Traffic Optimization Through Waiting Prediction and Evolutive Algorithms.

Francisco García; Helena Hernández; María N. Moreno García; Juan F. De Paz; Vivian F. López; Javier Bajo

doi:10.9781/ijimai.2023.12.001

Authors

Francisco García University of Salamanca.
Helena Hernández University of Salamanca.
María N. Moreno García University of Salamanca.
Juan F. De Paz University of Salamanca.
Vivian F. López University of Salamanca.
Javier Bajo Universidad Politécnica de Madrid.

DOI:

https://doi.org/10.9781/ijimai.2023.12.001

Keywords:

Evolutionary Algorithm, Prediction Systems, Traffic Optimization, Traffic Simulator

Supporting Agencies

This work was supported by the Spanish Agencia Estatal de Investigación. Project Monitoring and tracking systems for the improvement of intelligent mobility and behavior analysis (SiMoMIAC). Sistema de procesamiento distribuido para la optimización en movilidad y transporte - Distributed processing system for mobili-ty and transport optimization PID2019-108883RB-C21 / AEI / 10.13039/501100011033. PID2019-108883RB-C22 - Sistema de monitorizacion y control para el apoyo a la toma de decisiones en el mantenimiento de infraestructuras. Francisco García Encinas’ research was partly supported by the Spanish Ministry of Universities (FPU Fellowship under Grant FPU19/02455).

Abstract

Traffic optimization systems require optimization procedures to optimize traffic light timing settings in order to improve pedestrian and vehicle mobility. Traffic simulators allow obtaining accurate estimates of traffic behavior by applying different timing configurations, but require considerable computational time to perform validation tests. For this reason, this project proposes the development of traffic optimizations based on the estimation of vehicle waiting times through the use of different prediction techniques and the use of this estimation to subsequently apply evolutionary algorithms that allow the optimizations to be carried out. The combination of these two techniques leads to a considerable reduction in calculation time, which makes it possible to apply this system at runtime. The tests have been carried out on a real traffic junction on which different traffic volumes have been applied to analyze the performance of the system.

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