Abstract
The origin-destination (OD) matrices express the number and the pattern of trips distributed between OD pairs. OD matrix structural comparison can be used to identify different mobility patterns in the cities. A comparison of two OD matrices could express their difference from both numerical and structural aspects. Limited methods, such as the mean structural similarity (MSSIM) index and geographical window-based structural similarity index (GSSI), have been developed to compare the structural similarity (SSIM) of two matrices. These methods calculate the structural similarities of two OD matrices by grouping the OD pairs into local windows. The obtained results from the MSSIM entirely depend on the dimensions of the chosen windows. Meanwhile, the GSSI method only focuses on the geographical adjacency and correlation of zones while selecting local windows. Accordingly, this paper developed a novel method named Socioeconomy, Land-use, and Population Structural Similarity Index (SLPSSI) in which local windows are selected according to socioeconomic, land-use, and population properties for SSIM comparison of OD matrices. The proposed method was tested on Tehran’s OD matrix extracted from cell phone Geographic Position System (GPS) data. The advantage of this method over two previous ones was observed in determining the new pattern of trips on local windows and more precise detection of SSIM of the weekdays. The SLPSSI approach is up to 10 percent more accurate than the MSSIM method and up to 5.5 percent more accurate than the GSSI method. The proposed method also had a better performance on sparse OD matrices. It is capable of better determining the SSIM of sparse OD matrices by up to 8% compared with the GSSI method. Finally, the sensitivity analysis results indicate that the suggested method is robust and reliable since it is sensitive to applying both constant and random coefficients.
Highlights
An origin-destination (OD) matrix of urban trips indicates the demand for trips between different traffic zones [1]. e matrix provides transportation engineers with important information on the characteristics and patterns of trips in cities. ere are two aspects in an OD matrix comparison: (1) e numerical value of each cell of the matrix, which indicates the number of trips between OD pairs
Regardless of the geographical locations of Traffic Analysis Zones (TAZs), this study has considered the following properties to offer a new tool for developing the Mean structural similarity (MSSIM): (1) e socioeconomic properties of the TAZs, such as the level of residents’ employment and private vehicle ownership per capita
Summary of the Literature Review. e primary methods for comparing OD matrices that only focus on the numerical cell-to-cell comparison of two matrices cannot specify the structural difference of two matrices despite their overall numerical similarity
Summary
An origin-destination (OD) matrix of urban trips indicates the demand for trips between different traffic zones [1]. e matrix provides transportation engineers with important information on the characteristics and patterns of trips in cities. ere are two aspects in an OD matrix comparison:. Rows B has no structural similarity (SSIM) in the above matrices too For both matrices, C, B, D, and A are the preferred destinations for trips from origin C. us, rows C in the two matrices are dominantly consistent in terms of the structural framework while having different numerical values. E remainder of the paper is structured as follows: Section 2 reviews the literature on the use of statistical measures for OD matrices comparison; Section 3 presents the methodology and explains in detail the development process of the proposed measure, SLPSSI; Section 4 compares the proposed method with MSSIM and GSSI. Rows C in the two matrices are dominantly consistent in terms of the structural framework (the preferred order of destinations for trips from origin C are C, B, D, and A for both matrices)while having different numerical values.
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