As population increases, one of the factors affecting life is traffic. Efficient traffic management has a direct positive impact on issues such as time, carbon dioxide emissions, and fuel consumption. Today, an important parameter under the heading of traffic is the signalling systems for intersections, which are operated with fixed-time, semi-actuated, fully actuated, and fully adaptive control methods. In this study, an adaptive traffic management model is developed for signalised intersections. The adaptive traffic management model developed includes phase extension with minimum and maximum time intervals dependent on density and phase skip features. Additionally, the most distinctive feature of the model is its flexible phase structure rather than a sequential phase. The Heybe intersection, located within the boundaries of Antalya province, is modelled one-to-one in the simulation of urban mobility (SUMO) simulation programme with real intersection data. The developed adaptive traffic management model is applied to the Heybe intersection, and the effects of the model are revealed. Improvements obtained from the SUMO simulation programme were verified through visual inspection, and high-accuracy results were determined. As a result of the studies, it was found that the application of the adaptive traffic management model developed at Heybe intersection, which has approximately 50,000 vehicles passing daily, resulted in a 27.2 % improvement in the average delay per vehicle parameter, a 32.4 % improvement in the average waiting time per vehicle parameter, and a 16.7 % improvement in the average speed per vehicle parameter.

Günümüz sensör teknolojilerinin gelişimi ile saptanan veri çeşitliliği ve doğruluk oranları önemli oranda artmıştır. Tespit edilen verilerin çeşitliliği ve doğruluk oranlarının yüksek olmasıyla da yönetim algoritmalarının yetenekleri gelişmiş olup günlük yaşamımıza olumlu olarak çeşitli alanlarda yansımaktadır. Sinyalize kavşaklarda genel olarak sabit süreli sinyalizasyon sistemleri kullanılmaktadır. Ancak, son yıllarda trafik ile ilgili veri toplayan sensörler daha da geliştikçe yarı trafik uyarmalı, tam trafik uyarmalı ve adaptif trafik sinyalizasyon sistemleri yaygınlaşmaya başlamıştır. Araç sayısı, araç algılamaları, kuyruklanma, ortalama hız gibi trafik parametrelerine göre sinyalize kavşaktaki yeşil sürelerinin adaptif yönetilmesi gecikme, ortalama hız ve durma sayısı gibi önemli parametrelere olumlu yansımaktadır. Bu çalışmada örnek bir sinyalize kavşaktaki gerçek trafik verileri kullanılarak Aimsun simülasyon programı üzerinde simülasyon modellemesi gerçekleştirilmiştir. Ayrıca, bu sinyalize kavşak tam trafik uyarmalı olarak işletilerek kavşaktaki iyileşme yüzdeleri saptanmıştır. Tekirdağ il sınırları içerisinde yer alan ve günlük yaklaşık 30.000 adet araç geçen Santral Kavşağı’ndaki tam trafik uyarmalı sinyalizasyon yönetimi simülasyon çalışması sonucunda gecikmelerin ortalama %27,72 azaldığı, ortalama hızın ortalama %27,31 arttığı ve durma sayısının ortalama %25,54 azaldığı tespit edilmiştir.

Improving the performance at signalized intersections can be achieved through different management styles or sensor technologies. It is crucial that we measure the real-time impact of these variables on intersection performance. This study introduces a Bluetooth-based real-time performance measurement system applicable to all signalized intersections. Additionally, the developed method serves as a feedback tool for adaptive intersection management systems, providing valuable data input for performance optimization. The method developed in the study is applied at the Refik Cesur Intersection in the Polatlı district of Ankara where delay values are calculated based on traffic flows and data from Bluetooth sensors positioned at strategic locations. Initially, the intersection operated under a fixed-time signaling system, followed by a fully adaptive signaling system the next day. The performance of these two systems is compared using the Bluetooth-based application. The results show that the average delay per vehicle per day is 58.1 seconds/vehicle for the fixed-time system and 45.3 seconds/vehicle for the adaptive system. To validate the Bluetooth-based performance measurement system, the intersection is modeled and simulated using Aimsun Simulation Software Next 20.0.4. The simulation results confirm the findings of the Bluetooth-based analysis, demonstrating the effectiveness of the adaptive signaling system in reducing delays.