Análise do tempo de resposta dos motoristas na fluidez do tráfego de interseções semaforizadas microssimuladas

• Ano de defesa: 2024
• Autor(a) principal: Pedrosa, Wanderson Hugues de Vasconcelos
• Orientador(a): Castro Neto, Manoel Mendonça de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Área do conhecimento CNPq: CNPQ::ENGENHARIAS::ENGENHARIA DE TRANSPORTES
• Link de acesso: http://repositorio.ufc.br/handle/riufc/83247

Signalized intersections are critical points in road infrastructure, often prone to congestion and accidents due to capacity limitations and traffic conflicts. Driver reaction time (RT), particularly when elevated, is a behavioral variable that affects traffic performance at these locations, contributing to increased delays and reduced road capacity. This study aims to model and analyze the impact of driver RT on the traffic flow at signalized intersections using the microscopic simulation software AIMSUN and VISSIM. The methodology involved collecting RT and headway data at an intersection in Fortaleza, modeling the probability distribution of the observed RT (RT_obs), and implementing it in the simulation tools. Multiple scenarios were simulated, varying vehicle demand as well as the frequency and duration of RT, to evaluate their effects on average delay, saturation flow, and approach capacity. Results indicated that the log-normal distribution provided the best fit for RT data. The probabilistic modeling of RT showed that the first vehicle's RT (RT₁) in the queue was higher than that of the following vehicles. Incorporating probabilistic RT into the simulation increased delays and reduced capacity compared to the default model settings, particularly in AIMSUN. Scenarios where RT was deliberately elevated for the first vehicles in the queue exhibited the highest delays and lowest capacities. The study highlights that probabilistic modeling of RT significantly affects the flow efficiency of microsimulated signalized intersections, especially under saturated traffic conditions.