Traffic Flow Characteristics and Short-Term Prediction Model of Urban Intersection

WENG Xiao-xiong; TAN Guo-xian; YAO Shu-shen; HUANG Zheng

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WENG Xiao-xiong, TAN Guo-xian, YAO Shu-shen, HUANG Zheng. Traffic Flow Characteristics and Short-Term Prediction Model of Urban Intersection[J]. Journal of Traffic and Transportation Engineering, 2006, 6(1): 103-107.

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WENG Xiao-xiong, TAN Guo-xian, YAO Shu-shen, HUANG Zheng. Traffic Flow Characteristics and Short-Term Prediction Model of Urban Intersection[J]. Journal of Traffic and Transportation Engineering, 2006, 6(1): 103-107.

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Traffic Flow Characteristics and Short-Term Prediction Model of Urban Intersection

School of Transportation, South China University of Technology, Guangzhou 510640, Guangdong, China

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Author Bio:
WENG Xiao-xiong(1958-), female, associate professor, 86-20-87111030, ctxxweng@scut.edu.cn
Received Date: 2005-08-01
Publish Date: 2006-03-25

Abstract

Abstract

The long-term prediction models (time scale is larger than 15 min) of traffic flow did not satisfy the demands of traffic signal control and traveler information real-time dissemination.After observing and measuring actual intersection traffic flow in Guangzhou city center area for long time, the paper analyzed the characteristics of varied-time-scale traffic flow, and proposed an ARIMA (p, d, q) model, in which signal periods were taken as time intervals, and the flow rates of green phase were taken as model variables for predicting the short-term traffic flow of urban intersection.By the case study of traffic flow modeling and predicting with different time-sections separately in 1 signal period and 3 signal periods, it is validated that the ARIMA (p, d, q) prediction model construction is stable, its arithmetic is simple, the prediction model in 3 signal periods can well keep the characteristics of short-term traffic flow, its accuracy is quite satisfied, its root-mean-squareerror is 0.0159.
- traffic engineering,
- traffic flow characteristics,
- traffic prediction,
- short-term time scale,
- time series analysis

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References(9)

References

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