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Drivers\u2019 reaction time was calculated using Cross Correlation analysis. In the car-following model developed, relative speed, distance headway between leading and following vehicle, and speed of following vehicle are the three input parameters; while acceleration of the following vehicle is the output. Comparing with the traditional General Motor (GM) car-following model, the results show that the ANFIS-based car-following model can better describe the freeway driving behavior.<\/jats:p>","DOI":"10.3233\/ifs-151770","type":"journal-article","created":{"date-parts":[[2016,1,15]],"date-time":"2016-01-15T12:23:50Z","timestamp":1452860630000},"page":"461-466","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":8,"title":["Developing a car-following model with consideration of driver\u2019s behavior based on an Adaptive Neuro-Fuzzy Inference System"],"prefix":"10.1177","volume":"30","author":[{"given":"Junhua","family":"Wang","sequence":"first","affiliation":[{"name":"School of Transportation Engineering, Tongji University, Cao\u2019an Hwy., Shanghai, China"}]},{"given":"Lanfang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Transportation Engineering, Tongji University, Cao\u2019an Hwy., Shanghai, China"}]},{"given":"Siwen","family":"Lu","sequence":"additional","affiliation":[{"name":"Shuxin Town Government, Chongmin County, Shanghai, China"}]},{"given":"Zhongren","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Transportation, California, USA"}]}],"member":"179","published-online":{"date-parts":[[2015,9,9]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1369-8478(00)00005-X"},{"key":"e_1_3_2_3_2","first-page":"200","article-title":"Design of an improved fuzzy logic based model for prediction of car-following behavior","author":"Khodayari R. 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