Research on Short-Term Traffic Flow Prediction Method Based on Similarity Search of Time Series

Zhaosheng Yang, Qichun Bing, Ciyun Lin, Nan Yang and Duo Mei

Mathematical Problems in Engineering, 2014, vol. 2014, 1-8

Abstract:

Short-time traffic flow prediction is necessary for advanced traffic management system (ATMS) and advanced traveler information system (ATIS). In order to improve the effect of short-term traffic flow prediction, this paper presents a short-term traffic flow multistep prediction method based on similarity search of time series. Firstly, the landmark model is used to represent time series of traffic flow data. Then the input data of prediction model are determined through searching similar time series. Finally, the echo state networks model is used for traffic flow multistep prediction. The performance of the proposed method is measured with expressway traffic flow data collected from loop detectors in Shanghai, China. The experimental results demonstrate that the proposed method can achieve better multistep prediction performance than conventional methods.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:184632

DOI: 10.1155/2014/184632

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