Fuzzy Control Under Time-Varying Universe and Phase Optimization in Traffic Lights (ICSSE 2020)

Zhou, Cang; Mo, Hong; Chen, Xiuru; Wen, Huan

doi:10.1007/s40815-020-00995-7

Cited by 8 publications

(2 citation statements)

References 21 publications

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“…Fuzzy logic is used to control the learning parameters. Additionally, a higher tracing value is one of its advantages [39,40]. Xu et al [41] used flow prediction machine learning in intelligent support vector regression for short-term traffic flow prediction.…”

Section: Urban Traffic Control Based On Fuzzy Controller and Multi-ag...mentioning

confidence: 99%

Improving the Performance of Single-Intersection Urban Traffic Networks Based on a Model Predictive Controller

2021

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The use of a Model Predictive Controller (MPC) in an urban traffic network allows for controlling the infrastructure of a traffic network and errors in its operations. In this research, a novel, stable predictive controller for urban traffic is proposed and state-space dynamics are used to estimate the number of vehicles at an isolated intersection and the length of its queue. This is a novel control strategy based on the type of traffic light and on the duration of the green-light phase and aims to achieve an optimal balance at intersections. This balance should be adaptable to the unchanging behavior of time and to the randomness of traffic situations. The proposed method reduces traffic volumes and the number of crashes involving cars by controlling traffic on an urban road using model predictive control. A single intersection in Tehran, the capital city of Iran, was considered in our study to control traffic signal timing, and model predictive control was used to reduce traffic. A model of traffic systems was extracted at the intersection, and the state-space parameters of the intersection were designed using the model predictive controller to control traffic signals based on the length of the vehicle queue and on the number of inbound and outbound vehicles, which were used as inputs. This process demonstrates that this method is able to reduce traffic volumes at each leg of an intersection and to optimize flow in a road network compared to the fixed-time method.

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Section: Urban Traffic Control Based On Fuzzy Controller and Multi-ag...mentioning

confidence: 99%

Improving the Performance of Single-Intersection Urban Traffic Networks Based on a Model Predictive Controller

2021

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“…Therefore, this article proposes a fuzzy control method for signals in a time-changing world and a way to develop the topological structure. The delay of vehicles was diminished, and the traffic potential of the intersection was improved in [22]. Traffic lights play a pivotal role in urban traffic control.…”

Section: Fuzzy Controller-based Traffic Controlmentioning

confidence: 99%

Traffic Control Prediction Design Based on Fuzzy Logic and Lyapunov Approaches to Improve the Performance of Road Intersection

2021

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Due to the increasing use of private cars for urbanization and urban transport, the travel time of urban transportation is increasing. People spend a lot of time in the streets, and the queue length of waiting increases accordingly; this has direct effects on fuel consumption too. Traffic flow forecasts and traffic light schedules were studied separately in the urban traffic system. This paper presents a new stable TS (Takagi–Sugeno) fuzzy controller for urban traffic. The state-space dynamics are utilized to formulate both the vehicle’s average waiting time at an isolated intersection and the length of queues. A fuzzy intelligent controller is designed for light control based upon the length of the queue, and eventually, the system’s stability is proved using the Lyapunov theorem. Moreover, the input variables are the length of queue and number of input or output vehicles from each lane. The simulation results describe the appearance of the proposed controller. An illustrative example is also given to show the proposed method’s effectiveness; the suggested method is more efficient than both the conventional fuzzy traffic controllers and the fixed time controller.

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Probabilistic Reasoning Using the Normal Distribution for Traffic Light Controller

Ahmadov

2024

Lecture Notes in Networks and Systems

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Fuzzy Control Under Time-Varying Universe and Phase Optimization in Traffic Lights (ICSSE 2020)

Cited by 8 publications

References 21 publications

Improving the Performance of Single-Intersection Urban Traffic Networks Based on a Model Predictive Controller

Improving the Performance of Single-Intersection Urban Traffic Networks Based on a Model Predictive Controller

Traffic Control Prediction Design Based on Fuzzy Logic and Lyapunov Approaches to Improve the Performance of Road Intersection

Probabilistic Reasoning Using the Normal Distribution for Traffic Light Controller

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