Volume List  / Volume 12 (1)



DOI: 10.7708/ijtte2022.12(1).10

12 / 1 / 140-154 Pages


Zsombor Szabó - Budapest University of Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Department of Transport Technology and Economics – H-1111 Műegyetem rakpart 3. Budapest, Hungary & KTI Institute for Transport Sciences Nonprofit Ltd., Directorate for Public Transport Services – H-1119 Than Károly utca 3-5. Budapest, Hungary -

Tibor Sipos - Budapest University of Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Department of Transport Technology and Economics – H-1111 Műegyetem rakpart 3. Budapest, Hungary & KTI Institute for Transport Sciences Nonprofit Ltd., Directorate for Research and Innovation – H-1119 Than Károly utca 3-5. Budapest, Hungary -


Examining the traffic of border crossing points is a priority task due to the exploitation of the advantages of the national economy. An essential part in this process is the examination of the autocorrelation in the data. In this article, a theoretical approach was used: the geographically located physical parameters were removed, and random networks were generated and analysed to investigate the effect of autocorrelation. Spatial autocorrelation could explain up to nearly 50 percent of the effects with a well-chosen spatial weight matrix. This article can also be interpreted as the first element of a research series, thus defining future research directions and the steps of generalizability of the models is crucial.

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