Application of a Genetic Algorithm in Calibration of Traffic Microsimulation Models

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.
Original languageEnglish
Title of host publicationGenetic Algorithms: Advances in Research and Applications
Pages59-112
Number of pages54
Publication statusPublished - 2017

Publication series

NameCOMPUTER SCIENCE, TECHNOLOGY AND APPLICATIONS

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Fingerprint Dive into the research topics of 'Application of a Genetic Algorithm in Calibration of Traffic Microsimulation Models'. Together they form a unique fingerprint.

  • Cite this

    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).