摘要
针对现有多数交通仿真系统在交通状态估计问题精确度不高的缺陷,引入粒子滤波方法对交通状态进行预测估计,设计并实现基于粒子滤波的交通仿真系统。首先介绍系统粒子滤波的初始化、粒子状态转移过程、权值计算及归一化和重采样操作的设计,然后将实测交通数据通过粒子滤波算法引入模型以提高状态估计的能力,最后基于微观交通仿真软件MovSim实现该系统。实验表明:基于粒子滤波的交通仿真系统具有较强的预测稳定性和准确性。
Aiming at the existed most traffic simulation systems which have low precision to estimate the traffic state trend, this paper introduces the particle filter method to pre-estimate the motion state of vehicles, then designs and implements a traffic simu- lation system based on particle filter. First of all, the design of initialization, state transition, weight calculation and normalization and resample operation are introduced ; Then the basic process how the measured data which reflects the real characteristics of the system is dynamically incorporated to adjust the distribution of particles for getting closer to the real state development is dis- cussed; Finally, the system based on microscopic traffic simulation software MovSim is realized. Experiments indicate the pro- posed system is of high accuracy and stabilization of prediction.
出处
《计算机与现代化》
2014年第3期19-23,共5页
Computer and Modernization
基金
南京航空航天大学基本业务科研项目(NS2013091)
关键词
交通仿真
状态预测
数据同化
traffic simulation
state estimation
data assimilation
