{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T16:06:07Z","timestamp":1775059567845,"version":"3.50.1"},"reference-count":13,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2015,11,4]],"date-time":"2015-11-04T00:00:00Z","timestamp":1446595200000},"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":[[2015,11,27]]},"abstract":"<jats:p>Intelligent traffic signal control (TSC) system is important for the alleviation of traffic congestion. Usually, most of the researches about TSC focused on single intersection based on type-1 fuzzy set. Compared with type-1 fuzzy logic controller (FLC), type-2 FLC can deal with more uncertainties in the road traffic control system. Therefore, a type-2 FLC optimized by NSGAII (T2-NSGAII) is designed for TSC in a complex road network, in which the intersection\u2019s traffic signal time is dynamically adjusted by its own and adjacent intersections\u2019 traffic volumes to reduce global delay time and traffic congestion. In T2-NSGAII, the expert rule set and the parameters of the fuzzy membership functions are simultaneously optimized by NSGAII to achieve less time delay and traffic congestion. In the simulations of a six-intersection traffic network with different vehicular arrival rates, it is demonstrated that T2-NSGAII has better performance compared with vehicle actuated controller based on fixed-time control (FTC), type-1 FLC, type-2 FLC and isolatedly optimized Type-2 FLC and the total delay time could be reduced by 76.3% , 65.1% , 58.3% and 35.4% respectively.<\/jats:p>","DOI":"10.3233\/ifs-151964","type":"journal-article","created":{"date-parts":[[2015,12,9]],"date-time":"2015-12-09T14:28:26Z","timestamp":1449671306000},"page":"2611-2618","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["Intelligent traffic signal controller based on type-2 fuzzy logic and NSGAII"],"prefix":"10.1177","volume":"29","author":[{"given":"Chen","family":"Wen","sequence":"first","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}]},{"given":"Zhao","family":"Hui","sequence":"additional","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}]},{"given":"Li","family":"Tao","sequence":"additional","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}]},{"given":"Liu","family":"Yuling","sequence":"additional","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}]}],"member":"179","published-online":{"date-parts":[[2015,11,4]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0020-0255(02)00199-8"},{"key":"e_1_3_1_3_2","article-title":"Transport Research Laboratory in the United Kingdom","author":"Robertson DI","year":"1969","unstructured":"Robertson DI1969Transport Research Laboratory in the United KingdomTRANSYT: A Traffic Network Study Tool, Technical Report","journal-title":"TRANSYT: A Traffic Network Study Tool, Technical Report"},{"issue":"4","key":"e_1_3_1_4_2","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1109\/TSMCC.2011.2161577","article-title":"Computational intelligence in urban traffic signal control: A survey","volume":"42","author":"Zhao D","year":"2012","unstructured":"Zhao D, Dai Y, Zhang Z2012Computational intelligence in urban traffic signal control: A surveyIEEE Transactions on Systems, Man, and Cybernetics Part C: Applications and Reviews424485494","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications and Reviews"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/4235.996017"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0968-090X(99)00026-1"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2011.12.010"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2010.02.022"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2010.08.007"},{"key":"e_1_3_1_10_2","first-page":"210","article-title":"Traffic Signal Timing Optimization for Isolated Untersections Based on Differential Evolution Bacteria Foraging Algorithm","author":"Liu Q","year":"2012","unstructured":"Liu Q, Xu J2012Traffic Signal Timing Optimization for Isolated Untersections Based on Differential Evolution Bacteria Foraging AlgorithmProceeding of the 8th International Conference on Traffic and Transportation Studies210215","journal-title":"Proceeding of the 8th International Conference on Traffic and Transportation Studies"},{"key":"e_1_3_1_11_2","first-page":"350","article-title":"The myth of traffic-responsivesignal control: Why common sense does not always make sense","volume":"77","author":"Evers R","year":"2015","unstructured":"Evers R, Proost S2015The myth of traffic-responsivesignal control: Why common sense does not always make senseTransportation Research Part A77350357","journal-title":"Transportation Research Part A"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1570-6672(08)60080-X"},{"key":"e_1_3_1_13_2","first-page":"1737","article-title":"Towards Distributed Online Cooperative Traffic Signal Control Using the Cell Transmission Model","author":"Timotheou S","year":"2013","unstructured":"Timotheou S, Panayiotou CG, Polycarpou MM2013Towards Distributed Online Cooperative Traffic Signal Control Using the Cell Transmission ModelProceedings of the 16th Intelligent Transportation Systems Conference17371742","journal-title":"Proceedings of the 16th Intelligent Transportation Systems Conference"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2014.06.022"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-151964","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/IFS-151964","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-151964","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T10:49:32Z","timestamp":1770720572000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/IFS-151964"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,11,4]]},"references-count":13,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2015,11,27]]}},"alternative-id":["10.3233\/IFS-151964"],"URL":"https:\/\/doi.org\/10.3233\/ifs-151964","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,11,4]]}}}