Abstract: For the need of Intelligent Traffic System(ITS) on urban expressway, this paper presents a real-time traffic state estimator. The basic principle is to integrate Extended Kalman Filtering(EKF) with macroscopic hydrodynamic traffic flow models, and to estimate future traffic states in real time based on traffic detectors that fixed on urban expressway. The result of an example shows acceptable applicability and precision of the method, which can provide reference for traffic control and traffic guidance.

Key words: Extended Kalman Filtering(EKF), macroscopic hydrodynamic models, traffic state

摘要： 根据城市智能交通系统的实际需要，构建能够实时估计城市快速路上交通状态的估计器。其基本思想是将扩展卡尔曼滤波理论引入宏观流体力学模型，结合快速路上的固定检测设备，实时估计快速路上的交通状态。实例分析结果表明，该模型的适用性和精度都令人满意，可为城市快速路交通控制和诱导提供决策参考。

关键词: 扩展卡尔曼滤波, 宏观流体力学模型, 交通状态

CLC Number: 

• TP391.9