{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:07:49Z","timestamp":1777705669183,"version":"3.51.4"},"reference-count":41,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2022,3,4]]},"abstract":"<jats:p>Driving behavior type is a hotspot in transportation field, but there have been few studies on free driving behavior type. The factor of current driving behavior evaluation model is single, and its environmental adaptability is insufficient, and driving behavior type is difficult to predict accurately. In addition, free driving behavior as one kind of the important driving operation behaviors lacks quantitative assessment methods and models. In view of these deficiencies, evaluation and prediction of free driving behavior based on Fuzzy Comprehensive Support Vector Machine (FC-SVM) is proposed. Firstly, a variety of individual decision-making behavior data obfuscating with environmental complexity are collected. These obtained parameters were used as FC multi-factor evaluation parameters to quantitatively evaluate free driving behavior from multiple aspects, and to qualitatively derive the driver\u2019s driving behavior type. Further, the SVM used the RBF kernel function to obtain the optimal parameters and train the SVM network, and it used the obtained SVM model for the prediction of driving behavior type in short time. The results of simulations using different methods show that the SD value of FC-SVM evaluation results is the lowest, only 1.273. Compared with other common methods, its MacroP reaches 89.2%. It is interesting to find that aggressive driving can be more distinct from other behavior types. Moreover, the mixed traffic flow composed of aggressive driver has a higher traffic efficiency in basic sections. This work is of great value for improving driving behavior, reducing road congestion and improving road traffic efficiency in the mixed intelligent traffic.<\/jats:p>","DOI":"10.3233\/jifs-201680","type":"journal-article","created":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T13:44:50Z","timestamp":1643118290000},"page":"2863-2879","source":"Crossref","is-referenced-by-count":7,"title":["Evaluation and prediction of free driving behavior type based on fuzzy comprehensive support vector machine"],"prefix":"10.1177","volume":"42","author":[{"given":"Yucheng","family":"Zhao","sequence":"first","affiliation":[{"name":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Liang","sequence":"additional","affiliation":[{"name":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"Chen","sequence":"additional","affiliation":[{"name":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yafei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mechanical and Power Engineering, Shanghai Jiaotong University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinfeng","family":"Gong","sequence":"additional","affiliation":[{"name":"China Automotive Technology Research Center Co., Ltd, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-201680_ref1","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.aap.2017.04.023","article-title":"Stress-related psychosocial factors at work, fatigue, and risky driving behavior in bus rapid transport (BRT) drivers","volume":"104","author":"Useche","year":"2017","journal-title":"Accident Analysis and Prevention"},{"key":"10.3233\/JIFS-201680_ref2","first-page":"80","article-title":"Prediction of driving behaviors base on Theory Planned Behavior (TPB) model in truck drivers","volume":"10","author":"Aghamolaei","year":"2013","journal-title":"Life Science Journal"},{"issue":"2","key":"10.3233\/JIFS-201680_ref3","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1016\/j.aap.2007.09.001","article-title":"Modeling safe and unsafe driving behaviour","volume":"40","author":"Verschuur","year":"2008","journal-title":"Accident Analysis & Prevention"},{"issue":"24","key":"10.3233\/JIFS-201680_ref4","first-page":"9","article-title":"Multi-model assessment of the factors driving stratospheric ozone evolution over the 21st century","volume":"115","author":"Oman","year":"2010","journal-title":"Journal of Geophysical Research D: Atmospheres"},{"key":"10.3233\/JIFS-201680_ref5","unstructured":"Li P.-f. , Research on driving behavior characterization indicators and analysis methods, Ph.D. Dissertation, Jilin University, (2010)."},{"key":"10.3233\/JIFS-201680_ref6","unstructured":"Yang P.-f. , Research on Operational Driver Safety Assessment Method, Ph.D. Dissertation, Chang\u2019an University, (2013)."},{"key":"10.3233\/JIFS-201680_ref7","unstructured":"Li Y. , Multi-attribute evaluation method and application research of driving behavior safety, Ph.D. Dissertation, Jilin University, (2016)."},{"issue":"1","key":"10.3233\/JIFS-201680_ref8","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1007\/s11771-020-4286-1","article-title":"Driving rule extraction based on cognitive behavior analysis","volume":"27","author":"Zhao","year":"2020","journal-title":"Journal of Central South University"},{"issue":"3","key":"10.3233\/JIFS-201680_ref9","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1109\/JBHI.2016.2532354","article-title":"Driver Fatigue Classification With Independent Component by Entropy Rate Bound Minimization Analysis in an EEG-Based System","volume":"21","author":"Chai","year":"2017","journal-title":"IEEE Journal of Biomedical & Health Informatics"},{"key":"10.3233\/JIFS-201680_ref10","unstructured":"Ji Y. , Woo H. and Tamura Y. , Driver classification in vehicle following behavior by using dynamic potential field method, in Intelligent Transportation Systems (ITSC), IEEE 20th International Conference on. IEEE (2017), 1\u20136."},{"key":"10.3233\/JIFS-201680_ref11","first-page":"53","article-title":"Drivers Classification Based on the Driver Lane Change Behavior Parameters","volume":"5","author":"E","year":"2016","journal-title":"International Journal of Material & Mechanical"},{"issue":"2","key":"10.3233\/JIFS-201680_ref12","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.ergon.2004.05.009","article-title":"Passenger-side rear-view mirrors: driver behavior and safety","volume":"35","author":"Ayres","year":"2005","journal-title":"International journal of industrial ergonomics"},{"key":"10.3233\/JIFS-201680_ref13","unstructured":"Mao J. , Lane change warning Method considering driving style Ph.D. Dissertation, Chang\u2019an University, Xi\u2019an, (2012)."},{"issue":"3","key":"10.3233\/JIFS-201680_ref14","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/S0968-090X(96)00006-X","article-title":"A Microscopic Traffic Simulator for evaluation of dynamic traffic management systems","volume":"4","author":"Yang","year":"1996","journal-title":"Transportation Research Part C"},{"issue":"6","key":"10.3233\/JIFS-201680_ref15","doi-asserted-by":"crossref","first-page":"4235","DOI":"10.3233\/JIFS-16628","article-title":"The drivers\u2019 lane selection model basedonmixed fuzzy many-person multi-objective non-cooperative game","volume":"32","author":"Wang","year":"2017","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"key":"10.3233\/JIFS-201680_ref16","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.trc.2015.07.009","article-title":"Game theoretic approach for predictive lane-changing and car-following control","volume":"58","author":"Daamen","year":"2015","journal-title":"Transportation Research Part C"},{"key":"10.3233\/JIFS-201680_ref17","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1016\/j.jenvman.2018.02.085","article-title":"Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model","volume":"213","author":"Yang","year":"2018","journal-title":"Journal of Environmental Management"},{"issue":"99","key":"10.3233\/JIFS-201680_ref18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TFUZZ.2021.3052092","article-title":"A fuzzy system of operation safety assessment using multi-model linkage and multi-stage collaboration for in-wheel motor","volume":"PP","author":"Xue","year":"2021","journal-title":"IEEE Transactions on Fuzzy Systems"},{"issue":"6","key":"10.3233\/JIFS-201680_ref19","doi-asserted-by":"crossref","first-page":"3862","DOI":"10.1109\/TII.2019.2940475","article-title":"Linear Priors Mined and Integrated for Transparency of Blast Furnace Black-Box SVM Model","volume":"16","author":"Chen","year":"2020","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"10.3233\/JIFS-201680_ref20","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.knosys.2020.105845","article-title":"LR-SMOTE - An improved unbalanced data set oversampling based on K-means and SVM","volume":"196","author":"Liang","year":"2020","journal-title":"Knowledge-Based Systems"},{"issue":"9","key":"10.3233\/JIFS-201680_ref21","first-page":"1040","article-title":"A Study on the Driving Behavior Prediction of Dangerous Lane Change","volume":"39","author":"Xiong","year":"2017","journal-title":"Automotive Engineering"},{"issue":"2","key":"10.3233\/JIFS-201680_ref22","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1109\/72.991432","article-title":"Fuzzy Support Vector Machines","volume":"13","author":"Lin","year":"2002","journal-title":"IEEE Transactions on Neural Networks"},{"issue":"9","key":"10.3233\/JIFS-201680_ref23","doi-asserted-by":"crossref","first-page":"4709","DOI":"10.1007\/s00521-018-3823-4","article-title":"An adaptive twin support vector regression machine based on rough and fuzzy set theories","volume":"32","author":"Xue","year":"2020","journal-title":"Neural Computing & Applications"},{"issue":"1","key":"10.3233\/JIFS-201680_ref24","first-page":"1","article-title":"Human behavior characterization for driving style recognition in vehicle system","volume":"83","author":"Martinelli","year":"2020","journal-title":"Computers & Electrical Engineering"},{"key":"10.3233\/JIFS-201680_ref25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2020\/9263605","article-title":"Vehicle Fuel Consumption Prediction Method Based on Driving Behavior Data Collected from Smartphones","volume":"2020","author":"Yao","year":"2020","journal-title":"Journal of Advanced Transportation"},{"key":"10.3233\/JIFS-201680_ref26","unstructured":"Hai-qing Z. , Research on vehicle safety comprehensive evaluation based on driver cognition, M.D. Thesis, Beijing Forestry University, (2006)."},{"issue":"9","key":"10.3233\/JIFS-201680_ref27","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.ijar.2018.05.005","article-title":"A review of applications of fuzzy sets to safety and reliability engineering","volume":"100","author":"Kabir","year":"2018","journal-title":"International Journal of Approximate Reasoning"},{"issue":"5","key":"10.3233\/JIFS-201680_ref29","doi-asserted-by":"crossref","first-page":"1342","DOI":"10.1109\/TFUZZ.2016.2612300","article-title":"Granular Fuzzy Rule-Based Models: A Study in a Comprehensive Evaluation and Construction of Fuzzy Models","volume":"25","author":"Hu","year":"2017","journal-title":"IEEE Transactions on Fuzzy Systems"},{"issue":"16","key":"10.3233\/JIFS-201680_ref30","doi-asserted-by":"crossref","first-page":"12501","DOI":"10.1007\/s00500-020-04687-0","article-title":"Fuzzy conformable fractional differential equations: novel extended approach and new numerical solutions","volume":"24","author":"Arqub","year":"2020","journal-title":"Soft Computing"},{"key":"10.3233\/JIFS-201680_ref32","doi-asserted-by":"crossref","first-page":"117533","DOI":"10.1016\/j.energy.2020.117533","article-title":"Multi-criteria comprehensive energy efficiency assessment based on fuzzy-AHP method: A case study of post-treatment technologies for coal-fired units","volume":"200","author":"Si","year":"2020","journal-title":"Energy"},{"key":"10.3233\/JIFS-201680_ref34","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1007\/978-3-642-29390-0_81","article-title":"Comprehensive Analysis of Risky Driving Behaviors Based on Fuzzy Evaluation Model","volume":"160","author":"Pei","year":"2012","journal-title":"Advances in Intelligent and Soft Computing"},{"issue":"1","key":"10.3233\/JIFS-201680_ref35","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.physa.2015.09.009","article-title":"A new car-following model with the consideration of incorporating timid and aggressive driving behaviors","volume":"442","author":"Peng","year":"2016","journal-title":"Physica a-Statistical Mechanics and Its Applications"},{"issue":"15","key":"10.3233\/JIFS-201680_ref36","doi-asserted-by":"crossref","first-page":"1302","DOI":"10.1016\/j.physleta.2017.02.018","article-title":"An extended continuum model accounting for the driver\u2019s timid and aggressive attributions","volume":"381","author":"Cheng","year":"2017","journal-title":"Physics Letters A"},{"issue":"2","key":"10.3233\/JIFS-201680_ref37","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1049\/iet-ipr.2017.0368","article-title":"License number plate recognition system using entropy-based features selection approach with SVM","volume":"12","author":"Khan","year":"2018","journal-title":"Iet Image Processing"},{"issue":"3","key":"10.3233\/JIFS-201680_ref38","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1007\/s11063-017-9771-7","article-title":"Performance Analysis for SVM Combining with Metric Learning","volume":"48","author":"Hu","year":"2018","journal-title":"Neural Processing Letters"},{"issue":"5","key":"10.3233\/JIFS-201680_ref41","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1080\/15389588.2010.495761","article-title":"The effect of feedback on attitudes toward cellular phone use while driving: a comparison between novice and experienced drivers","volume":"11","author":"Wang","year":"2010","journal-title":"Traffic Injury Prevention"},{"issue":"12","key":"10.3233\/JIFS-201680_ref42","doi-asserted-by":"crossref","first-page":"1366","DOI":"10.1039\/C8PY00138C","article-title":"The downside of dispersity: why the standard deviation is a better measure of dispersion in precision polymerization","volume":"9","author":"Harrisson","year":"2018","journal-title":"Polymer Chemistry"},{"issue":"2","key":"10.3233\/JIFS-201680_ref43","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1287\/trsc.2015.0638","article-title":"Optimal Recharging Policies for Electric Vehicles","volume":"51","author":"Swed","year":"2017","journal-title":"Transportation Science"},{"issue":"4","key":"10.3233\/JIFS-201680_ref44","doi-asserted-by":"crossref","first-page":"924","DOI":"10.1109\/TMC.2015.2436393","article-title":"Passive RFID for Object and Use Detection during Trauma Resuscitation","volume":"15","author":"Parlak","year":"2016","journal-title":"Ieee Transactions on Mobile Computing"},{"issue":"1","key":"10.3233\/JIFS-201680_ref45","first-page":"1","article-title":"A novel framework of fuzzy oblique decision tree construction for pattern classification","author":"Cai","year":"2020","journal-title":"Applied Intelligence"},{"key":"10.3233\/JIFS-201680_ref46","doi-asserted-by":"crossref","unstructured":"Luan J. , Zhang C. , Xu B. , Xue Y. and Ren Y. , The predictive performances of random forest models with limited sample size and different species traits, Fisheries Research 227 (2020).","DOI":"10.1016\/j.fishres.2020.105534"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-201680","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:44:40Z","timestamp":1777455880000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-201680"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,4]]},"references-count":41,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.3233\/jifs-201680","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,4]]}}}