The Path Inference Filter: Model-Based Low-Latency Map Matching of Probe Vehicle Data

We consider the problem of reconstructing vehicle trajectories from sparse sequences of GPS points, for which the sampling interval is between 1 s and 2 min. We introduce a new class of algorithms, which are altogether called the path inference filter (PIF), that maps GPS data in real time, for a va...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on intelligent transportation systems Ročník 15; číslo 2; s. 507 - 529
Hlavní autoři:	Hunter, Timothy, Abbeel, Pieter, Bayen, Alexandre
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.04.2014 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Expectation-maximization algorithms filtering Global Positioning System GPS data Inference Intelligent transportation systems Markov random fields Matching maximum likelihood estimation Mobile communication network-free data path observation generation probabilistic map matching Probability distribution Probes Real time Roads route choice modeling Sampling State of the art Traffic information Trajectory Vehicles San Francisco California route choice modeling GPS data path observation generation network-free data probabilistic map matching Expectation-maximization algorithms filtering maximum likelihood estimation Markov random fields
ISSN:	1524-9050, 1558-0016
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	We consider the problem of reconstructing vehicle trajectories from sparse sequences of GPS points, for which the sampling interval is between 1 s and 2 min. We introduce a new class of algorithms, which are altogether called the path inference filter (PIF), that maps GPS data in real time, for a variety of tradeoffs and scenarios and with a high throughput. Numerous prior approaches in map matching can be shown to be special cases of the PIF presented in this paper. We present an efficient procedure for automatically training the filter on new data, with or without ground-truth observations. The framework is evaluated on a large San Francisco taxi data set and is shown to improve upon the current state of the art. This filter also provides insights about driving patterns of drivers. The PIF has been deployed at an industrial scale inside the Mobile Millennium traffic information system, and is used to map fleets of data in San Francisco and Sacramento, CA, USA; Stockholm, Sweden; and Porto, Portugal.
AbstractList	We consider the problem of reconstructing vehicle trajectories from sparse sequences of GPS points, for which the sampling interval is between 1 s and 2 min. We introduce a new class of algorithms, which are altogether called the path inference filter (PIF), that maps GPS data in real time, for a variety of tradeoffs and scenarios and with a high throughput. Numerous prior approaches in map matching can be shown to be special cases of the PIF presented in this paper. We present an efficient procedure for automatically training the filter on new data, with or without ground-truth observations. The framework is evaluated on a large San Francisco taxi data set and is shown to improve upon the current state of the art. This filter also provides insights about driving patterns of drivers. The PIF has been deployed at an industrial scale inside the Mobile Millennium traffic information system, and is used to map fleets of data in San Francisco and Sacramento, CA, USA; Stockholm, Sweden; and Porto, Portugal.
Author	Hunter, Timothy Abbeel, Pieter Bayen, Alexandre
Author_xml	– sequence: 1 givenname: Timothy surname: Hunter fullname: Hunter, Timothy email: tjhunter@eecs.berkeley.edu organization: Dept. of Electr. Eng. & Comput. Sci., Univ. of California at Berkeley, Berkeley, CA, USA – sequence: 2 givenname: Pieter surname: Abbeel fullname: Abbeel, Pieter email: pabbeel@cs.berkeley.edu organization: Dept. of Electr. Eng. & Comput. Sci., Univ. of California at Berkeley, Berkeley, CA, USA – sequence: 3 givenname: Alexandre surname: Bayen fullname: Bayen, Alexandre email: bayen@berkeley.edu organization: Dept. of Electr. Eng. & Comput. Sci., Univ. of California at Berkeley, Berkeley, CA, USA
BookMark	eNp9kU1rGzEQhkVIIYnbHxByEfTSy7oaSbur7a1N82FwSCB2r0I7nq1l1itXkin591nj0EMOPYgRM-87MzxzwU6HMBBjlyCmAKL5upgtnqdSgJpKaaQq5Qk7h7I0hRBQnR7-UheNKMUZu0hpM2Z1CXDOlos18SeX13w2dBRpQOK3vs8Uv_GHsKK--OESrfg8_C3mLo_1F_7gduPLuPbDbx46_hRDS_wXrT32xH-67D6yD53rE316ixO2vL1ZXN8X88e72fX3eYGqkblA2TrRtq3WQtcNOtEg1KoFp5UUqtaIzhkk6mrVAcjWCNRVq9GgNooA1YR9OfbdxfBnTynbrU9Ife8GCvtkoaoaU0ItzCj9_E66Cfs4jNtZKEErZWCkN2FwVGEMKUXq7C76rYsvFoQ9gLYH0PYA2r6BHj31Ow_67LIPQ47O9_91Xh2dnoj-TaoqLcdDqVfAdIrk
CODEN	ITISFG
CitedBy_id	crossref_primary_10_1111_mice_12595 crossref_primary_10_1016_j_compag_2023_108529 crossref_primary_10_1016_j_ins_2019_10_060 crossref_primary_10_1109_TITS_2021_3058123 crossref_primary_10_1109_LRA_2019_2891488 crossref_primary_10_1080_21680566_2020_1852128 crossref_primary_10_1109_TITS_2018_2812147 crossref_primary_10_1016_j_heliyon_2023_e21368 crossref_primary_10_1007_s11116_016_9734_2 crossref_primary_10_1080_13658816_2015_1086922 crossref_primary_10_1109_TRO_2020_3046419 crossref_primary_10_1109_TITS_2017_2647967 crossref_primary_10_3390_ijgi5110204 crossref_primary_10_9728_dcs_2025_26_8_2191 crossref_primary_10_3390_aerospace12080721 crossref_primary_10_1109_TITS_2018_2883217 crossref_primary_10_3390_su132011450 crossref_primary_10_1109_LRA_2021_3056032 crossref_primary_10_1109_ACCESS_2024_3432590 crossref_primary_10_1016_j_ress_2021_108090 crossref_primary_10_1109_JSYST_2022_3150267 crossref_primary_10_1016_j_trc_2022_103707 crossref_primary_10_1016_j_trc_2019_09_019 crossref_primary_10_1109_TITS_2014_2357835 crossref_primary_10_1109_TITS_2017_2697439 crossref_primary_10_1109_MITS_2017_2709804 crossref_primary_10_1109_TITS_2023_3346649 crossref_primary_10_1016_j_trc_2016_10_011 crossref_primary_10_1016_j_neucom_2020_07_150 crossref_primary_10_1080_13658816_2015_1049540 crossref_primary_10_1109_TITS_2023_3280114 crossref_primary_10_1145_3130800_3130847 crossref_primary_10_1016_j_artint_2018_12_008 crossref_primary_10_1109_TCCN_2019_2961660 crossref_primary_10_1145_3329676 crossref_primary_10_1016_j_trc_2018_05_013 crossref_primary_10_3390_ijgi10050333 crossref_primary_10_1111_mice_12251 crossref_primary_10_3390_s20185143 crossref_primary_10_4018_IJWSR_306243 crossref_primary_10_3390_su132212820 crossref_primary_10_1109_TITS_2016_2604484 crossref_primary_10_1109_MITS_2018_2806630 crossref_primary_10_1109_ACCESS_2019_2958982 crossref_primary_10_1186_s12544_021_00516_z crossref_primary_10_1109_TITS_2021_3113710 crossref_primary_10_1109_TITS_2014_2353302 crossref_primary_10_1177_03611981241283461 crossref_primary_10_1109_JSAC_2023_3322841 crossref_primary_10_1007_s10586_017_0869_5 crossref_primary_10_1016_j_trc_2019_10_001 crossref_primary_10_1016_j_trc_2023_104283 crossref_primary_10_1109_TITS_2014_2331758 crossref_primary_10_1049_iet_its_2018_0007 crossref_primary_10_1109_TITS_2017_2743206 crossref_primary_10_1016_j_trc_2020_01_023 crossref_primary_10_1177_1550147719830552 crossref_primary_10_1080_21680566_2017_1353449 crossref_primary_10_1109_TKDE_2023_3287739 crossref_primary_10_1016_j_eswa_2017_08_027 crossref_primary_10_3233_JIFS_202292 crossref_primary_10_3390_s22010247 crossref_primary_10_1016_j_trc_2017_10_012 crossref_primary_10_1007_s11831_023_09962_5 crossref_primary_10_1109_TITS_2018_2867834 crossref_primary_10_1016_j_trc_2021_103265 crossref_primary_10_1016_j_trc_2018_03_004 crossref_primary_10_1016_j_trc_2015_07_003 crossref_primary_10_1016_j_trpro_2024_12_045 crossref_primary_10_1109_TITS_2021_3077904 crossref_primary_10_3390_s17030550
Cites_doi	10.1145/2038916.2038944 10.1109/SSDBM.2006.11 10.1109/78.978396 10.1145/1869983.1869993 10.1007/s10291-003-0069-z 10.1109/ITSC.2004.1398868 10.1109/CDC.2008.4739016 10.1109/ITSC.2012.6338641 10.1109/TRA.2002.807557 10.1016/j.trc.2010.06.001 10.1016/j.trc.2007.05.002 10.1016/S0968-090X(00)00026-7 10.1016/j.trc.2012.08.001 10.1007/BF00263991 10.1109/MDM.2010.14 10.1016/j.trc.2007.07.007 10.1109/PROC.1973.9030 10.1109/TSSC.1968.300136 10.1017/CBO9780511804441 10.1007/s10514-005-0609-1 10.1145/1378600.1378604 10.1109/TITS.2012.2187196 10.1109/TITS.2012.2200474 10.1145/504729.504754 10.1145/1644038.1644048 10.1109/79.543975
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Apr 2014
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Apr 2014
DBID	97E RIA RIE AAYXX CITATION 7SC 7SP 8FD FR3 JQ2 KR7 L7M L~C L~D 7TB F28
DOI	10.1109/TITS.2013.2282352
DatabaseName	IEEE Xplore (IEEE) IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Technology Research Database Engineering Research Database ProQuest Computer Science Collection Civil Engineering Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Mechanical & Transportation Engineering Abstracts ANTE: Abstracts in New Technology & Engineering
DatabaseTitle	CrossRef Civil Engineering Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Engineering Research Database Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional Mechanical & Transportation Engineering Abstracts ANTE: Abstracts in New Technology & Engineering
DatabaseTitleList	Civil Engineering Abstracts Civil Engineering Abstracts
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	529
ExternalDocumentID	3271246031 10_1109_TITS_2013_2282352 6642050
Genre	orig-research
GeographicLocations	San Francisco California
GeographicLocations_xml	– name: San Francisco California
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 7SC 7SP 8FD FR3 JQ2 KR7 L7M L~C L~D 7TB F28
ID	FETCH-LOGICAL-c392t-c2ba0bbb440479ca09c173b1a4320374ccaa8ceef73f112b80c46b4c8c483e1c3
IEDL.DBID	RIE
ISICitedReferencesCount	91
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000334584800005&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	Sun Nov 23 09:52:14 EST 2025 Sun Nov 09 06:41:42 EST 2025 Sat Nov 29 06:34:48 EST 2025 Tue Nov 18 22:18:25 EST 2025 Tue Aug 26 16:49:59 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	2
Keywords	route choice modeling GPS data path observation generation network-free data probabilistic map matching Expectation-maximization algorithms filtering maximum likelihood estimation Markov random fields
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c392t-c2ba0bbb440479ca09c173b1a4320374ccaa8ceef73f112b80c46b4c8c483e1c3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
PQID	1514338101
PQPubID	75735
PageCount	23
ParticipantIDs	crossref_primary_10_1109_TITS_2013_2282352 ieee_primary_6642050 crossref_citationtrail_10_1109_TITS_2013_2282352 proquest_miscellaneous_1669851708 proquest_journals_1514338101
PublicationCentury	2000
PublicationDate	2014-04-01
PublicationDateYYYYMMDD	2014-04-01
PublicationDate_xml	– month: 04 year: 2014 text: 2014-04-01 day: 01
PublicationDecade	2010
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationTitle	IEEE transactions on intelligent transportation systems
PublicationTitleAbbrev	TITS
PublicationYear	2014
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref13 ref12 lafferty (ref24) 2001 ref14 ref33 ref32 ref10 schrank (ref35) 2009 greenfeld (ref16) 0 ref39 seymore (ref36) 1999 ref17 bayen (ref2) 2011 (ref9) 0 ref19 ref18 zheng (ref48) 0 (ref1) 0 murphy (ref28) 1994 miwa (ref26) 2004; 2 brakatsoulas (ref8) 2005 bilmes (ref6) 1998; 4 downs (ref11) 2004 pyo (ref31) 2001 rogers (ref34) 2000 ref46 ref45 ref47 ref20 ref42 ref41 ref22 ref44 ref21 ref43 (ref38) 0 liu (ref25) 2008; 6 giovannini (ref15) 2011 ref27 ochieng (ref30) 2003; 55 (ref29) 0 ref7 ref4 ref3 ref5 ref40 syed (ref37) 2004; 1 (ref23) 0
References_xml	– ident: ref22 doi: 10.1145/2038916.2038944 – volume: 4 start-page: 1 year: 1998 ident: ref6 article-title: A gentle tutorial of the EM algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models publication-title: Int Comput Sci Inst – start-page: 853 year: 2005 ident: ref8 article-title: On map-matching vehicle tracking data publication-title: Proc Int Conf On Very Large Data Bases – ident: ref43 doi: 10.1109/SSDBM.2006.11 – ident: ref17 doi: 10.1109/78.978396 – ident: ref39 doi: 10.1145/1869983.1869993 – ident: ref33 doi: 10.1007/s10291-003-0069-z – start-page: 37 year: 1999 ident: ref36 article-title: Learning hidden Markov model structure for information extraction publication-title: Proc AAAI Workshop Mach Learning Inf Extraction – ident: ref12 doi: 10.1109/ITSC.2004.1398868 – year: 2004 ident: ref11 publication-title: Still stuck in traffic Coping with peak-hour traffic congestion – ident: ref45 doi: 10.1109/CDC.2008.4739016 – ident: ref19 doi: 10.1109/ITSC.2012.6338641 – year: 0 ident: ref38 publication-title: Telenav Inc – ident: ref10 doi: 10.1109/TRA.2002.807557 – ident: ref47 doi: 10.1016/j.trc.2010.06.001 – ident: ref32 doi: 10.1016/j.trc.2007.05.002 – volume: 1 start-page: 982 year: 2004 ident: ref37 article-title: Fuzzy logic-based map matching algorithm for vehicle navigation system in urban canyons publication-title: Proc ION Nat Tech Meeting – ident: ref44 doi: 10.1016/S0968-090X(00)00026-7 – ident: ref4 doi: 10.1016/j.trc.2012.08.001 – year: 1994 ident: ref28 publication-title: Dynamic Bayesian Networks Representation Inference and Learning – ident: ref3 doi: 10.1007/BF00263991 – ident: ref46 doi: 10.1109/MDM.2010.14 – year: 2011 ident: ref15 publication-title: A Novel Map-matching Procedure for Low-sampling Gps Data with Applicatins to Traffic Flow Analysis – ident: ref5 doi: 10.1016/j.trc.2007.07.007 – ident: ref14 doi: 10.1109/PROC.1973.9030 – ident: ref18 doi: 10.1109/TSSC.1968.300136 – start-page: 125 year: 2000 ident: ref34 article-title: Creating and evaluating highly accurate maps with probe vehicles publication-title: Proc IEEE Intell Transp Syst – ident: ref7 doi: 10.1017/CBO9780511804441 – volume: 6 start-page: 29 year: 2008 ident: ref25 article-title: Study on the cost-effectiveness of a probe vehicle system at lower polling frequencies publication-title: Int'l J ITS Research – volume: 2 start-page: 21 year: 2004 ident: ref26 article-title: Route identification and travel time prediction using probe-car data publication-title: Int J – year: 0 ident: ref1 publication-title: Supporting Code for the Path Inference Filter – year: 0 ident: ref48 article-title: Weight-based shortest-path aided map-matching algorithm for low-frequency positioning data – year: 2011 ident: ref2 publication-title: Mobile millennium final report – ident: ref13 doi: 10.1007/s10514-005-0609-1 – ident: ref21 doi: 10.1145/1378600.1378604 – year: 0 ident: ref29 publication-title: NAVTEQ Inc – ident: ref42 doi: 10.1109/TITS.2012.2187196 – year: 0 ident: ref23 publication-title: Inrix Inc – start-page: 282 year: 2001 ident: ref24 article-title: Conditional random fields: Probabilistic models for segmenting and labeling sequence data publication-title: Proc 18th ICML – year: 2009 ident: ref35 publication-title: 2009 urban mobility report – volume: 55 start-page: 1 year: 2003 ident: ref30 article-title: Map-matching in complex urban road networks publication-title: Revista Brasileira de Cartografia – ident: ref20 doi: 10.1109/TITS.2012.2200474 – year: 0 ident: ref16 article-title: Matching GPS observations to locations on a digital map – ident: ref41 doi: 10.1145/504729.504754 – year: 0 ident: ref9 publication-title: The Cabspotting Program – ident: ref40 doi: 10.1145/1644038.1644048 – ident: ref27 doi: 10.1109/79.543975 – start-page: 23 year: 2001 ident: ref31 article-title: Development of a map matching method using the multiple hypothesis technique publication-title: Proc IEEE Intell Transp Syst
SSID	ssj0014511
Score	2.4313064
Snippet	We consider the problem of reconstructing vehicle trajectories from sparse sequences of GPS points, for which the sampling interval is between 1 s and 2 min....
SourceID	proquest crossref ieee
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	507
SubjectTerms	Algorithms Expectation-maximization algorithms filtering Global Positioning System GPS data Inference Intelligent transportation systems Markov random fields Matching maximum likelihood estimation Mobile communication network-free data path observation generation probabilistic map matching Probability distribution Probes Real time Roads route choice modeling Sampling State of the art Traffic information Trajectory Vehicles
Title	The Path Inference Filter: Model-Based Low-Latency Map Matching of Probe Vehicle Data
URI	https://ieeexplore.ieee.org/document/6642050 https://www.proquest.com/docview/1514338101 https://www.proquest.com/docview/1669851708
Volume	15
WOSCitedRecordID	wos000334584800005&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/eLvHCXMwlV3fS-QwEB5UfPAevPMXrqdHDnwSo-kmNsm9nXcuCnuy4Cq-lSSboiBb0a7if-9MtlsE5cCHlkKnSckknS-dmW8AdqPJvfLKcamC58pGw_0IT1bpUhpldUhkz1d9fX5urq_tYA7221yYGGMKPosHdJl8-aMqTOhX2WGOYFnQBn1eaz3N1Wo9BsSzlbhRu4pbFGo8mJmwh8Oz4QUFccmDLm4wUo7RGxuUiqq8-xIn89L7-rkX-wbLDYxkv6d6X4G5OF6FL2_IBdfgEmcAGyDAY2ezpD7WuyXn-C9GFdDu-DFasBHrV8-87wg6v7B_7h6POsVXsqpkA0oWYlfxhnphf13t1uGydzL8c8qbIgo8IPSpeeh6J7z3xAOobXDChkxLnzklu8Q9gxp0Bi1lqWWJ2MsbERSqL5igjIxZkBuwMK7GcRNYboTPjYkBm1BlkC6KKEcuM-FIa5PpDojZsBahYRinQhd3RdppCFuQJgrSRNFoogN77SP3U3qN_wmv0dC3gs2od2B7pruiWYCPRUZAMLGXdeBnexuXDvlD3DhWE5TJc4uAUwuz9XHL32EJ-28CdbZhoX6YxB1YDE_17ePDjzT_XgG_-NYK
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3fa9swED5KV9j2sHXryrJ1qwp9GlMrW6ol7W0_GhrmhkDT0jcjKTIrlLi0zsb--90pjil0DPZgY_BZFjrJ98l39x3AfjSFV145LlXwXNlouJ_hySpdS6OsDons-aLU47G5vLSTNfjY58LEGFPwWTygy-TLnzVhQb_KDgsEy4I26I-OlMqzZbZW7zMgpq3EjporblGs82Fmwh5OR9MzCuOSBzluMVKW0T0rlMqqPPgWJwMzfP5_XduEZx2QZJ-Xmn8Ba3H-Ep7eoxfcgnOcA2yCEI-NVml9bHhF7vFPjGqgXfMvaMNmrGx-8dIReP7NTt0NHm2KsGRNzSaULsQu4g96C_vmWvcKzofH068nvCujwAOCn5aH3DvhvScmQG2DEzZkWvrMKZkT-wzq0Bm0lbWWNaIvb0RQqMBggjIyZkFuw_q8mcfXwAojfGFMDNiEqoN0UUQ5c5kJR1qbTA9ArIa1Ch3HOJW6uK7SXkPYijRRkSaqThMD-NA_crMk2PiX8BYNfS_YjfoAdla6q7oleFdlBAUTf9kA9vrbuHjII-LmsVmgTFFYhJxamDd_b3kXHp9MT8uqHI2_v4Un2JcubGcH1tvbRXwHG-Fne3V3-z7NxT8MINlR
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=The+Path+Inference+Filter%3A+Model-Based+Low-Latency+Map+Matching+of+Probe+Vehicle+Data&rft.jtitle=IEEE+transactions+on+intelligent+transportation+systems&rft.au=Hunter%2C+Timothy&rft.au=Abbeel%2C+Pieter&rft.au=Bayen%2C+Alexandre&rft.date=2014-04-01&rft.issn=1524-9050&rft.eissn=1558-0016&rft.volume=15&rft.issue=2&rft.spage=507&rft.epage=529&rft_id=info:doi/10.1109%2FTITS.2013.2282352&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_TITS_2013_2282352
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