Optimal Design of Signal Controlled Road Networks Using Differential Evolution Optimization Algorithm

Huseyin Ceylan

doi:10.1155/2013/696374

Abstract

This study proposes a traffic congestion minimization model in which the traffic signal setting optimization is performed through a combined simulation-optimization model. In this model, the TRANSYT traffic simulation software is combined with Differential Evolution (DE) optimization algorithm, which is based on the natural selection paradigm. In this context, the EQuilibrium Network Design (EQND) problem is formulated as a bilevel programming problem in which the upper level is the minimization of the total network performance index. In the lower level, the traffic assignment problem, which represents the route choice behavior of the road users, is solved using the Path Flow Estimator (PFE) as a stochastic user equilibrium assessment. The solution of the bilevel EQND problem is carried out by the proposed Differential Evolution and TRANSYT with PFE, the so-called DETRANSPFE model, on a well-known signal controlled test network. Performance of the proposed model is compared to that of two previous works where the EQND problem has been solved by Genetic-Algorithms- (GAs-) and Harmony-Search- (HS-) based models. Results show that the DETRANSPFE model outperforms the GA- and HS-based models in terms of the network performance index and the computational time required.

Highlights

Configuring the traffic signal timings is a challenging problem in transportation engineering as it is important to minimize delays and total travel time in the road networks
This study proposes a traffic congestion minimization model in which the traffic signal setting optimization is performed through a combined simulation-optimization model
The EQuilibrium Network Design (EQND) problem, which has been formulated in the bilevel form, has been solved by searching for the optimal or near-optimal signal setting strategy on the upper level with the Differential Evolution (DE) optimization technique

Summary

Introduction

Configuring the traffic signal timings is a challenging problem in transportation engineering as it is important to minimize delays and total travel time in the road networks. Ceylan and Ceylan [30] developed a hybrid solution approach, where the metaheuristic Harmony Search (HS) and TRANSYT Hill-Climbing optimization methods were combined, considering drivers’ route choice behavior. The performance of their model was compared with that of the pure HS- and GA-based solution models. The Differential Evolution and TRANSYT with PFE (DETRANSPFE) model are developed for the solution of the EQND problem For this purpose, the Stochastic User Equilibrium (SUE) traffic assignment and traffic signal optimization problems are combined using the DE solution framework to minimize the network PI value.

Problem Formulation

Basics of the Differential Evolution Algorithm and DETRANSPFE Model

A N Origin-Destination

Numerical Example and Computational Comparison

Conclusions