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Forecasting available parking space with largest Lyapunov exponents method

Lookup NU author(s): Dr Amy Guo, Professor Phil Blythe

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Abstract

The techniques to forecast available parking space (APS) are indispensable components for parking guidance systems (PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of APS were studied. Thereafter, aiming to build up a multi-step APS forecasting model that provides richer information than a conventional one-step model, the largest Lyapunov exponents (largest LEs) method was introduced into PGS. By experimental tests conducted using the same dataset, its prediction performance was compared with traditional wavelet neural network (WNN) method in both one-step and multi-step processes. Based on the results, a new multi-step forecasting model called WNN-LE method was proposed, where WNN, which enjoys a more accurate performance along with a better learning ability in short-term forecasting, was applied in the early forecast steps while the Lyapunov exponent prediction method in the latter steps precisely reflect the chaotic feature in latter forecast period. The MSE of APS forecasting for one hour time period can be reduced from 83.1 to 27.1 (in a parking building with 492 berths) by using largest LEs method instead of WNN and further reduced to 19.0 by conducted the new method.


Publication metadata

Author(s): Ji Y, Tang D, Guo W, Blythe PT, Wang W

Publication type: Article

Publication status: Published

Journal: Journal of Central South University

Year: 2014

Volume: 21

Issue: 4

Pages: 1624-1632

Print publication date: 01/04/2014

ISSN (print): 2095-2899

ISSN (electronic): 2227-5223

Publisher: Central South University

URL: http://dx.doi.org/10.1007/s11771-014-2104-3

DOI: 10.1007/s11771-014-2104-3


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