Impacto do tempo de resposta elevado do motorista na fluidez do tráfego em interseções semaforizadas

Abstract

Signalized intersections are the major bottlenecks of road infrastructure, they are the highest rates of congestion and accidents, due to capacity restrictions and traffic movement conflicts, and one of the factors for capacity restriction is the driver's response time. Especially when these are occurring to some type of distraction, causing high Response Times, which negatively impact the road flow, increase the delay, reaction time, and saturation headways. Although there are some studies that investigate the Response Time of drivers, there are gaps in the modeling of this phenomenon at signalized intersections, and as it is difficult to observe in the field, it is necessary to use a micro-simulation tool, so that it can be analyzed several scenarios and their impacts. This study has the general objective of modeling and analyzing the impacts of high response time (TR) of drivers on traffic performance and on the capacity of traffic light intersections. The method consists of data collection, statistical modeling of the TR, implementation of the TR in VISSIM, comparison between scenarios with high TR and the analysis of its impact on performance and capacity measures. Statistical analyzes showed that the average TR of the 1st vehicle in the queue is higher than that of the other positions and that the Log-Normal distribution was the one that best represents the TR data. Through the VISSIM API, the drivers' TR distributions were incorporated into the simulator, one for the 1st position and one for the other positions. The implemented model provided a delay and average queue higher than the standard in the model, and a lower capacity, confirming the importance of the correct modeling of this variable in the estimation of traffic performance. Regarding the influence of the high TR on performance measures and capacity, it was observed that the greatest impacts related to the delay were caused when the high TR occurred in the positions closest to the retention range, in relation to the average row size, there were no significant differences between the positions in which the high TR occurred, however, there was a significant effect when compared to the model without the programmed high TR, in which the average row size was smaller than the simulated scenarios. Regarding capacity, the scenarios that had high TR in all cycles showed lower capacities than the model without the programmed high TR, however, there were no significant differences when the position of the high TR was analyzed.