Developing a Capacity Model for Roundabouts Using SIDRA Calibrated via Simulation-Based Optimization

Various intersection structures are utilized in city-wide traffic network infrastructure by local transportation authorities to handle the exponentially increasing traffic loads in developing countries. In this regard, numerous studies have considered the notable positive contribution of the modern roundabouts in intersection performance as a prominent method utilized widely in our contemporary world. Properly designed roundabouts are vital components of sustainable transportation planning, as they significantly influence traffic efficiency, safety, and environmental performance. Accurate estimation of roundabout capacity is essential to ensure that they can accommodate anticipated traffic volumes without causing congestion, thereby contributing to energy efficiency and reducing emissions. Moreover, sustainable roundabout design supports the development of safer and more inclusive transportation networks by improving accessibility for all road users, thus strengthening the overall sustainability of urban mobility. The SIDRA (version 8.0), a traffic simulation software, is frequently employed in performance analysis and determining the effects of possible outcomes of different scenarios of roundabouts in today’s world. On the other hand, driver behaviors are found to play a significant role in software performance during the analysis process of roundabout capacity and performance. Therefore, in order to optimize the environmental factor (EF) representing driver behaviors in the SIDRA software, a Differential Evolution Algorithm-Based Bi-Level Calibration Model (DEBCAM) was introduced. Observation data collected from eight different modern-structured roundabouts through drones were run into the SIDRA simulation software; the average delays obtained were employed to estimate optimum EF values through DEBCAM. Observed average delay values were taken into consideration with respect to the delay values obtained as a result of the SIDRA calibration by using the GEH statistics. GEH values indicate the consistency of vehicle delay data obtained via the DEBCAM with observed data. Acquired results clearly suggest that the SIDRA software needs to be calibrated so that it can represent drivers’ behaviors. After determination of the optimum values of the EF parameter for calibration of the SIDRA software, the regression analysis was conducted through the Partial Least Squares (PLS) method. As a result of the analysis, a capacity estimation model was developed, which displayed a significant conformity with the SIDRA capacity estimation results. Our findings suggested that the parameter requirement for the roundabout capacity estimation can be decreased by employing the appropriate EF value for the roundabout that needs to be analyzed.