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Historical traffic flow data reconstrucion applying Wavelet Transform

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Document pages: 14 pages

Abstract: Despite the importance of fundamental parameters (traffic flow, density andspeed) to describe the traffic behavior, there still are some difficulties inorder to obtain and store this information. Furthermore, given the type ofstudy or the project the resolution analysis interval can vary from less thanone hour to annual. To create alternatives in database structures,this articleaims to present a method to reconstruct disaggregated historical data fromaggregated data using Wavelet Transform. From the proposed method, it ispossible to reconstruct data in short intervals from data with longerintervals,since they have the same behavior, for example, data from the same orsimilar highway. For such, a Detail coefficient is generated through theDiscrete Wavelet Transform (DWT) with the disaggregated data. The aggregateddata was reconstructed through an Approximation coefficient. After establishingthese coefficients, the Inverse Wavelet Transform (IWT) is applied. The resultsindicated an average correlation between the reconstructed the original data of0.960; 0.974; 0.968 and 0.960 for data initially aggregated at 10, 20, 40 and80 minutes interval, respectively. The results also indicated an absolute meanerror of 7.13 ; 8.74 ; 9.83 and 11.23 for data initially aggregated in 10,20, 40 and 80 minutes, respectively. In other words, results suggest that thereconstituted data have a high correlation and a low percentage of meanabsolute error with the original signal. In conclusion, the reconstruction ofdata from aggregated data and Wavelet Transform presents a good correlation andlow average absolute error rate, comparable to traffic estimation studies(CASTRO-NETO et al., 2009; CORIC et al. 2012, LAM et al., 2006; LIM, 2001).

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