A Progressive Extended Kalman Filter Method for Freeway Traffic State Estimation Integrating Multisource Data

作者：Liu, Yingshun; He, Shanglu^*; Ran, Bin; Cheng, Yang

来源：Wireless Communications and Mobile Computing, 2018, 2018: 6745726.

DOI：10.1155/2018/6745726

• HETEROGENEOUS DATA
• SPEED
• LOOP
• DETECTOR

Variable techniques have been used to collect traffic data and estimate traffic conditions. In most cases, more than one technology is available. A legitimate need for research and application is how to use the heterogeneous data from multiple sources and provide reliable and consistent results. This paper aims to integrate the traffic features extracted from the wireless communication records and the measurements from the microwave sensors for the state estimation. A state-space model and a Progressive Extended Kalman Filter (PEKF) method are proposed. The results from the field test exhibit that the proposed method efficiently fuses the heterogeneous multisource data and adaptively tracks the variation of traffic conditions. The proposed method is satisfactory and promising for future development and implementation.

• 出版日期2018
• 单位东南大学; 南京理工大学