Journal of Frontiers of Computer Science and Technology ›› 2020, Vol. 14 ›› Issue (6): 901-917.DOI: 10.3778/j.issn.1673-9418.2001029

Previous Articles     Next Articles

Survey on Research and Application of Support Vector Machines in Intelligent Transportation System

LIN Hao, LI Leixiao, WANG Hui   

  1. 1. College of Data Science and Application, Inner Mongolia University of Technology, Hohhot 010080, China
    2. Inner Mongolia Autonomous Region Engineering & Technology Research Center of Big Data Based Software Service, Hohhot 010080, China
  • Online:2020-06-01 Published:2020-06-04



  1. 1. 内蒙古工业大学 数据科学与应用学院,呼和浩特 010080
    2. 内蒙古自治区基于大数据的软件服务工程技术研究中心,呼和浩特 010080


Support vector machine (SVM) is a supervised machine learning algorithm based on statistical learning theory. Due to low requirements for data and excellent generalization ability in regression and classification modeling, SVM is used widely in data analysis and mining modeling of intelligent transportation system. This paper first introduces the basic principles and open source tools of SVM. Next, this paper summarizes the applications of SVM in regression prediction of passenger flow, traffic congestion, traffic accident and traffic carbon emission. After that, this paper summarizes the applications of SVM in classified prediction of traffic status estimation, traffic sign recognition and traffic incident detection. This paper compares SVM with other widely used algorithms in intelligent transportation system. The research status of the optimization algorithms and derivative algorithms based on SVM are analyzed. Finally, this paper prospects the optimization and application trend of SVM in the future intelligent transportation system.

Key words: intelligent transportation system (ITS), support vector machine (SVM), regression prediction, classification prediction



关键词: 智能交通系统(ITS), 支持向量机(SVM), 回归预测, 分类预测