基于卡尔曼滤波理论的实时等参数交通量预测模型

Proceedings of the IEEE International Vehicle Electronics Conference (IVEC'99) (Cat. No.99EX257) Pub Date : 1999-09-06 DOI:10.1109/IVEC.1999.830634

Zhu Zhong, Y. Zhaosheng

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引用次数: 4

摘要

本文利用卡尔曼滤波理论建立了交通流量预测模型。利用长春地区的检测数据对下一时间段的交通流量进行了预测，结果表明该预测模型具有较好的实时预测性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A real-time isoparametric traffic volume prediction model based on the Kalman filtering theory

In this paper, a traffic volume prediction model is formulated through Kalman filtering theory. The traffic volumes of the next time interval are forecasted with the detected data collected in Changchun, China, which shows that the prediction model has good performance in real-time prediction.

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Proceedings of the IEEE International Vehicle Electronics Conference (IVEC'99) (Cat. No.99EX257)

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