Master of Science in Engineering (MSE)
Civil and Environmental Engineering and Construction
First Committee Member
Second Committee Member
Third Committee Member
Fourth Committee Member
Number of Pages
This study proposes a methodology for the calibration of microscopic traffic flow simulation models by enabling simultaneous selection of traffic links and associated parameters. That is, any number and combination of links and model parameters can be selected for calibration. Most calibration approaches consider the entire network without enabling a specific selection of location and associated parameters. In practice, only a subset of links and parameters are used for calibration based on a number of factors such as expert local knowledge of the system. In this study, the calibration problem for the simultaneous selection of links and parameters was formulated using a mathematical programming approach. The proposed methodology is capable of calibrating model parameters model parameters, taking into consideration multiple performance measures and time periods simultaneously. The performance measures used in this study were volume and speed. The development of the methodology is independent of the characteristics of a specific traffic flow model. A genetic algorithm was implemented to determine the solution to the proposed mathematical program for the calibration of microscopic traffic flow models. In the experiments, two traffic models were calibrated. The first set of experiments included selection of links only, while all associated parameters were considered for calibration. The second set of experiments considered simultaneous selection of links and parameters. Results showed that the models were calibrated successfully subject to selection of a minimum number of links. All parameter values were reasonable and within constraints after successful calibration.
Calibration; CORSIM; Genetic Algorithm; Mathematical programming; Microscopic traffic flow; Traffic flow simulation
Shrestha, Kul Prasad, "Calibration of Microscopic Traffic Flow Models Enabling Simultaneous Selection of Specific Links and Parameters" (2017). UNLV Theses, Dissertations, Professional Papers, and Capstones. 3033.