{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T23:31:15Z","timestamp":1782948675855,"version":"3.54.5"},"reference-count":35,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,21]],"date-time":"2021-12-21T00:00:00Z","timestamp":1640044800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Transport agencies require accurate and updated information about public transport systems for the optimal decision-making processes regarding design and operation. In addition to assessing topology and service components, users\u2019 behaviors must be considered. To this end, a data-driven performance evaluation based on passengers\u2019 actual routes is key. Automatic fare collection platforms provide meaningful smart card data (SCD), but these are incomplete when gathered by entry-only systems. To obtain origin\u2013destination (OD) matrices, we must manage complete journeys. In this paper, we use an adapted trip chaining method to reconstruct incomplete multi-modal journeys by finding spatial similarities between the outbound and inbound routes of the same user. From this dataset, we develop a performance evaluation framework that provides novel metrics and visualization utilities. First, we generate a space-time characterization of the overall operation of transport networks. Second, we supply enhanced OD matrices showing mobility patterns between zones and average traversed distances, travel times, and operation speeds, which model the real efficacy of the public transport system. We applied this framework to the Comunidad de Madrid (Spain), using 4 months\u2019 worth of real SCD, showing its potential to generate meaningful information about the performance of multi-modal public transport systems.<\/jats:p>","DOI":"10.3390\/s22010017","type":"journal-article","created":{"date-parts":[[2021,12,21]],"date-time":"2021-12-21T09:50:43Z","timestamp":1640080243000},"page":"17","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Data-Driven Performance Evaluation Framework for Multi-Modal Public Transport Systems"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0023-9607","authenticated-orcid":false,"given":"Ana Bel\u00e9n","family":"Rodr\u00edguez Gonz\u00e1lez","sequence":"first","affiliation":[{"name":"Group Biometry, Biosignals, Security, and Smart Mobility, Departamento de Matem\u00e1tica Aplicada a las Tecnolog\u00edas de la Informaci\u00f3n y las Comunicaciones, Escuela T\u00e9cnica Superior de Ingenieros de Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Avenida Complutense 30, 28040 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1283-0311","authenticated-orcid":false,"given":"Juan Jos\u00e9","family":"Vinagre D\u00edaz","sequence":"additional","affiliation":[{"name":"Group Biometry, Biosignals, Security, and Smart Mobility, Departamento de Matem\u00e1tica Aplicada a las Tecnolog\u00edas de la Informaci\u00f3n y las Comunicaciones, Escuela T\u00e9cnica Superior de Ingenieros de Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Avenida Complutense 30, 28040 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0062-2948","authenticated-orcid":false,"given":"Mark R.","family":"Wilby","sequence":"additional","affiliation":[{"name":"Group Biometry, Biosignals, Security, and Smart Mobility, Departamento de Matem\u00e1tica Aplicada a las Tecnolog\u00edas de la Informaci\u00f3n y las Comunicaciones, Escuela T\u00e9cnica Superior de Ingenieros de Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Avenida Complutense 30, 28040 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7306-8450","authenticated-orcid":false,"given":"Rub\u00e9n","family":"Fern\u00e1ndez Pozo","sequence":"additional","affiliation":[{"name":"Group Biometry, Biosignals, Security, and Smart Mobility, Departamento de Matem\u00e1tica Aplicada a las Tecnolog\u00edas de la Informaci\u00f3n y las Comunicaciones, Escuela T\u00e9cnica Superior de Ingenieros de Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Avenida Complutense 30, 28040 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Mulley, C., Nelson, J.D., and Ison, S. (2021). Public transport evaluation. The Routledge Handbook of Public Transport, Taylor and Francis Group. Chapter 11.","DOI":"10.4324\/9780367816698"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/s12061-015-9177-8","article-title":"Measuring the Accessibility of Public Transport: A Critical Comparison between Methods in Helsinki","volume":"10","author":"Albacete","year":"2017","journal-title":"Appl. Spat. Anal. Policy"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/S0967-070X(02)00011-2","article-title":"An introduction to road vulnerability: What has been done, is done and should be done","volume":"9","author":"Berdica","year":"2002","journal-title":"Transp. Policy"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1016\/j.trc.2018.08.006","article-title":"A robust method for estimating transit passenger trajectories using automated data","volume":"95","author":"Kumar","year":"2018","journal-title":"Transp. Res. C Emerg. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"183","DOI":"10.3141\/1817-24","article-title":"Origin and destination estimation in New York City with Automated Fare System data","volume":"1817","author":"Barry","year":"2002","journal-title":"Transp. Res. Rec. J. Transp. Res. Board"},{"key":"ref_6","unstructured":"Scheurer, J., and Silva, C. (2010, January 7\u201310). Refining Accessibility Tools: SAL and SNAMUTS for Porto. Proceedings of the 24th AESOP Congress, Helsinki, Finland."},{"key":"ref_7","first-page":"93","article-title":"Performance measures for public transport accessibility: Learning from international practice","volume":"10","author":"Curtis","year":"2017","journal-title":"J. Transp. Land Use"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"102919","DOI":"10.1016\/j.jtrangeo.2020.102919","article-title":"Public transport accessibility accounting for level of service and competition for urban opportunities: An equity analysis for education in Santiago de Chile","volume":"90","author":"Hurtubia","year":"2021","journal-title":"J. Transp. Geogr."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1007\/s11067-014-9237-7","article-title":"Dynamic Vulnerability Analysis of Public Transport Networks: Mitigation Effects of Real-Time Information","volume":"14","author":"Cats","year":"2014","journal-title":"Netw. Spat. Econ."},{"key":"ref_10","first-page":"1","article-title":"Exposing the orle of exposure: Public transport network risk analysis","volume":"88","author":"Cats","year":"2016","journal-title":"Transp. Res. Part A"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.jtrangeo.2014.01.008","article-title":"Measuring the vulnerability of public transport networks","volume":"35","year":"2014","journal-title":"J. Transp. Geogr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/0270-0255(87)90473-8","article-title":"The analytic hierarchy process\u2014What is it and how it is used","volume":"9","author":"Saaty","year":"1987","journal-title":"Math. Model."},{"key":"ref_13","first-page":"5","article-title":"Developing a performance importance matrix for a public sector bus transport company: A case study","volume":"6","author":"Sezhian","year":"2011","journal-title":"Theor. Empir. Res. Urban Manag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1007\/s11205-020-02284-0","article-title":"An Integrated Approach to Select Key Quality Indicators in Transit Services","volume":"149","author":"Barabino","year":"2020","journal-title":"Soc. Indic. Res."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Dey, S., Winter, S., and Tomko, M. (2020). Origin-Destination flow information from link count data. Sensors, 20.","DOI":"10.3390\/s20185226"},{"key":"ref_16","first-page":"57","article-title":"A Probability Model of Transit OD Distribution Based on the Allure of Bus Station","volume":"32","author":"Zhang","year":"2014","journal-title":"J. Trans. Inf. Saf."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1049\/iet-its.2016.0276","article-title":"Deep-learning architecture to forecast destinations of bus passengers from entryonly smart-card data","volume":"11","author":"Jung","year":"2017","journal-title":"IET Intell. Transp. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"53","DOI":"10.3141\/2112-07","article-title":"Use of entry-only Automatic Fare Collection data to estimate linked transit trips in New York City","volume":"2112","author":"Barry","year":"2009","journal-title":"Transp. Res. Rec. J. Transp. Res. Board"},{"key":"ref_19","unstructured":"Zhao, J. (2004). The Planning and Analysis Implications of Automated Data Collection Systems: Rail Transit OD Matrix Inference and Path Choice Modeling Examples, Massachusetts Institute of Technology."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1016\/j.trc.2010.12.003","article-title":"Smart card data use in public transit: A literature review","volume":"19","author":"Pelletier","year":"2011","journal-title":"Transp. Res. C Emerg. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Li, T., Sun, D., Jing, P., and Yang, K. (2018). Smart card data mining of public transport destination: A literature review. Information, 9.","DOI":"10.3390\/info9010018"},{"key":"ref_22","unstructured":"Cui, A. (2006). Bus Passenger Origin-Destination Matrix Estimation Using Automated Data Collection Systems. [Master\u2019s Thesis, Massachusetts Institute of Technology]."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1111\/j.1467-8667.2007.00494.x","article-title":"Estimating a rail passenger trip origin-destination matrix using automatic data collection systems","volume":"22","author":"Zhao","year":"2007","journal-title":"Comput. Aided Civil Infras. Eng."},{"key":"ref_24","unstructured":"Tr\u00e9panier, M., and Chapleau, R. (2006, January 17\u201319). Destination estimation from public transport smartcard data. Proceedings of the 12th IFAC Symposium on Information Control Problems in Manufacturing, St. Etienne, France."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"140","DOI":"10.3141\/2263-16","article-title":"Transit stop-level origin\u2013destination estimation through use of transit schedule and automated data collection system","volume":"2263","author":"Nassir","year":"2011","journal-title":"Transp. Res. Rec. J. Transp. Res. Board"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Li, D., Lin, Y., Zhao, X., Song, H., and Zou, N. (2011, January 22\u201325). Estimating a transit passenger trip origin-destination matrix using Automatic Fare Collection system. Proceedings of the 16th International Conference on Database Systems for Advanced Applications (DASFAA), Hong Kong, China.","DOI":"10.1007\/978-3-642-20244-5_48"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"131","DOI":"10.5038\/2375-0901.14.4.7","article-title":"Bus passenger origin-destination estimation and related analyses using automated data collection systems","volume":"14","author":"Wang","year":"2011","journal-title":"J. Public Transp."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.trc.2012.01.007","article-title":"Estimation of a disaggregate multimodal public transport origin-destination matrix from passive smartcard data from Santiago, Chile","volume":"24","author":"Munizaga","year":"2012","journal-title":"Transp. Res. C Emerg. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Briand, A.S., C\u00f4me, E., Mahrsi, M.K.E., and Oukhellou, L. (2015, January 19\u201321). A mixture model clustering approach for temporal passenger pattern characterization in public transport. Proceedings of the IEEE International Conference on Data Science and Advanced Analytics (DSAA), Paris, France.","DOI":"10.1109\/DSAA.2015.7344847"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1109\/TITS.2015.2464335","article-title":"Passenger journey destination estimation from automated Fare Collection System data using spatial validation","volume":"17","author":"Nunes","year":"2016","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"55","DOI":"10.3141\/2121-06","article-title":"Analyzing multimodal public transport journeys in London with smart card fare payment data","volume":"2121","author":"Seaborn","year":"2009","journal-title":"Transp. Res. Rec. J. Transp. Res. Board"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.trc.2016.05.004","article-title":"Validating and improving public transport origin\u2013destination estimation algorithm using smart card fare data","volume":"68","author":"Alsger","year":"2016","journal-title":"Transp. Res. C Emerg. Technol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3135","DOI":"10.1109\/TITS.2017.2679179","article-title":"Spatio-temporal analysis of passenger travel patterns in massive smart card data","volume":"18","author":"Zhao","year":"2017","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1140\/epjds\/s13688-018-0147-7","article-title":"Travelers or locals? Identifying meaningful sub-populations from human movement data in the absence of ground truth","volume":"7","author":"Scherrer","year":"2018","journal-title":"EPJ Data Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1007\/s12469-016-0137-8","article-title":"Identifying passenger flow characteristics and evaluating travel time reliability by visualizing AFC data: A case study of Shanghai Metro","volume":"8","author":"Sun","year":"2016","journal-title":"Public Transp."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/1\/17\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:50:38Z","timestamp":1760169038000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/1\/17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,21]]},"references-count":35,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["s22010017"],"URL":"https:\/\/doi.org\/10.3390\/s22010017","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,21]]}}}