Sinyalize Kavşaklarda Gecikmeyi Minimize Etmekte Kullanılan Optimizasyon Tekniklerinin Karşılaştırılması: PSO ve GA

Öz

Kavşak gecikmelerini en aza indirmek günümüzün akıllı şehirlerinde önemli bir zorluktur. Gecikme minimizasyonu için farklı yaklaşımlar olsa da bunların çoğu Karayolu Kapasite El Kitabı (ABD) tarafından tanımlanan aynı doğrusal olmayan gecikme formülünü kullanır. Sonuç olarak, gecikme çıktısını en aza indiren optimum girdileri bulmak için hızlı ve hassas bir algoritma seçmek kritik bir karardır. Bu makalede, kavşaklardaki kişi gecikmelerini en aza indirmek için yenilikçi bir sistem geliştirme çalışmamızın bir parçası olarak en iyi optimizasyon algoritmasının seçimindeki deneyimimizi paylaşıyoruz. En iyi bilinen iki algoritmayı karşılaştırdık: Genetik Algoritmalar (GA) ve Parçacık Sürü Optimizasyonu (PSO). Aynı popülasyon boyutu ve iterasyon sayısı kullanıldığında PSO'nun GA'dan 7 kat daha hızlı ve 17 kat daha hassas olduğu gösterilmiştir.

Anahtar Kelimeler

• Adaptif trafik sinyal kontrolü
• Genetik algoritmalar
• Parçacık sürü optimizasyonu
• Kavşak gecikme minimizasyonu
• Gerçek zamanlı eniyileme

Comparison of Optimization Techniques for Delay Minimization in Signalized Intersections: PSO vs GA

Abstract

Minimizing intersection delays is an important challenge in today’s smart cities. Even there are different approaches for delay minimization most of them uses the same nonlinear delay formula defined by Highway Capacity Manual (US). As a result choosing a fast and precise algorithm for finding the optimum inputs minimizing the delay output is a critical decision. In this paper we share our experience in selection of best optimization algorithm as a part of our work of developing an innovative system to minimize person delays in intersections. We compared two best known algorithms: Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). It is shown that using the same population size and number of iterations PSO is 7x faster and 17x more precise than GA.

Keywords

• Adaptive traffic signal control
• Genetic algorithms
• Particle swarm optimization
• Intersection delay minimization
• Real-time optimization.

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