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基于现实与虚拟交互的交通流再现实验方法
引用本文:杨晓光,张楠.基于现实与虚拟交互的交通流再现实验方法[J].同济大学学报(自然科学版),2018,46(12):1659-1667.
作者姓名:杨晓光  张楠
作者单位:同济大学 道路与交通工程教育部重点实验室,上海 201804,同济大学 道路与交通工程教育部重点实验室,上海 201804
基金项目:国家自然科学基金重点项目 (项目编号:51238008)
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.

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
收稿时间:2018/1/26 0:00:00
修稿时间:2018/10/29 0:00:00

An Experimental Method for Reproducing Traffic Flow Based on Reality and VirtualInteraction
YANG Xiaoguang and ZHANG Nan.An Experimental Method for Reproducing Traffic Flow Based on Reality and VirtualInteraction[J].Journal of Tongji University(Natural Science),2018,46(12):1659-1667.
Authors:YANG Xiaoguang and ZHANG Nan
Institution:Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China and Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
Abstract: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.
Keywords:experimental traffic engineering  traffic flow  nonparametric method  variational Bayesian learning  Markov chain Monte Carlo mathod
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