2026-09-19T17:35:34Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/53742024-05-20T06:50:11Zcom_10259_4204com_10259_5086com_10259_2604col_10259_5373

Rojo Arce, Marta 2020-07-13T10:29:13Z 2020-07-13T10:29:13Z 2020-07 http://hdl.handle.net/10259/5374 10.3390/su12145536 2071-1050 Assignment methodologies attempt to determine the traffic flow over each network arc based on its characteristics and the total flow over the entire area. There are several methodologies—some fast and others that are more complex and require more time to complete the calculation. In this study, we evaluated different assignment methodologies using a computer simulation and tested the results in a specific case study. The results showed that the “all-or-nothing” methods and the incremental assignment methods generally yield results with an unacceptable level of error unless the traffic is divided into four or more equal parts. The method of successive averages (MSA) was valid starting from a relatively low number of iterations, while the user equilibrium methodologies (approximated using the Frank and Wolfe algorithm) were valid starting from an even lower number of iterations. These results may be useful to researchers in the field of computer simulation and planners who apply these methodologies in similar cases. Research Contract entitled “Simulación y Análisis de Tráfico dentro del Estudio Informativo de la Autovía Orbital B-40” (Simulation and Traffic Analysis within the Study Report of the B-40 Orbital Highway) between GPYO Innova, S.L. and the University of Burgos (Spain) with reference number W24T06. application/pdf eng MDPI Sustainability. 2020, V. 12, n. 14, 5536 https://doi.org/10.3390/su12145536 Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess assignment models Traffic Simulation Traffic studies Transport planning Transportes Transportation Evaluation of traffic assignment models through simulation info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Sustainability 12 14 5536