKHIROORZLQJ
³OXQJ´HIIHFW¶DYHUDJHGLVWDQFHGHFUHDVHVGXULQJWKHGD\$0WR30DQGLQFUHDVHVGXULQJWKHUHVWRIWKH
GD\LHSHRSOHPRYHLQWRWKHFLW\GXULQJGD\WLPHDQGPRYHRXWRIWKHFLW\RWKHUZLVH
WKHUHLVDFRQFHQWUDWLRQSHDNEHWZHHQ$0DQG30LHGXULQJOXQFKWLPHXVHUVDUHRQWKHDYHUDJHQHDUHU
WRWKHFLW\FHQWUH
EHWZHHQ$0DQG$0WKHUHLVDVXGGHQRXWPRYHPHQWRISHRSOHFORVHO\IROORZHGE\DQLQPRYHPHQWLH
PDQ\XVHUVPRYHLQRXWLQWKRVHKRXUVEXWQRWH[DFWO\DWWKHVDPHWLPHWKH\ZRXOGEOHQGLQWKHDYHUDJH
GLVWDQFH
DOVRFRPSDULQJ)LJXUH GXULQJ 0RQ)UL QLJKW  PRUQLQJV PLGQLJKW WR $0 DYHUDJH GLVWDQFH GHFUHDVHV
IDVWHUWKDQGXULQJ6DW6XQ
$QRWDEOHUHPDUNLQ)LJXUHLVWKDWEHWZHHQ$0DQG30WKHUHDUHQRELJVSLNHVEXWRQO\DJHQHUDODQGVORZ
LQFUHDVHLQDYHUDJHGLVWDQFH
'$<
'$7(
0LQLPXP
/RZH
U
KLQJH
0HGLDQ
8SSH
U
KLQJH
0D[LPXP
0RQGD\






7XHVGD\






:HGQHVGD\






7KXUVGD\






)ULGD\






6DWXUGD\






6XQGD\






7DEOH)LYHQXPIRUZHHNLQ)LJXUHDQG)LJXUH
)LJXUH$YHUDJHRIGLVWDQFHVDW\SLFDOZHHN0RQ)UL
)LJXUH$YHUDJHGLVWDQFHVDW\SLFDOZHHNVDWVXQ
602 Andrea Trentini and Federico Losacco / Procedia Environmental Sciences 37 ( 2017 ) 594 – 603
7DEOHVKRZVWKHILYHQXPIRUWKHVDPHZHHNWROHWWKHUHDGHUHYDOXDWHWKHVLPLODULWLHVDQGGLIIHUHQFHV7KHUHLVD
ORZHUGLVWDQFHSHDNRQ0RQGD\DQGWKHQDVORZLQFUHDVHGXULQJWKHZHHN
)LJXUHGHSLFWVWKHGLVWDQFHV44SORWVRIWZRGD\SDLUVWDNHQDVH[DPSOHDJDLQVW:HG
DJDLQVW7KXQHDUWKH\ [OLQHėVWDWLVWLFDOO\VLPLODUDJDLQVW0RQDJDLQVW6XQIDUIURP
WKH\ [OLQHėVWDWLVWLFDOO\GLIIHUHQW,HDJDLQXVHUV¶EHKDYLRXURQ6XQGD\LVGLIIHUHQWIURPDQRUPDOZHHNGD\
&RQFOXVLRQVDQGIXWXUHZRUN
7KLVSDSHUGHVFULEHVD\HDUORQJHIIRUWLQZHEVFUDSLQJDQGDQDO\]LQJFDUVKDULQJGDWDLQ0LODQ,WDO\6LQFH$XJXVW
VKHOODQGS\WKRQVFULSWVUXQHYHU\PLQXWHWRFROOHFWGDWDIURPFDUVKDULQJYHQGRUZHEVLWHVWKHQGDWDLVXQLIRUPHG
DQG IHG LQWR D PRQJRGE GDWDEDVH 6WDWV DQG JUDSKVDUH WKHQ JHQHUDWHG IURP WKH GDWDEDVH 6XFK D GDWDVHW FDQ EH
HQRUPRXVO\ XVHIXO WR VWDNHKROGHUV FLWL]HQV SRWHQWLDO FDUVKDULQJ FRPSHWLWRUV SXEOLF DGPLQLVWUDWLRQV LQWHUHVWHG LQ
XQGHUVWDQGLQJPRELOLW\WUHQGVDQGLQGHVLJQLQJQHZVXVWDLQDEOHPRELOLW\VHUYLFHV&XUUHQWYHQGRUVVKRXOGPDNHWKHLU
GDWDPRUHHDVLO\DYDLODEOHIRUWKHVDNHRISXEOLFJRRG
'DWDJDWKHUHGSORWWHGVRIDUSUHVHQWHGLQ6HFWLRQVKRZVWKDW
 WKHUHLVDQHYLGHQWXVDJHSDWWHUQLQRIIUHHFDUVDQGDYHUDJHGLVWDQFHIURPFHQWHUGLIIHUHQFHEHWZHHQZRUN
GD\V0RQ)ULDQGZHHNHQGV6DW6XQ
 WKHUHDUHLQWHUHVWLQJ WLPHZLQGRZV)ULDQG 6DW QLJKWVPRUQLQJ$0$0PRUQLQJ $0QRRQ $0
30HWFWKDWFRXOGEHPRUHWKRURXJKO\DQDO\]HG
 WKHUHDUHXVDJHSHDNVRXWVLGHWKH³$UHD&´WLPHZLQGRZ
 WKH DYHUDJH GLVWDQFH IURP FHQWHU VWDWV RQ $XJ ė0DU  GDWD DUH 0LQ VW 4X 
0HGLDQ 0HDQ UG4X 0D[ 0LODQUDGLXVFDQEHDSSUR[LPDWHGZLWKVTUW.Pʌ
׽.PLHWKHDYHUDJHGLVWDQFHLVFHQWHUHGDWRIFLW\UDGLXV
7KHDXWKRUVDUHFXUUHQWO\DQDO\]LQJ
x³KRWVSRWV´]RQHVZKHUHFDUVDUHPRUHIUHTXHQWO\OHIW
xPRYHPHQWWUHQGVH[WUDFWLQJWULSYHFWRUVIRUHYHU\YHKLFOH
xIUHTXHQF\DQGORFDWLRQRIIXHOUHILOOLQJ
:KLOHIXWXUHDQGPRUHJHQHUDODQDO\VLVZRUNFDQEHLPDJLQHGVXFKDVVWXG\LQJFRQJHVWLRQ]RQHVDQGWLPHVHJ
WRLGHQWLI\EDGO\PRELOLW\ZLVHGHVLJQHGXUEDQ]RQHVFRUUHODWLQJFDUVKDULQJGDWDZLWKRWKHUGDWDSXEOLFWUDQVSRUW
ZHDWKHUKROLGD\VVWULNHVHWFHYDOXDWLRQRIFDUVKDULQJYHQGRUV¶TXDOLW\RIVHUYLFHLQWHUPVRIFRYHUHG]RQHVYHKLFOH
DYDLODELOLW\HWFFRPSDULVRQZLWKVLPLODUVWXGLHVXQGHUWDNHQZRUOGZLGH
)LJXUH'LVWDQFHV44SORWVW\SLFDO1+1+YHUVXVW\SLFDO+1+
603
Andrea Trentini and Federico Losacco / Procedia Environmental Sciences 37 ( 2017 ) 594 – 603
5HIHUHQFHV
%HUQHUV/HH7/LQNHGGDWDKWWSZZZZRUJ'HVLJQ,VVXHV/LQNHG'DWDKWPO
'DYLHV7DQG3DUWLFLSDWLRQ32SHQGDWDGHPRFUDF\DQGSXEOLFVHFWRUUHIRUP$ORRNDWRSHQJRYHUQPHQWGDWDXVHIURPGDWDJRYXN
3UDFWLFDO3DUWLFLSDWLRQ
)LUQNRUQ-DQG0XOOHU0:KDWZLOOEHWKHHQYLURQPHQWDOHIIHFWVRIQHZIUHHIORDWLQJFDUVKDULQJV\VWHPV"WKH FDVHRIFDUJRLQ
XOP(FRORJLFDO(FRQRPLFV±
*18*18ZJHWKWWSZZZJQXRUJVRIWZDUHZJHW
/DYH/%DQG6HVNLQ(3$LUSROOXWLRQDQGKXPDQKHDOWKYROXPH5RXWOHGJH
0RQJR'%,QFUHDGKWWSZZZPRQJRGEFRP
0RUHQF\&7UHSDQLHU0$JDUG%0DUWLQ %DQG 4XDVKLH-&DUVKDULQJ V\VWHPZKDWWUDQVDFWLRQ GDWDVHWVUHYHDORQ XVHUV¶
EHKDYLRUV,Q,QWHOOLJHQW7UDQVSRUWDWLRQ6\VWHPV&RQIHUHQFH,76&,(((SDJHV±,(((
5HSRUW77,KWWSZZZWRPWRPFRPWUDIILFLQGH[>@5RVVXP*9UHDGKWWSZZZS\WKRQRUJ
6HLQIHOG-+DQG3DQGLV61$WPRVSKHULFFKHPLVWU\DQGSK\VLFVIURPDLUSROOXWLRQWRFOLPDWHFKDQJH-RKQ:LOH\6RQV
6WHLQOH65HLV6DQG6DEHO&(4XDQWLI\LQJKXPDQH[SRVXUHWRDLUSROOXWLRQ²PRYLQJIURPVWDWLFPRQLWRULQJWRVSDWLRWHPSRUDOO\
UHVROYHGSHUVRQDOH[SRVXUHDVVHVVPHQW6FLHQFHRIWKH7RWDO(QYLURQPHQW±
7KH5)RXQGDWLRQ7KH5SURMHFWIRUVWDWLVWLFDOFRPSXWLQJKWWSZZZUSURMHFWRUJ
7UDQVSRUWIRU/RQGRQ&RQJHVWLRQFKDUJLQJSXEOLFDWLRQVKWWSZZZWIOJRYXNURDGXVHUVFRQJHVWLRQFKDUJLQJDVS[
7UHQWLQL$ /RPEDUG\HSD REWRUWRFROORGDWD DQGDQWLSROOXWLRQ SROLFLHV IDOODFLHV-RXUQDO RIH/HDUQLQJDQG .QRZOHGJH6RFLHW\

7UHQWLQL$9HULI\LQJWUDIILFEDQHIIHFWVRQDLUSROOXWLRQ-RXUQDORI$WPRVSKHULF3ROOXWLRQ±
86(3$+LVWRU\RIWKHFOHDQDLUDFWKWWSZZZHSDJRYDLUFDDDPHQGPHQWVKWPO
9DQGHUELOW77UDIILF:K\:H'ULYHWKH:D\:H'RDQG:KDW,W6D\V$ERXW8V1HZ<RUN7LPHV
... Moreover, census data are commonly used for estimating demand for car sharing systems [26], bike sharing systems [27], or for setting up electric vehicle charging stations [28]. Data mining and other related techniques are also often employed to detect traffic patterns for bike sharing systems [29,30], as well as car sharing systems [31]. ...
Article
Full-text available
This article presents a cooperative optimization approach (COA) for distributing service points for mobility applications, which generalizes and refines a previously proposed method. COA is an iterative framework for optimizing service point locations, combining an optimization component with user interaction on a large scale and a machine learning component that learns user needs and provides the objective function for the optimization. The previously proposed COA was designed for mobility applications in which single service points are sufficient for satisfying individual user demand. This framework is generalized here for applications in which the satisfaction of demand relies on the existence of two or more suitably located service stations, such as in the case of bike/car sharing systems. A new matrix factorization model is used as surrogate objective function for the optimization, allowing us to learn and exploit similar preferences among users w.r.t. service point locations. Based on this surrogate objective function, a mixed integer linear program is solved to generate an optimized solution to the problem w.r.t. the currently known user information. User interaction, refinement of the matrix factorization, and optimization are iterated. An experimental evaluation analyzes the performance of COA with special consideration of the number of user interactions required to find near optimal solutions. The algorithm is tested on artificial instances, as well as instances derived from real-world taxi data from Manhattan. Results show that the approach can effectively solve instances with hundreds of potential service point locations and thousands of users, while keeping the user interactions reasonably low. A bound on the number of user interactions required to obtain full knowledge of user preferences is derived, and results show that with 50% of performed user interactions the solutions generated by COA feature optimality gaps of only 1.45% on average.
... In de Luca and Pace (2015) and Morency et al. (2007) the authors analyzed the characteristics of car sharing users and discovered different classes of users. The paths covered by FFCS vehicles have also been studied to identify the urban traffic patterns (Ampudia-Renuncio et al., 2020;Schmöller et al., 2015;Trentini and Losacco, 2017) and to predict the presence of available cars within a given urban area (Daraio et al., 2020;Formentin et al., 2015;Phithakkitnukoon et al., 2010). Car movements appeared to be non-stationary and correlated with (i) the previous car movements within nearby areas, (ii) the weather conditions in the recent past, and (iii) the variations of the socio-demographic factors in the long run. ...
Article
During the last decade, car sharing systems appeared in many cities and gained popularity. The research community has analyzed their current utilization trends in different contexts, their growth perspectives, and their gradual shift towards more sustainable technologies. Through the large and heterogeneous amount of car sharing usage data that is now available, researchers have been able to gain new insights into these services. In this paper, we provide an extensive characterization of the Free-Floating Car Sharing (FFCS) service usage in 23 cities in Europe and North America over a 14-month period. From our data about FFCS services, we detail fleet size, operating area, and characteristics of the car bookings and rentals. We also identify temporal patterns that are peculiar to specific cities and countries. We further highlight urban zones with high attractiveness or with a high rental generation rate. Finally, we compare the systems relying on internal combustion engine cars with those based on electric vehicles in terms of various indicators, including the influence on car refueling. The results show that car utilization patterns are rather variable across cities with the highest per-car utilization rate in Madrid. The majority of the cities show negative or stable usage trends due to either the reduced appeal of the service or the presence of inefficiencies in the service provision. These data-driven insights may help system managers assess the provided services’ profitability and sustainability from multiple perspectives.
... For instance, Hui et al. (2017) see stronger commuting behavior in the Chinese CS market than abroad. The web scrapping approach of Trentini and Losacco (2017) indicates commuting behavior among CS users as well as a substitution of taxicabs for leisure purposes. Kortum et al. (2016) use a similar approach to identify key factors in FF growth rates and state a negative relationship between the size of households and their odds to use CS on a regular basis. ...
Article
The rapidly developing concept of carsharing is an essential and scalable part of sustainable, multimodal mobility in urban environments. There is a clear need for carsharing operators to understand their users and how they use different transportation modes to intensify the development of carsharing and its positive impacts on the environment and urban cohabitation. We foster this understanding by analyzing usage data of carsharing in a medium-sized German city. We compare user groups based on individual characteristics and their carsharing usage behavior. We focus on a station-based two-way carsharing scheme and its relation to free-floating carsharing. Based on different clustering and segmentation approaches, we defined 20 particularly interesting user groups among the carsharing users and analyzed noticeable usage patterns. Additionally, we examined these partially overlapping user groups in the spatial dimension. With these results, we support research and operators in understanding carsharing customers and assessing users’ individual behavior.
... The analysis of FFCS usage data have been extensively addressed in literature. For example, to support system managers and operators, a relevant effort has been devoted to the identification of relevant service usage patterns and user profiles [1,6,[12][13][14][15][16][17]. An example of FFCS service characterization is given in [1]. ...
Article
Full-text available
Free-Floating Car Sharing (FFCS) services are currently available in tens of cities and countries spread all over the worlds. Depending on citizens’ habits, service policies, and road conditions, car usage profiles are rather variable and often hardly predictable. Even within the same city, different usage trends emerge in different districts and in various time slots and weekdays. Therefore, modeling car availability in FFCS systems is particularly challenging. For these reasons, the research community has started to investigate the applicability of Machine Learning models to analyze FFCS usage data. This paper addresses the problem of predicting the short-term level of availability of the FFCS service in the short term. Specifically, it investigates the applicability of Machine Learning models to forecast the number of available car within a restricted urban area. It seeks the spatial and temporal contexts in which nonlinear ML models, trained on past usage data, are necessary to accurately predict car availability. Leveraging ML has shown to be particularly effective while considering highly dynamic urban contexts, where FFCS service usage is likely to suddenly and unexpectedly change. To tailor predictive models to the real FFCS data, we study also the influence of ML algorithm, prediction horizon, and characteristics of the neighborhood of the target area. The empirical outcomes allow us to provide system managers with practical guidelines to setup and tune ML models.
... Similar use data can be extracted for many of the emerging mobility systems. With regards to bikesharing there are more than 800 programs around the world with a fleet of more than 900.000 bicycles with trip proposes to be commute to work on weekdays and leisure and/or social purposes (Fishman et al., (Trentini and Losacco, 2017). This latter methods is subject to the general data use policy of the provider and bears issues such as inability to define relocation, false/canceled reservations and routes. ...
Article
Abstract This study explores the mobility patterns of carsharing members from their trip distance perspective and its associated factors with a specific focus on its members' personal, usage, and stations' locational characteristics. Using Seoul as a case study, one-month rental transaction datasets provided by two-way carsharing operators were used as a data source. The multilevel mixed-effect modeling approach was applied to remedy spatial heterogeneity across station locations that affect the distance traveled by each rental. In addition, a classification among the carsharing members based on trip distance was conducted using regression tree to obtain clusters of the most homogenous member groups. The multilevel model results confirmed the important roles played by the station location and individual-level factors that affect mobility patterns of carsharing members. Individual-level characteristics showed that members in their 50s and female travel longer. Similarly, rentals made on non-workdays and in the morning showed longer travel distances. The station-level characteristics indicate that carsharing stations' proximity to public transit and leisure areas positively affects trip distances, suggesting the effect of the built environment and land use on the travel patterns of carsharing members. By combining carsharing transaction and their stations’ built environment data, this study suggests a new interface for city officials and carsharing operators to work together for achieving their sustainable mobility objectives together.
Article
Full-text available
Air pollution started to become a problem for human beings with the industrial revolution, but nowadays, with the introduction of laws against emissions (e.g., the EuroX normative), the situation is getting better. Moreover, governments must constantly monitor pollution levels to check policies effects. This article describes a method to verify traffic ban effect claims on air pollution using monitored data. In Lombardia (our region), ARPA (the local EPA) maintains pollution monitoring stations from downtown Milano to remote places near the mountains since 1999. Measured data are " somewhat " available through ARPA's website. " Somewhat " because a CAPTCHA protected download request form must be filled up for every combination of (station, pollutant, time-frame < 1 yr). In 2003 the Lombardia government introduced a vehicle ban to reduce air pollution. Then, more recently (in 2008 and 2012) the Milano City Council introduced a stricter ban. The author implemented an automated (in place since 2004) data collecting " web gatherer " to overcome ARPA's overcomplicated download procedure and, above all, to verify air pollution reduction claims. Data are published on the author's website and this paper presents a method to analyse effects on air pollution and to verify policies claims.
Article
Full-text available
Quantifying human exposure to air pollutants is a challenging task. Ambient concentrations of air pollutants at potentially harmful levels are ubiquitous in urban areas and subject to high spatial and temporal variability. At the same time, every individual has unique activity-patterns. Exposure results from multifaceted relationships and interactions between environmental and human systems, adding complexity to the assessment process. Traditionally, approaches to quantify human exposure have relied on pollutant concentrations from fixed air quality network sites and static population distributions. New developments in sensor technology now enable us to monitor personal exposure to air pollutants directly while people are moving through their activity spaces and varying concentration fields. The literature review on which this paper is based on reflects recent developments in the assessment of human exposure to air pollution. This includes the discussion of methodologies and concepts, and the elaboration of approaches and study designs applied in the field. We identify shortcomings of current approaches and discuss future research needs. We close by proposing a novel conceptual model for the integrated assessment of human exposure to air pollutants taking into account latest technological capabilities and contextual information.
Article
The purpose of this paper is the discussion of the environmental effects of a free-floating car-sharing system operating in Ulm, Germany. The system, called car2go, allows users to take and leave vehicles at any point within the city limits. Thus opposed to traditional car-sharing, there are no fixed stations and in particular one-way trips of any length are possible without a booking requirement. Since this is the first free-floating system in operation, there is as yet no associated empirical research. Based on primary data from a survey, a model was developed to forecast the environmental impact of car2go. The prognosis considers the period of five years after the launch of car2go in 2009 and indicates a CO2-reduction per average car2go-user. In addition, more than a quarter of the survey respondents stated that they may forgo a car purchase if car2go was offered permanently. By reaching a greater share of citizens than traditional systems, the results indicate that free-floating car-sharing systems could contribute to reducing private vehicle ownership in cities.