Real-Time Corrected Traffic Correlation Model for Traffic Flow Forecasting

Hua-pu Lu, Zhi-yuan Sun, Wen-cong Qu and Ling Wang

Mathematical Problems in Engineering, 2015, vol. 2015, 1-7

Abstract:

This paper focuses on the problems of short-term traffic flow forecasting. The main goal is to put forward traffic correlation model and real-time correction algorithm for traffic flow forecasting. Traffic correlation model is established based on the temporal-spatial-historical correlation characteristic of traffic big data. In order to simplify the traffic correlation model, this paper presents correction coefficients optimization algorithm. Considering multistate characteristic of traffic big data, a dynamic part is added to traffic correlation model. Real-time correction algorithm based on Fuzzy Neural Network is presented to overcome the nonlinear mapping problems. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling methods.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:348036

DOI: 10.1155/2015/348036

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