A smart algorithm for traffic lights intersections control in developing countries

Olaya-Quiñones, Jose D.; Perafan-Villota, Juan C.

doi:10.1109/colcaci52978.2021.9469581

Cited by 1 publication

(1 citation statement)

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“…In [2] a development towards wireless connectivity for traffic light control is presented. However, the development of intelligent systems for traffic light control presents a wide field of development, for example, based on the number of vehicles on the road [3], the action that may require image processing algorithms for this identification [4], [5], among other similar [6]- [9]. One of them is a study [10], which presents an intelligent traffic light system for emergency vehicles, using strategies for route identification and traffic light status change, mainly using the message queuing telemetry transport (MQTT) protocol.…”

Section: Introductionmentioning

confidence: 99%

Ambulance detection for smart traffic light applications with fuzzy controller

Moreno

Baquero²,

Umaña³

2022

IJECE

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<p>In the development of intelligent cities, the automation of vehicular mobility is one of the strong points of research, where intelligent traffic lights stand out. It is essential in this field to prioritize emergency vehicles that can help save lives, where every second counts in favor of the transfer of a patient or injured person. This paper presents an artificial intelligence algorithm based on two stages, one is the recognition of emergency vehicles through a ResNet-50 and the other is a fuzzy inference system for timing control of a traffic light, both lead to an intelligent traffic light. An application of traffic light vehicular flow control for automatic preemption when detecting emergency vehicles, specifically ambulances, is oriented. The training parameters of the network, which achieves 100% accuracy with confidence levels between 65% with vehicle occlusion and 99% in direct view, are presented. The traffic light cycles are able to extend the green time of the traffic light with almost 50% in favor of the road that must yield the priority, in relation to not using the fuzzy inference system.</p>

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