Adaptive Traffic Light Control System Using Wireless Sensors Networks

Rida, Nouha; Ouadoud, Mohammed; Hasbi, Abderrahim; Chebli, Samira

doi:10.1109/cist.2018.8596620

Cited by 27 publications

(9 citation statements)

References 11 publications

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“…the dynamic controller uses traffic status information that can be collected in real time by inductive loops. [13], cameras [14], [15] [16], radars, VANET (ad hoc network for vehicles) [17], [18] or wireless sensor network [4], [19], [20], [21].…”

Section: Related Workmentioning

confidence: 99%

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Ant Colony Optimization for Real Time Traffic Lights Control on a Single Intersection

Rida

Ouadoud

Hasbi³

2020

Int. J. Interact. Mob. Technol.

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In this paper, we present a new scheme to intelligently control the cycles and phases of traffic lights by exploiting the road traffic data collected by a wireless sensor network installed on the road. The traffic light controller determines the next phase of traffic lights by applying the Ant Colony Optimazation metaheuristics to the information collected by WSN. The objective of this system is to find an optimal solution that gives the best possible results in terms of reducing the waiting time of vehicles and maximizing the flow crossing the intersection during the green light. The results of simulations by the SUMO traffic simulator confirm the preference of the developed algorithm over the predefined time controller and other dynamic controllers.

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Section: Related Workmentioning

confidence: 99%

“…In the literature we find several theoretical models for adaptive management traffic lights: fuzzy logic [1], fluid mechanics [2], [19], [16] [9], neural networks [3], queues [4], genetic algorithm [3] and others.…”

Section: Related Workmentioning

confidence: 99%

Ant Colony Optimization for Real Time Traffic Lights Control on a Single Intersection

Rida

Ouadoud

Hasbi³

2020

Int. J. Interact. Mob. Technol.

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“…We proposed the "Smallest phase first" algorithm which gives priority to phases with the smallest queues. Subsequently, in [22], we integrated the waiting time in the algorithm proposed in [21].…”

Section: Related Workmentioning

confidence: 99%

Coordinated Signal Control System in Urban Road Network

Rida

Ouadoud

Hasbi³

2020

Int. J. Onl. Eng.

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Road congestion has become one of the major problems of urban cities due to the growth in the number of vehicles and the limitation of road infrastructure. The consequences of this congestion can be seen through a difficult movement of vehicles, an increase in CO2 emissions, increasing energy consumption, and stress for drivers. Intelligent Transport Systems (ITS) based on wireless sensor networks (WSN) have emerged with new solutions and application potentials in the context of the Intelligent city. In this article, we study an approach of using a wireless sensor network to control the traffic lights of several intersections and optimize their performance by reducing the average waiting time of users. the proposed adaptive traffic light controller determines the traffic lights sequence in real time based on the current traffic situation at the local intersection, the expected arrivals and the degree of congestion at destination intersections. To evaluate our approach, we construct an intersection network of twenty-four intersections with high traffic intensity using the SUMO simulator, the results of the simulation demonstrate the efficiency and practicality of the proposed algorithm.

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“…Another researcher examined an adaptive traffic light system that uses wireless sensor networks [8]. The research focus was more on the traffic control algorithm.…”

Section: Adaptive Traffic Lights Control Systemmentioning

confidence: 99%

Adaptive Traffic Light Control Based on Actual Condition Using Google Map API

Arkanuddin

Sulistyo

Persada

2019

IJITEE

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Traffic congestion is one of the main problems in transportation sector and it causes a lot of drawbacks to public. The traffic light system is used to reduce the level of occurring traffic congestion. Generally, the available traffic light systems use a fixed time setting. This old traffic control system is no longer able to manage the ever-changing traffic conditions effectively and efficiently, causing a long queue of vehicles. To overcome this problem, a traffic light control system that can adapt to actual conditions of road density and can run automatically is offered. This system utilizes Google Map API as a road density data source. The result of this study is a traffic control system that can adjust the green light time duration based on the obtained density values and density trends, simulation of this adaptive system as well as simulation results analysis. A prototype of this adaptive control system was also produced in this study.

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Adaptive Traffic Light Control System Using Wireless Sensors Networks

Cited by 27 publications

References 11 publications

Ant Colony Optimization for Real Time Traffic Lights Control on a Single Intersection

Ant Colony Optimization for Real Time Traffic Lights Control on a Single Intersection

Coordinated Signal Control System in Urban Road Network

Adaptive Traffic Light Control Based on Actual Condition Using Google Map API

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