ABSTRACT
A calibration procedure for microscopic simulation models based on a genetic algorithm is proposed. Focus is made on single-lane roundabouts for which many random factors such as gap-acceptance affect operations. A comparison is performed between the capacity functions based on a meta-analytic estimation of critical and follow up headways and simulation outputs of a roundabout built in Aimsun microscopic simulator. Aimsun parameters were optimized using the genetic algorithm tool in MATLAB® which automatically interacted with Aimsun through a Python interface. Results showed that applying the genetic algorithm in the calibration process of the microscopic simulation model, a good match to the capacity functions was reached with the optimization parameters set. By this way, automation of the calibration process results effective for analysts which use traffic microsimulation for real world case studies in the professional sphere.
