Saturation Flow Rate of Urban At-Grade Signalized Intersection Under Different Climatic Conditions (Case Study: Sattari-Mokhberi Intersection)

Abstract

This research aimed to compare the saturation flow rates of an urban at-grade signalized intersection under different climatic conditions in order to optimize the traffic light control system of this intersection. Data collection was performed with a video camera. The case studied was the intersection of Sattari-Mokhberi Intersection, in Tehran. The road surface conditions occurring in this intersection were divided into three classes: dry, wet, and snowy. Modeling and simulations were performed with the help of the software Vissim and Synchro. Model calibration was performed using the parameters “desired speed” and “acceleration/deceleration at zero speed”. Data analysis was performed using descriptive statistics and inferential statistics, including analysis of variance (ANOVA), Kolmogorov–Smirnov test, and Tukey and Scheffe tests. The saturation flow for dry, wet, and snowy road conditions was estimated to 1967, 1722, and 1607, respectively. Also, the relationship between saturation headway and sight distance in meters was modeled linearly and logarithmically. The analysis of videos showed that the mean desired speed in wet and snowy road conditions was, respectively, 23% and 36% lower than in normal conditions. The mean desired acceleration at zero speed in wet and snowy road conditions was, respectively, 24% and 30% lower than normal. The simulation results showed a 15% reduction in the total delay of the intersection after the implementation of weather-responsive schedules. The results of this research show that the benefits of adjusting the schedule of traffic lights based on weather are more pronounced in snowy conditions than in rainy conditions.