{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T13:46:20Z","timestamp":1777902380363,"version":"3.51.4"},"reference-count":30,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2016,10,15]],"date-time":"2016-10-15T00:00:00Z","timestamp":1476489600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["SIMULATION"],"published-print":{"date-parts":[[2017,1]]},"abstract":"<jats:p>Efforts to address operational issues in transportation have been the focus of many research efforts. A number of these efforts were geared toward developing microscopic traffic simulation models to accurately represent the complex and dynamic operation of a transportation network. One of the challenges with such models is that they do not always adequately reflect field conditions\u2014particularly when representing traffic operations across different time periods. This paper presents a robust calibration procedure that aims to increase the accuracy of calibrated microscopic traffic simulation models. This procedure is based on a Monte Carlo approach to generate candidate parameter sets, which are aimed to produce calibrated simulation models. Model runs of these parameter sets are evaluated against robust calibration criteria, including startup and saturation flow characteristics and travel time distributions. The parameter sets that satisfy these criteria are considered as adequately calibrated to accurately reflect field performance measures. In applying this procedure, the results suggest that this approach offers a robust and effective method of calibrating simulation models where disaggregate-level vehicle data are available\u2014which is becoming more prevalent with further advancements in mobile sensor and connected vehicle technologies.<\/jats:p>","DOI":"10.1177\/0037549716673723","type":"journal-article","created":{"date-parts":[[2016,10,13]],"date-time":"2016-10-13T22:34:08Z","timestamp":1476398048000},"page":"35-47","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":23,"title":["A calibration procedure for increasing the accuracy of microscopic traffic simulation models"],"prefix":"10.1177","volume":"93","author":[{"given":"Dwayne","family":"Henclewood","sequence":"first","affiliation":[{"name":"Booz Allen Hamilton, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wonho","family":"Suh","sequence":"additional","affiliation":[{"name":"Department of Transportation and Logistics Engineering, Hanyang University, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael O","family":"Rodgers","sequence":"additional","affiliation":[{"name":"School of Civil and Environmental Engineering, Georgia Institute of Technology, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard","family":"Fujimoto","sequence":"additional","affiliation":[{"name":"School of Computational Science & Engineering, Georgia Institute of Technology, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael P","family":"Hunter","sequence":"additional","affiliation":[{"name":"School of Civil and Environmental Engineering, Georgia Institute of Technology, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2016,10,15]]},"reference":[{"key":"bibr1-0037549716673723","author":"Schrank D","year":"2011","journal-title":"Texas Transportation Institute"},{"key":"bibr2-0037549716673723","volume-title":"Real-time estimation of arterial performance measures using a data-driven microscopic traffic simulation technique","author":"Henclewood D","year":"2012"},{"key":"bibr3-0037549716673723","doi-asserted-by":"publisher","DOI":"10.1007\/s11116-007-9156-2"},{"key":"bibr4-0037549716673723","author":"Zhang M","year":"2008","journal-title":"California PATH Research Report"},{"key":"bibr5-0037549716673723","first-page":"1","volume-title":"Transportation Research Board 83rd Annual Meeting compedium of papers CD-ROM, #04-4165","author":"Chu L"},{"key":"bibr6-0037549716673723","first-page":"1","volume-title":"Transportation Research Board 84th Annual Meeting compedium of papers CD-ROM, #05-1938","author":"Oketch T"},{"key":"bibr7-0037549716673723","doi-asserted-by":"publisher","DOI":"10.3141\/1876-02"},{"key":"bibr8-0037549716673723","author":"Dowling R","year":"2002","journal-title":"California Department of Transportation"},{"key":"bibr9-0037549716673723","unstructured":"Dowling R, Skabardonis A, Alexiadis V. Traffic analysis toolbox: guidelines for applying traffic microsimulation modeling software. Federal Highway Administration, http:\/\/ops.fhwa.dot.gov\/trafficanalysistools\/tat_vol3\/Vol3_Guidelines.pdf (2004, accessed 27 June 2016)."},{"key":"bibr10-0037549716673723","doi-asserted-by":"publisher","DOI":"10.3141\/1876-01"},{"key":"bibr11-0037549716673723","unstructured":"Park B, Won J. Microscopic simulation model calibration and validation handbook. Virginia DOT, http:\/\/www.virginiadot.org\/vtrc\/main\/online_reports\/pdf\/07-cr6.pdf (2006, accessed 27 June 2016)."},{"key":"bibr12-0037549716673723","author":"Zhang M","year":"2008","journal-title":"California PATH Research Report"},{"key":"bibr13-0037549716673723","doi-asserted-by":"publisher","DOI":"10.1139\/l94-048"},{"key":"bibr14-0037549716673723","doi-asserted-by":"publisher","DOI":"10.3141\/1856-20"},{"key":"bibr15-0037549716673723","doi-asserted-by":"publisher","DOI":"10.3141\/1978-16"},{"key":"bibr16-0037549716673723","volume-title":"Uncertainty analysis for computer simulations through validation and calibration","author":"McFarland J","year":"2008"},{"key":"bibr17-0037549716673723","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2012.05.023"},{"key":"bibr18-0037549716673723","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2012.10.031"},{"key":"bibr19-0037549716673723","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.2015.1049749"},{"key":"bibr20-0037549716673723","doi-asserted-by":"publisher","DOI":"10.13182\/NSE12-55"},{"key":"bibr21-0037549716673723","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2012.2199486"},{"key":"bibr22-0037549716673723","first-page":"47","author":"Molina G","year":"2005","journal-title":"Am Stat Assoc Am Soc Qual Technometric"},{"key":"bibr23-0037549716673723","first-page":"1","volume-title":"Transportation Research Board 87th Annual Meeting compedium of papers CD-ROM, #08-2964","author":"Lee J"},{"key":"bibr24-0037549716673723","volume-title":"Developing a procedure to identify parameters for calibration of a VISSIM model","author":"Miller D","year":"2009"},{"key":"bibr25-0037549716673723","first-page":"1","volume-title":"Transportation Research Board 91st Annual Meeting compedium of papers CD-ROM, #12-2924","author":"Miller D"},{"key":"bibr26-0037549716673723","volume-title":"Traffic Engineering","author":"Roess R","year":"2010","edition":"4"},{"key":"bibr27-0037549716673723","doi-asserted-by":"publisher","DOI":"10.4135\/9781412983532"},{"key":"bibr28-0037549716673723","doi-asserted-by":"publisher","DOI":"10.1002\/9780470168707"},{"key":"bibr29-0037549716673723","unstructured":"FHWA. Next generation simulation, http:\/\/ngsim-community.org\/ (2007, accessed 27 June 2016)."},{"key":"bibr30-0037549716673723","unstructured":"PTV. VISSIM 5.10 user manual, 2011."}],"container-title":["SIMULATION"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0037549716673723","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/0037549716673723","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0037549716673723","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T11:27:35Z","timestamp":1777634855000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/0037549716673723"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,10,15]]},"references-count":30,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,1]]}},"alternative-id":["10.1177\/0037549716673723"],"URL":"https:\/\/doi.org\/10.1177\/0037549716673723","relation":{},"ISSN":["0037-5497","1741-3133"],"issn-type":[{"value":"0037-5497","type":"print"},{"value":"1741-3133","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,10,15]]}}}