A multi-objective optimization problem of ramp metering and dynamic route guidance is presented. The problem domain, a freeway integration control application considers the efficiency and equity of system, is formulated as a multi-objective optimization problem. The Gini coefficient is adopted in this study as an indicator of equity. The control strategy’s effect is demonstrated through its application to the simple freeway network. Analyses of simulation results using this approach show the equity of the system have a significant improvement over traditional control, especially for the case of large traffic demand. Using the multi-objective optimization approach, the Gini coefficient of the network has been reduced by 55% compared to traditional method.
Multi-Objective Optimization of Freeway Network Traffic Flow Using Particle Swarm Optimization
Applied Mechanics and Materials ; 713-715 ; 1777-1781
13.01.2015
5 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Improved multi-objective particle swarm optimization algorithm
British Library Online Contents | 2013
|Training Neural Networks to Detect Freeway Incidents by Using Particle Swarm Optimization
Transportation Research Record | 2004
|Training Neural Networks to Detect Freeway Incidents by Using Particle Swarm Optimization
Online Contents | 2004
|E-puck motion control using multi-objective particle swarm optimization
BASE | 2022
|