Design of Robust and Energy-Efficient ATO Speed Profiles of Metropolitan Lines Considering Train Load Variations and Delays

Metropolitan railway operators' strategic plans include nowadays actions to reduce energy consumption. The application of ecodriving initiatives in lines equipped with automatic train operation (ATO) systems can provide important savings with low investments. Previous studies carried out under...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transactions on intelligent transportation systems Vol. 16; no. 4; pp. 2061 - 2071
Main Authors:	Fernandez-Rodriguez, Adrian, Fernandez-Cardador, Antonio, Cucala, Asuncion P., Dominguez, Maria, Gonsalves, Tad
Format:	Journal Article
Language:	English
Published:	IEEE 01.08.2015
Subjects:	Communication-based train control (CBTC) Delays Energy consumption energy saving Linear programming multi objective particle swarm optimization (MOPSO) Optimization Particle swarm optimization Robustness subway systems train load variations train operation Uncertainty multi objective particle swarm optimization (MOPSO) train load variations subway systems Communication-based train control (CBTC) uncertainty energy saving train operation
ISSN:	1524-9050, 1558-0016
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	Metropolitan railway operators' strategic plans include nowadays actions to reduce energy consumption. The application of ecodriving initiatives in lines equipped with automatic train operation (ATO) systems can provide important savings with low investments. Previous studies carried out under the ATO framework have not considered the main uncertainties in the traffic operation: the train load and delays in the line. This paper proposes a method to design robust and efficient speed profiles to be programmed in the ATO equipment of a metro line. First, an optimal Pareto front for ATO speed profiles that are robust to changes in train load is constructed. There are two objectives: running time and energy consumption. A robust optimization technique and an alternative method based on the conservation of the shape of the speed profiles (pattern robustness) are compared. Both procedures make use of a multi objective particle swarm optimization algorithm. Then, the set of speed profiles to be programmed in the ATO equipment is selected from the robust Pareto front by means of an optimization model. This model is a particle swarm optimization algorithm (PSO) to minimize the total energy consumption considering the statistical information about delays in the line. This procedure has been applied to a case study. The results showed that the pattern robustness is more restrictive and meaningful than the robust optimization technique as it provides information about shapes that are more comfortable for passengers. In addition, the use of statistical information about delays provides additional energy savings between 3% and 14%.
AbstractList	Metropolitan railway operators' strategic plans include nowadays actions to reduce energy consumption. The application of ecodriving initiatives in lines equipped with automatic train operation (ATO) systems can provide important savings with low investments. Previous studies carried out under the ATO framework have not considered the main uncertainties in the traffic operation: the train load and delays in the line. This paper proposes a method to design robust and efficient speed profiles to be programmed in the ATO equipment of a metro line. First, an optimal Pareto front for ATO speed profiles that are robust to changes in train load is constructed. There are two objectives: running time and energy consumption. A robust optimization technique and an alternative method based on the conservation of the shape of the speed profiles (pattern robustness) are compared. Both procedures make use of a multi objective particle swarm optimization algorithm. Then, the set of speed profiles to be programmed in the ATO equipment is selected from the robust Pareto front by means of an optimization model. This model is a particle swarm optimization algorithm (PSO) to minimize the total energy consumption considering the statistical information about delays in the line. This procedure has been applied to a case study. The results showed that the pattern robustness is more restrictive and meaningful than the robust optimization technique as it provides information about shapes that are more comfortable for passengers. In addition, the use of statistical information about delays provides additional energy savings between 3% and 14%.
Author	Fernandez-Rodriguez, Adrian Cucala, Asuncion P. Fernandez-Cardador, Antonio Dominguez, Maria Gonsalves, Tad
Author_xml	– sequence: 1 givenname: Adrian surname: Fernandez-Rodriguez fullname: Fernandez-Rodriguez, Adrian email: adrian.fernandez@iit.upcomillas.es organization: Inst. for Res. in Technol., Comillas Pontifical Univ., Madrid, Spain – sequence: 2 givenname: Antonio surname: Fernandez-Cardador fullname: Fernandez-Cardador, Antonio email: antonio.fernandez@iit.upcomillas.es organization: Inst. for Res. in Technol., Comillas Pontifical Univ., Madrid, Spain – sequence: 3 givenname: Asuncion P. surname: Cucala fullname: Cucala, Asuncion P. email: paloma.cucala@iit.upcomillas.es organization: Inst. for Res. in Technol., Comillas Pontifical Univ., Madrid, Spain – sequence: 4 givenname: Maria surname: Dominguez fullname: Dominguez, Maria email: maria.dominguez@iit.upcomillas.es organization: Inst. for Res. in Technol., Comillas Pontifical Univ., Madrid, Spain – sequence: 5 givenname: Tad surname: Gonsalves fullname: Gonsalves, Tad email: tad-gonsal@sophia.jp organization: Dept. of Inf. & Commun. Sci., Sophia Univ., Tokyo, Japan
BookMark	eNp9kE1OwzAQhS0EEqVwAMTGF0jxb5Msq1KgUlERDWwjJx5XRsGu7LCouDwOrViwYGGN9UbfzLx3gU6dd4DQNSUTSkl5Wy2rzYQRKieMl7Tg9ASNqJRFRgidng5_JrKSSHKOLmJ8T6qQlI7Q1x1Eu3XYG_zim8_YY-U0XjgI2322MMa2FlyPZ9Uab3YAGj8Hb2wHcSCeoA9-5zvbK4dX1iV17l20GoJ1W1wFZZPulcZvKljV29T8mX8HndrHS3RmVBfh6ljH6PV-Uc0fs9X6YTmfrbJW5LTPpMyJSudrmafXQCOJkA3jipSaUUOZEKVhBdNTxQvJGYFW59KUpAReiEbzMaKHuW3wMQYw9S7YDxX2NSX1kF49pFcP6dXH9BKT_2Ha5HJw0CdX3b_kzYG0APC7KU83i1Lwb19nf2o
CODEN	ITISFG
CitedBy_id	crossref_primary_10_1016_j_ijepes_2018_12_038 crossref_primary_10_1016_j_trc_2018_08_009 crossref_primary_10_1016_j_treng_2025_100361 crossref_primary_10_1177_03611981231205876 crossref_primary_10_1080_23249935_2017_1332113 crossref_primary_10_1002_ese3_1971 crossref_primary_10_1007_s12544_017_0253_9 crossref_primary_10_1080_23248378_2016_1179599 crossref_primary_10_1109_ACCESS_2024_3427314 crossref_primary_10_1109_ACCESS_2020_3017193 crossref_primary_10_1109_TTE_2022_3194698 crossref_primary_10_1016_j_ins_2021_04_088 crossref_primary_10_1109_TTE_2025_3544112 crossref_primary_10_1109_ACCESS_2021_3091550 crossref_primary_10_1080_23248378_2020_1829513 crossref_primary_10_3390_biomimetics10060384 crossref_primary_10_1016_j_energy_2022_124848 crossref_primary_10_1109_TVT_2020_2967467 crossref_primary_10_1002_tee_23003 crossref_primary_10_1108_IJSE_04_2021_0210 crossref_primary_10_1109_JIOT_2019_2919066 crossref_primary_10_1109_TIA_2025_3531327 crossref_primary_10_1016_j_physa_2020_124927 crossref_primary_10_1016_j_jclepro_2019_03_037 crossref_primary_10_1016_j_trb_2016_06_006 crossref_primary_10_1109_TVT_2023_3262345 crossref_primary_10_1016_j_conengprac_2023_105605 crossref_primary_10_1016_j_est_2024_113498 crossref_primary_10_1016_j_jrtpm_2018_03_003 crossref_primary_10_1016_j_trc_2023_104059 crossref_primary_10_1016_j_trc_2025_105148 crossref_primary_10_3390_en12132518 crossref_primary_10_1109_ACCESS_2022_3167155 crossref_primary_10_1016_j_cie_2020_106594 crossref_primary_10_1080_0305215X_2020_1746782 crossref_primary_10_1007_s40864_020_00130_7 crossref_primary_10_1109_ACCESS_2021_3132938 crossref_primary_10_29328_journal_jairi_1001003 crossref_primary_10_1016_j_ijepes_2020_106631 crossref_primary_10_1016_j_epsr_2023_109196 crossref_primary_10_1177_09544097221103351 crossref_primary_10_1109_MCI_2022_3155330 crossref_primary_10_3390_en13051115 crossref_primary_10_1002_eej_23059 crossref_primary_10_1109_TCSS_2023_3303473 crossref_primary_10_1049_iet_its_2017_0156 crossref_primary_10_1016_j_swevo_2025_102027 crossref_primary_10_3390_su15129238 crossref_primary_10_1016_j_simpat_2018_01_006 crossref_primary_10_1061__ASCE_CO_1943_7862_0002288 crossref_primary_10_1109_TITS_2018_2805917 crossref_primary_10_3390_app10217705 crossref_primary_10_1016_j_egyr_2023_12_014 crossref_primary_10_1016_j_rineng_2024_103129 crossref_primary_10_1049_itr2_12509 crossref_primary_10_1080_0305215X_2024_2385583 crossref_primary_10_3390_en13071836 crossref_primary_10_3390_su14148645 crossref_primary_10_1049_iet_its_2016_0256 crossref_primary_10_1109_TITS_2019_2897279 crossref_primary_10_1007_s40864_016_0047_8 crossref_primary_10_1016_j_jclepro_2021_127163 crossref_primary_10_1109_ACCESS_2023_3261900 crossref_primary_10_1109_TITS_2016_2630718 crossref_primary_10_1016_j_trc_2023_104113 crossref_primary_10_1002_eej_23380 crossref_primary_10_1109_TITS_2019_2906483 crossref_primary_10_1016_j_apenergy_2018_05_092 crossref_primary_10_1016_j_simpat_2016_12_008
Cites_doi	10.1049/iet-epa:20070005 10.1002/tee.21782 10.1109/ICNN.1995.488968 10.1109/TITS.2013.2244885 10.1109/TITS.2013.2266255 10.1109/CEC.2003.1299816 10.1016/j.engappai.2008.03.008 10.1061/(ASCE)TE.1943-5436.0000550 10.1177/09544097JRRT420 10.1016/S0952-1976(00)00027-0 10.1109/TITS.2014.2366495 10.1016/j.engappai.2013.07.015 10.1049/iet-epa:20070381 10.1109/TITS.2012.2234118 10.1016/j.sbspro.2013.10.606 10.1177/0954409711429411 10.1109/TITS.2013.2285737 10.1109/9.867018 10.1049/ip-epa:20040346 10.1049/ic.2010.0038 10.1109/ACC.2011.5991057 10.1145/1068009.1068047 10.1049/iet-its.2010.0144 10.1016/j.epsr.2011.08.004 10.1109/TITS.2014.2303146 10.1007/s12239-013-0099-7 10.1109/TASE.2011.2160537 10.1109/TIA.2014.2312538 10.1080/00207720412331203633 10.1109/CDC.2000.914108 10.1016/j.engappai.2012.02.006 10.1007/978-3-540-31880-4_11 10.1109/TITS.2013.2292712 10.1109/TIA.2009.2031898 10.1002/tee.20528 10.1109/CSIE.2009.323 10.1109/TVT.2012.2187225 10.1016/j.engappai.2013.12.015 10.1243/09544097F00505 10.1016/j.enconman.2014.01.060 10.1109/TITS.2013.2296655 10.1109/ICSMC.1997.637339 10.1109/TITS.2014.2319233 10.1016/j.omega.2011.12.001 10.1155/2013/156548 10.1109/ITSC.2011.6082964 10.1016/j.trc.2013.01.007 10.1016/j.trb.2014.03.006 10.1109/TASE.2012.2201148 10.1109/TITS.2012.2219620 10.1061/(ASCE)TE.1943-5436.0000483 10.1155/2013/643274 10.1049/iet-est.2010.0074 10.1016/0165-0114(94)90109-0
ContentType	Journal Article
DBID	97E RIA RIE AAYXX CITATION
DOI	10.1109/TITS.2015.2391831
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef
DatabaseTitle	CrossRef
DatabaseTitleList
Database_xml	– sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	1558-0016
EndPage	2071
ExternalDocumentID	10_1109_TITS_2015_2391831 7045494
Genre	orig-research
GroupedDBID	-~X 0R~ 29I 4.4 5GY 5VS 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACGFS ACIWK ACNCT AENEX AETIX AGQYO AGSQL AHBIQ AIBXA AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS EJD HZ~ H~9 IFIPE IPLJI JAVBF LAI M43 O9- OCL P2P PQQKQ RIA RIE RNS ZY4 AAYXX CITATION
ID	FETCH-LOGICAL-c471t-5570a524d574d5beb5045b23a09d21f12449f282d6a385320ecd75f909e384bd3
IEDL.DBID	RIE
ISICitedReferencesCount	86
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000359253600039&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1524-9050
IngestDate	Tue Nov 18 22:28:57 EST 2025 Sat Nov 29 06:34:49 EST 2025 Tue Aug 26 16:39:28 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	4
Keywords	multi objective particle swarm optimization (MOPSO) train load variations subway systems Communication-based train control (CBTC) uncertainty energy saving train operation
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c471t-5570a524d574d5beb5045b23a09d21f12449f282d6a385320ecd75f909e384bd3
PageCount	11
ParticipantIDs	crossref_primary_10_1109_TITS_2015_2391831 crossref_citationtrail_10_1109_TITS_2015_2391831 ieee_primary_7045494
PublicationCentury	2000
PublicationDate	2015-08-01
PublicationDateYYYYMMDD	2015-08-01
PublicationDate_xml	– month: 08 year: 2015 text: 2015-08-01 day: 01
PublicationDecade	2010
PublicationTitle	IEEE transactions on intelligent transportation systems
PublicationTitleAbbrev	TITS
PublicationYear	2015
Publisher	IEEE
Publisher_xml	– name: IEEE
References	ref13 ref12 ref59 ref15 ref58 ref14 ref53 ref52 ref11 ref54 ref10 lin (ref55) 0 ref17 ref16 ref19 ref18 de cuadra (ref44) 1996; 1 ref50 chuang (ref40) 0 ref46 ref45 ref48 ref47 ref42 ref41 ref43 ref49 ref8 (ref51) 1999 ref7 ref9 ref4 ref3 ref6 ref5 kennedy (ref56) 2001 ref35 ref34 ref37 ref36 ref31 ref30 ref33 ref32 ref2 ref1 ref39 ref38 deb (ref57) 2005; 3410 ref23 ref26 ref25 ref20 ko (ref24) 2004 ref22 ref21 ref28 ref27 ref29 ref60
References_xml	– ident: ref30 doi: 10.1049/iet-epa:20070005 – ident: ref34 doi: 10.1002/tee.21782 – ident: ref59 doi: 10.1109/ICNN.1995.488968 – ident: ref27 doi: 10.1109/TITS.2013.2244885 – ident: ref47 doi: 10.1109/TITS.2013.2266255 – ident: ref36 doi: 10.1109/CEC.2003.1299816 – ident: ref2 doi: 10.1016/j.engappai.2008.03.008 – ident: ref46 doi: 10.1061/(ASCE)TE.1943-5436.0000550 – ident: ref50 doi: 10.1177/09544097JRRT420 – ident: ref11 doi: 10.1016/S0952-1976(00)00027-0 – year: 1999 ident: ref51 – ident: ref12 doi: 10.1109/TITS.2014.2366495 – ident: ref33 doi: 10.1016/j.engappai.2013.07.015 – ident: ref41 doi: 10.1049/iet-epa:20070381 – ident: ref32 doi: 10.1109/TITS.2012.2234118 – ident: ref16 doi: 10.1016/j.sbspro.2013.10.606 – ident: ref5 doi: 10.1177/0954409711429411 – ident: ref18 doi: 10.1109/TITS.2013.2285737 – ident: ref23 doi: 10.1109/9.867018 – ident: ref45 doi: 10.1049/ip-epa:20040346 – ident: ref29 doi: 10.1049/ic.2010.0038 – ident: ref20 doi: 10.1109/ACC.2011.5991057 – ident: ref58 doi: 10.1145/1068009.1068047 – year: 2004 ident: ref24 publication-title: Application of Dynamic Programming to the Optimization of the Running Profile of a Train – ident: ref54 doi: 10.1049/iet-its.2010.0144 – ident: ref14 doi: 10.1016/j.epsr.2011.08.004 – ident: ref4 doi: 10.1109/TITS.2014.2303146 – ident: ref42 doi: 10.1007/s12239-013-0099-7 – ident: ref8 doi: 10.1109/TASE.2011.2160537 – ident: ref19 doi: 10.1109/TIA.2014.2312538 – ident: ref35 doi: 10.1080/00207720412331203633 – ident: ref21 doi: 10.1109/CDC.2000.914108 – ident: ref31 doi: 10.1016/j.engappai.2012.02.006 – volume: 3410 start-page: 150 year: 2005 ident: ref57 article-title: Searching for robust pareto-optimal solutions in multi-objective optimization publication-title: Evolutionary Multi-Criterion Optimization doi: 10.1007/978-3-540-31880-4_11 – ident: ref43 doi: 10.1109/TITS.2013.2292712 – year: 2001 ident: ref56 publication-title: Swarm Intelligence – ident: ref39 doi: 10.1109/TIA.2009.2031898 – ident: ref25 doi: 10.1002/tee.20528 – ident: ref53 doi: 10.1109/CSIE.2009.323 – ident: ref7 doi: 10.1109/TVT.2012.2187225 – ident: ref49 doi: 10.1016/j.engappai.2013.12.015 – ident: ref48 doi: 10.1243/09544097F00505 – ident: ref17 doi: 10.1016/j.enconman.2014.01.060 – ident: ref22 doi: 10.1109/TITS.2013.2296655 – ident: ref60 doi: 10.1109/ICSMC.1997.637339 – ident: ref15 doi: 10.1109/TITS.2014.2319233 – ident: ref37 doi: 10.1016/j.omega.2011.12.001 – volume: 1 year: 1996 ident: ref44 article-title: Energy-saving automatic optimisation of train speed commands using direct search techniques publication-title: Computers Railways V-Railway Systems Management – start-page: 1 year: 0 ident: ref55 article-title: Adaptive critic design of automatic train regulation of MRT system publication-title: Proc IEEE ICIT – ident: ref1 doi: 10.1155/2013/156548 – ident: ref52 doi: 10.1109/ITSC.2011.6082964 – ident: ref28 doi: 10.1016/j.trc.2013.01.007 – ident: ref38 doi: 10.1016/j.trb.2014.03.006 – ident: ref13 doi: 10.1109/TASE.2012.2201148 – ident: ref6 doi: 10.1109/TITS.2012.2219620 – ident: ref26 doi: 10.1061/(ASCE)TE.1943-5436.0000483 – ident: ref3 doi: 10.1155/2013/643274 – ident: ref9 doi: 10.1049/iet-est.2010.0074 – start-page: 2833 year: 0 ident: ref40 article-title: Design of optimal coasting speed for saving social cost in mass rapid transit systems publication-title: Proc 3rd Int Conf Elect Utility DRPT – ident: ref10 doi: 10.1016/0165-0114(94)90109-0
SSID	ssj0014511
Score	2.4718194
Snippet	Metropolitan railway operators' strategic plans include nowadays actions to reduce energy consumption. The application of ecodriving initiatives in lines...
SourceID	crossref ieee
SourceType	Enrichment Source Index Database Publisher
StartPage	2061
SubjectTerms	Communication-based train control (CBTC) Delays Energy consumption energy saving Linear programming multi objective particle swarm optimization (MOPSO) Optimization Particle swarm optimization Robustness subway systems train load variations train operation Uncertainty
Title	Design of Robust and Energy-Efficient ATO Speed Profiles of Metropolitan Lines Considering Train Load Variations and Delays
URI	https://ieeexplore.ieee.org/document/7045494
Volume	16
WOSCitedRecordID	wos000359253600039&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1558-0016 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0014511 issn: 1524-9050 databaseCode: RIE dateStart: 20000101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3dS8MwED-m-KAPfk3xmzz4JHZmbbI0j6IThTnFVdlbSZoUBFnH1gniP28u7YaCCD4USskdbS7lcrm73w_glLsfiCuug5ybTsBiZgLZETkWUzFlNDMd7XFme6Lfj4dD-diA80UvjLXWF5_ZFt76XL4pshkelV0IxIuTbAmWhBBVr9YiY4A4Wx4bNWSBpHyewWxTeZHcJQMs4uKtMJJuCbd_-KBvpCrep9xs_O9tNmG93juSy8rYW9Cwo21Y-4Yo2ITPa1-RQYqcPBV6Ni2JGhnS9Q1-QdfDRTil5DJ5IIOxc1zkseLsnqLEvS09Z8Kr2zCSHtbDkzmfp1NOEmSTIL1CGfLiIuzqqM_rv7Zv6mO6A8833eTqNqj5FYLMuaQyQPQt5ebLcOEubTV3X6TDSFFpwnaOnl_mLiQzHRXFSCBhMyN4Lqm0Ucy0iXZheVSM7B4QF7XlNotDbalhVCuFLOEi5oq67QpTeh_ofMbTrAYfRw6Mt9QHIVSmaKQUjZTWRtqHs4XIuELe-GtwEw20GFjb5uD3x4ewisJVHd8RLJeTmT2Gley9fJ1OTvy6-gJhtspV
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3dS8MwED_mB6gPfovf5sEnsS5rk7V5FJ0o1ilaxbeSNCkMxiquE8R_3lzajQki-FAoJTnaXMrd5e5-P4Bjbn8gLrnycq7bHouY9kQ7zLGYikmtmG4rhzMbh91u9PoqHhpwOumFMca44jNzhrcul6-LbIRHZc0Q8eIEm4E5zpjfqrq1JjkDRNpy6Kg-8wTl4xxmi4pmcpM8YRkXP_MDYTdx64cVmqJVcVblauV_77MKy7X3SM4rda9BwwzWYWkKU3ADvi5dTQYpcvJYqNGwJHKgSce1-HkdBxhhhZLz5J48vVnTRR4q1u4hzrgzpWNN6FmXkcRYEU_GjJ5WOEmQT4LEhdTkxcbY1WGfk39p-vJzuAnPV53k4tqrGRa8zBql0kP8LWnXS_PQXsoobr9I-YGkQvutHG2_yG1QptsyiJBCwmQ65LmgwgQRUzrYgtlBMTDbQGzclpss8pWhmlElJfKEhxGX1DosTKodoOMVT7MafhxZMPqpC0OoSFFJKSoprZW0AyeTKW8V9sZfgzdQQZOBtW52f398BAvXyV2cxjfd2z1YREFVVd8-zJbvI3MA89lH2Ru-H7o99g0SH82c
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Design+of+Robust+and+Energy-Efficient+ATO+Speed+Profiles+of+Metropolitan+Lines+Considering+Train+Load+Variations+and+Delays&rft.jtitle=IEEE+transactions+on+intelligent+transportation+systems&rft.au=Fernandez-Rodriguez%2C+Adrian&rft.au=Fernandez-Cardador%2C+Antonio&rft.au=Cucala%2C+Asuncion+P.&rft.au=Dominguez%2C+Maria&rft.date=2015-08-01&rft.issn=1524-9050&rft.eissn=1558-0016&rft.volume=16&rft.issue=4&rft.spage=2061&rft.epage=2071&rft_id=info:doi/10.1109%2FTITS.2015.2391831&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_TITS_2015_2391831
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1524-9050&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1524-9050&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1524-9050&client=summon