摘要
实时动态OD(Origin-Destination)矩阵是动态交通分配系统的重要输入.运用状态空间模型的有关概念,考虑交叉口进口道观测数据建立了相应的状态空间模型,提出了一步预测卡尔曼滤波方程实现估计和预测.案例研究表明,将交叉口观测数据纳入测量方程能更好地对OD矩阵做出较精确的估计和预测,且基于仿真的分配矩阵估计方法能更准确地反映OD流量在检测设施上的比例分配.
Real-time dynamic OD matrix is an important input for dynamic traffic assignment system.This paper built a new state-space model whose measurement equation will take the interaction detection data into account,and proposed a one-step prediction Kalman-filtering model to achieve this target.The case study shows that including the interaction data into the measurement equation will give a more accurate estimation and prediction and a simulation-based assignment matrix will give a more accurate reflection on how many volumes are detected by certain facility.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2012年第3期436-440,共5页
Journal of Shanghai Jiaotong University
基金
国家自然科学基金资助项目(50978163
71001067)
关键词
动态交通分配
状态空间模型
卡尔曼滤波
仿真
dynamic traffic assignment（DTA）
state-space model
Kalman filtering
simulation
