摘要
面向连续与间断交通流实验系统框架,利用现实交通流的观测数据,在实验框架的虚拟环境中建立交通流的非参数模型,通过虚拟框架的贝叶斯学习再现与现实等价的实验交通流.选取更为复杂的信号控制交通流场景对该实验方法进行验证.结果表明,该方法在一定精度内可以近似再现信号控制交通流.
With the development and application of information technology,it is becoming a new research direction to analyze complex traffic flow based on experimental methods.One of the basic problems is the reproduction of the actual traffic flow in the experiment.Based on the framework of a traffic flow experimental system,this paper proposes an experimental method to reproduce the real traffic flow in virtual environment by giving the observation data of traffic flow in real environment whose system framework includes the nonparametric model of traffic flow and the Bayesian learning algorithm.Subsequently,the experimental method was numerically verified in the scene of traffic flow on signal control.The results show that the method proposed could realize the approximate dynamic traffic flow on signal control in virtual environment.
作者
杨晓光
张楠
YANG Xiaoguang;ZHANG Nan(Key Laboratory of Road and Traffic Engineering of the Ministry of Education,Tongji University,Shanghai 201804,China)
出处
《同济大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2018年第12期1659-1667,共9页
Journal of Tongji University:Natural Science
基金
国家自然科学基金重点项目(51238008)
关键词
实验交通工程
交通流
非参数方法
变分贝叶斯学习
马尔科夫链-蒙特卡罗方法
experimental traffic engineering
traffic flow
nonparametric method
variational Bayesian learning
Markov chain Monte Carlo mathod
