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Title:

Using Parallel Particle Swarm Optimization for Auto-Tuning of Traffic Micro-simulations in Heterogeneous Conditions

Accession Number:

01517512

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

Abstract:

This study contributes towards enhancing two dimensions of traffic micro-simulations. Firstly, it provides a methodology to reduce the calibration time and effort of micro-simulation models by integrating knowledge of multithreading techniques and evolutionary algorithm. Secondly, it implements this methodology to calibrate a traffic micro-simulation with specific consideration of heterogeneity in traffic stream. The first contribution looks at the importance of calibration and its related difficulties. It applies the particle swarm optimization algorithm for auto calibration of traffic micro-simulations simplifying the process by eliminating human intervention during trial-and-error procedures. To shorten the execution time, parallelization of the algorithm was implemented using 32 CPUs in this study. The results implied that this method could reduce the running time by approximately 25 times when compared to unparalleled evolutionary algorithms. The second contribution deals with the different behavior of drivers in heterogeneous traffic conditions. This consideration could be very important, in particular when considering the increasing number of heavy vehicles on the road. The developed parallel particle swarm optimization algorithm was implemented as a case study to calibrate a micro-simulation model which specifically considers heavy vehicles and passenger cars and their interactions. The method was also used for calibration of the micro-simulation with the existing models. The results show that this approach could enhance the performance of micro-simulations in estimation of traffic measurements.

Supplemental Notes:

This paper was sponsored by TRB committee AHB45-1 Traffic Flow Theory and Characteristics Special Paper Review.

Monograph Accession #:

01503729

Report/Paper Numbers:

14-2296

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Aghabayk, Kayvan
Sarvi, Majid
Forouzideh, Nefiseh
Young, William

Pagination:

16p

Publication Date:

2014

Conference:

Transportation Research Board 93rd Annual Meeting

Location: Washington DC
Date: 2014-1-12 to 2014-1-16
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Subject Areas:

Data and Information Technology; Freight Transportation; Highways; I71: Traffic Theory; I72: Traffic and Transport Planning

Source Data:

Transportation Research Board Annual Meeting 2014 Paper #14-2296

Files:

TRIS, TRB, ATRI

Created Date:

Jan 27 2014 2:49PM