|Table of Contents|

Short-term prediction method of freeway traffic flow(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2013年02期
Page:
114-119
Research Field:
交通信息工程及控制
Publishing date:

Info

Title:
Short-term prediction method of freeway traffic flow
Author(s):
XU Yan-yan1;  ZHAI Xi2;  KONG Qing-jie1;  LIU Yun-cai1
1. Key Laboratory of System Control and Information Processing of Ministry of Education, Shanghai Jiaotong University, Shanghai 200240, China; 2. Transportation Information Center, Shanghai Urban-Rural Construction and Transportation Development Research Institute, Shanghai 200032, China
Keywords:
intelligent transportation system;  traffic flow prediction;  data mining;  time series analysis;  classification and regression tree;  Kalman filter
PACS:
U491.14
DOI:
-
Abstract:
According to the complexity and nonlinearity characteristics of short-term traffic flow, the application of classification and regression tree model in freeway traffic volume prediction was investigated, and its including growing, splitting and pruning of the model was studied. The real traffic volume data of the freeways in Portland State of US was tested and verified. Afterwards, the experimental result of model was compared with the traditional ARIMA model and Kalman filtering model by using the error analysis methods of RMSE and MAPE. Comparison result indicates that the RMSEs of tree model are 42.1% and 13.1% lower than ARIMA model and Kalman filtering model, respectively. 1 tab, 6 figs, 17 refs.

References:

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Last Update: 2013-05-20