Calibration of microscopic traffic flow simulation models using a memetic algorithm with solis and wets local search chaining (MA-SW-Chains)

Editors

H.J. Escalante, M. Montes-y-Gomez, A. Segura, J. de Dios Murillo (Eds.)

Document Type

Conference Proceeding

Publication Date

1-1-2016

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Publisher

Springer Verlag

Volume

10022 LNAI

First page number:

365

Last page number:

375

Abstract

Traffic models require calibration to provide an adequate representation of the actual field conditions. This study presents the adaptation of a memetic algorithm (MA-SW-Chains) based on Solis and Wets local search chains, for the calibration of microscopic traffic flow simulation models. The effectiveness of the proposed MA-SW-Chains approach was tested using two vehicular traffic flow models (McTrans and Reno). The results were superior compared to two state-of-the-art approaches found in the literature: (i) a single-objective genetic algorithm that uses simulated annealing (GASA), and (ii) a stochastic approximation simultaneous perturbation algorithm (SPSA). The comparison was based on tuning time, runtime and the quality of the calibration, measured by the GEH statistic (which calculates the difference between the counts of real and simulated links). © Springer International Publishing AG 2016.

Keywords

Calibration; Local search chaining; Memetic algorithm; Single-objective optimization; Solis and wets; Traffic flow simulation

Language

English

Find It

UNLV article access

Share

COinS