Genetic-algorithm based approach for calibrating microscopic simulation models

In the transportation field simulation has been widely used as a powerful tool for the analysis and design of transportation systems. The proper calibration of the input parameters of microscopic simulation models is essential if the model is to replicate supply characteristics, demand characteristics, and their interaction. These parameters affect the interaction among the driver, vehicle, and the roadway environment systems. This paper presents an automatic calibration approach for microscopic simulation model that is based on a genetic algorithm. The proposed approach can be demonstrated on a section of US 290 in Houston and a section of I-37 in San Antonio, Texas.