Estimação da velocidade média em vias urbanas com uso do microssimulador Vissim

• Ano de defesa: 2016
• Autor(a) principal: Lacerda, Victor Macêdo
• Orientador(a): Castro Neto, Manoel Mendonça de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Transportes; Algoritmos genéticos; Trânsito urbano; Urban traffic modeling; Microscopic traffic simulation; Micro simulators calibration; Driving behavioral models
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/31543

The search for alternative solutions for high traffic congestions in big cities is becoming an increasingly concern of public management, since the growth of this issue impacts directly or indirectly the quality of life and productivity of users. In attempt to reliably predict the several scenarios for the various solution alternatives, micro simulators have been one of the main tools available and can assist in both the decision-making process and the evaluation of the cost/benefit. However, the major challenge is the high number of parameters and the degree of refinement of micro simulators models. Basically, the majority presents three models: car-following, which represents the longitudinal movement of traffic stream; lane-changing; lateral movements and gap acceptance. Such models may display, in conjunction, hundreds of parameters which, besides the individually impact on traffic performance measurements, can be correlated among each other, generating different driving behaviors. However, nowadays, a satisfactory calibration method aiming to model urban traffic performance is not available, having existing methods biased to automated calibration process. Therefore, this study aims to propose a calibration methodology of the behavioral VISSIM models for urban arterial roads considering all parameters and behavioral models that impact the longitudinal movement of the vehicles. Initially the effects of parameters on performance measure average speed will be understood and quantified, in order to classify all parameters in clusters. For each parameter set, a calibration strategy based on the respective target measure will be defined. Finally, two arterial corridors were calibrated and validated as a case study, in order to consolidate the established calibration methodology and compare it with the automated calibration process by genetic algorithms.