A New Minimum Delay Model for Multi-Lane Traffic Circles

Tanyel, Serhan; Çalışkanelli, Süheyla Pelin; Özuysal, Mustafa

doi:10.18400/tekderg.557823

Cited by 2 publications

(2 citation statements)

References 22 publications

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“…The tra c volume will uctuate over time, so, designing the green time at the beginning of a phase for the present phase can be more compatible with the present tra c situation. During the test process, Our results also support that designing a phase-based controller can be more accurate as explained by [57,58]. The controller in this study used Optimum cycle time extracted from the VISSIM simulator.…”

Section: Resultssupporting

confidence: 83%

Traffic Signal Prediction Based on ANFIS and Metaheuristic Algorithms Applied to a Vissim-Based Simulated Intersection

Shahkar

Oruç

Yelghi³

2023

Preprint

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Traffic signs are among the most important traffic equipment that are used in urban and non-urban areas and their purpose is to increase road volume and reduce delays while ensuring safe movement. Over the years, due to the growing trend of car production and car use, which has increased urban and road traffic, traffic signs have increased and become more diverse and efficient. One of these traffic control methods at intersections is the use of traffic signal scheduling techniques, which despite the advantages of this method has a major drawback, and that is that due to the dynamic behavior of traffic, this method has issues in predicting traffic signal timing especially in times of peak traffic. Designing appropriate green times for traffic signal lights with Adaptive Neuro-Fuzzy Inference System (ANFIS) technique in traffic signal controller is a feasible solution to tackle this issue in urban network congestion during peak hours. The capability to learn from experience is one of the specifications of ANFIS that makes these techniques appropriate to mention genuine universe challenges. ANFIS Traffic Signal Controller is used to control the traffic density of an intersection so that it can reduce the queue length and latency to the minimum optimal time expected. ANFIS Traffic Controller is an intelligent controller with automatic learning sets the appropriate green time for each phase of the traffic light at the beginning of the phase, and the system generally depends on traffic information. The controller uses metaheuristic algorithms to tune ANFIS parameters during learning time. The first part of this article concerns the simulation of an isolated intersection in a VISSIM simulator, for the generation of the new phase distribution of it (optimum cycle). In the second part, ANFIS with metaheuristic algorithms is modelized and applied to the VISSIM simulated intersection. In the modelized system, for training and testing phases, 90 samples of newly generated data sets from VISSIM, and 40 others were considered respectively. By tuning the parameters using metaheuristic algorithms, we tried to increase the accuracy of the ANFIS network prediction to demonstrate the high performance of the ANFIS network in predicting and controlling traffic in intersections. The predicting system uses real-time data to predict the signal time. Results of the analysis demonstrated that our predictor system with ANFIS-GA indicates better predicts in comparison to ANFIS-PSO and ANFIS-HS. The predictor system presented a total and Relative Mean Square Error of 2.9619 and 8.4215 in the train set and 4.2209 and 11.8501 in the test respectively. The designed prediction model in the field of complex data showed an acceptable level of reliability and flexibility.

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Section: Resultssupporting

confidence: 83%

Traffic Signal Prediction Based on ANFIS and Metaheuristic Algorithms Applied to a Vissim-Based Simulated Intersection

Shahkar

Oruç

Yelghi³

2023

Preprint

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“…[45] ile Tanyel v.d. [46]'nin çalışmalarında da kullanılmış olan aşağıdaki yöntem tercih edilmiştir.…”

Section: Aralik Kabulü Değeri̇ni̇n Engelleyi̇ci̇ Akim Ve Kavşak Geome...unclassified

Işıksız Kavşaklarda Kritik Aralık Kabulü İçin Yeni Bir Yaklaşım

HIZARCI,

TANYEL,

DÜNDAR

et al. 2023

Turkish Journal of Civil Engineering

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Bu çalışma kapsamında İzmir’de yer alan 4 ışıksız kavşaktan toplanan verilerden yararlanarak, farklı manevralar için bağıntılar geliştirilmeye çalışılmıştır. Çalışmada, kritik aralık kabul değerinin, düşük ana yol hacim değerleri altında önemli oranda değişkenlik gösterdiği; ancak ana yol trafik akımı yüksek değerlere ulaştığında sürücülerin daha kısa aralıkları kabul ettikleri görülmüştür. Aralık kabul değerinin belirlenmesinde, kavşağa giriş yapacak sürücünün manevrasından daha çok; uygun aralık bulmaya çalıştığı manevranın daha etkin olduğu görülmüştür. Çalışmanın bir diğer çıktısı da, özellikle düşük ana yol trafik akımı etkisi altında sürücü davranışlarının daha etkili olduğu ve davranış farklılıklarının modele katılmasıyla sahada gözlemlenen değerlere daha sağlıklı biçimde ulaşılabileceği anlaşılmıştır.

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A New Minimum Delay Model for Multi-Lane Traffic Circles

Cited by 2 publications

References 22 publications

Traffic Signal Prediction Based on ANFIS and Metaheuristic Algorithms Applied to a Vissim-Based Simulated Intersection

Traffic Signal Prediction Based on ANFIS and Metaheuristic Algorithms Applied to a Vissim-Based Simulated Intersection

Işıksız Kavşaklarda Kritik Aralık Kabulü İçin Yeni Bir Yaklaşım

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