{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:40:01Z","timestamp":1777704001787,"version":"3.51.4"},"reference-count":38,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2018,6,18]],"date-time":"2018-06-18T00:00:00Z","timestamp":1529280000000},"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":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2018,8,26]]},"abstract":"<jats:p>\n                    The paper introduces a methodological approach based on genetic algorithms to calibrate microscopic traffic simulation models. The specific objective is to test an automated procedure utilizing genetic algorithms for assigning the most appropriate values to driver and vehicle parameters in AIMSUN. The genetic algorithm tool in MATLAB\n                    <jats:sup>\u00ae<\/jats:sup>\n                    and AIMSUN micro-simulation software were used. A subroutine in Python implemented the automatic interaction of AIMSUN with MATLAB\n                    <jats:sup>\u00ae<\/jats:sup>\n                    . Focus was made on two roundabouts selected as case studies. Empirical capacity functions based on summary random-effects estimates of critical headway and follow up headway derived from meta-analysis were used as reference for calibration purposes. Objective functions were defined and the difference between the empirical capacity functions and simulated data were minimized. Some model parameters in AIMSUN, which can significantly affect the simulation outputs, were selected. A better match to the empirical capacity functions was reached with the genetic algorithm-based approach compared with that obtained using the default parameters of AIMSUN. Overall, GA performs well and can be recommended for calibrating microscopic simulation models and solving further traffic management applications that practioners usually face using traffic microsimulation in their professional activities.\n                  <\/jats:p>","DOI":"10.3233\/jifs-169714","type":"journal-article","created":{"date-parts":[[2018,6,19]],"date-time":"2018-06-19T15:05:40Z","timestamp":1529420740000},"page":"1791-1806","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Calibrating a microscopic traffic simulation model for roundabouts using genetic algorithms"],"prefix":"10.1177","volume":"35","author":[{"given":"Orazio","family":"Giuffr\u00e8","sequence":"first","affiliation":[{"name":"Department of Civil, Environmental, Aerospace, and Material Engineering, Polytechnic School, University of Palermo, Palermo, Italy"}]},{"given":"Anna","family":"Gran\u00e0","sequence":"additional","affiliation":[{"name":"Department of Civil, Environmental, Aerospace, and Material Engineering, Polytechnic School, University of Palermo, Palermo, Italy"}]},{"given":"Maria Luisa","family":"Tumminello","sequence":"additional","affiliation":[{"name":"Department of Civil, Environmental, Aerospace, and Material Engineering, Polytechnic School, University of Palermo, Palermo, Italy"}]},{"given":"Antonino","family":"Sferlazza","sequence":"additional","affiliation":[{"name":"Department of Energy, Information Engineering and Mathematical Models, Polytechnic School, University of Palermo, Palermo, Italy"}]}],"member":"179","published-online":{"date-parts":[[2018,6,18]]},"reference":[{"issue":"3","key":"e_1_3_1_2_2","article-title":"Subcommittee on Surrogate Measures of Safety","volume":"20","author":"Tarko A.","year":"2009","unstructured":"TarkoA., DavisG., SaunierN., SayedT., and WashingtonS., Surrogate Measures of Safety, White paper, ANB20 (3) Subcommittee on Surrogate Measures of Safety, 2009.","journal-title":"Surrogate Measures of Safety"},{"key":"e_1_3_1_3_2","unstructured":"AIMSUN Dynamic Simulator User Manual Transport Simulation System (TSS) version 8 Barcelona 2011."},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11721-016-0129-y"},{"key":"e_1_3_1_5_2","volume-title":"International Conference on Computing in Civil and Building Engineering","author":"Ahmad Al-Hadad B.","year":"2010","unstructured":"Ahmad Al-HadadB., MawdesleyM.J. and StaceR., A genetic algorithm approach to highway alignment development, In: International Conference on Computing in Civil and Building Engineering, Nottingham University Press, Nottingham, 2010."},{"key":"e_1_3_1_6_2","first-page":"129","volume-title":"International Conference on Evolutionary Computation","author":"Ahmad Al-Hadad B.","year":"2010","unstructured":"Ahmad Al-HadadB. and MawdesleyM., A genetic algorithm approach to a 3D highway alignment development, In: International Conference on Evolutionary Computation, SciTePress, Valencia, 2010, pp. 129\u2013136."},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)TE.1943-5436.0000775"},{"issue":"2","key":"e_1_3_1_8_2","first-page":"135","article-title":"Pavement maintenance scheduling using genetic algorithms","volume":"11","author":"Yang C.","year":"2015","unstructured":"YangC., Remenyte-PrescottR., AndrewsJ.D., Pavement maintenance scheduling using genetic algorithms, International Journal of Performability Engineering11 (2) (2015), 135\u2013152.","journal-title":"International Journal of Performability Engineering"},{"key":"e_1_3_1_9_2","volume-title":"Genetic Algorithms in Search, Optimization and Machine Learning","author":"Goldberg D.E.","year":"1989","unstructured":"GoldbergD.E., Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley Longman Publishing Co., Inc, Boston1989."},{"key":"e_1_3_1_10_2","unstructured":"GenStat for Windows 17th Edition V."},{"key":"e_1_3_1_11_2","unstructured":"Highway Capacity Manual Transportation Research Board 5th. 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