This chapter describes the genetic algorithm-based calibration procedure for a microscopic traffic simulation model focusing on freeways and modern roundabouts. For both case studies, the genetic algorithm tool in MATLAB® was applied in order to reach the convergence between the outputs from Aimsun microscopic simulator and the observed data. The automatic interaction with Aimsun software was implemented through an original external Python script. Results showed that the genetic algorithm-based calibration procedure gave a better match to the observed data than simple manual calibration and the efficiency of the calibration efforts resulted significantly improved. At last, the calbrated model was applied to calculate the passenger car equivalents for heavy vehicles which represent the starting point for operational analysis of road and intersections.
|Title of host publication||Genetic Algorithms: Advances in Research and Applications|
|Number of pages||54|
|Publication status||Published - 2017|
|Name||COMPUTER SCIENCE, TECHNOLOGY AND APPLICATIONS|
All Science Journal Classification (ASJC) codes
- Computer Science(all)
Giuffre', O., Grana', A., Tumminello, M. L., & Sferlazza, A. (2017). Application of a Genetic Algorithm in Calibration of Traffic Microsimulation Models. In Genetic Algorithms: Advances in Research and Applications (pp. 59-112). (COMPUTER SCIENCE, TECHNOLOGY AND APPLICATIONS).