Smart Traffic Light based on IoT and mBaaS using High Priority Vehicles Method

Mahali, Muhammad Izzuddin; Marpanaji, Eko; Dewanto, Satriyo Agung; Wulandari, Bekti; Rochayati, Umi; Hasanah, Nur

doi:10.1109/eecsi.2018.8752694

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…Ultimately, Mahali et al [26] aims to build a smart traffic light as a solution with the goal of making the prioritized vehicle journey smooth when crossing the road with smart traffic light. A few meters before crossing, smart traffic application will send the location to mobile backend as a service (mBaaS) and continue to be read by smart traffic controller using internet.…”

Section: Related Workmentioning

confidence: 99%

Integrated tripartite modules for intelligent traffic light system

Kareem

Hoomod

2022

IJECE

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<span>The traffic in urban areas is primarily controlled by traffic lights, contributing to the excessive, if not properly installed, long waiting times for vehicles. The condition is compounded by the increasing number of road accidents involving pedestrians in cities across the world. Thus, this work presents an integrated tripartite module for an intelligent traffic light system. This system has enough ingredients for success that can solve the above challenges. The proposed system has three modules: the intelligent visual monitoring module, intelligent traffic light control module, and the intelligent recommendation module for emergency vehicles. The monitor module is a visual module capable of identifying the conditions of traffic in the streets. The intelligent traffic light control module configures many intersections in a city to improve the flow of vehicles. Finally, the intelligent recommendation module for emergency vehicles offers an optimal path for emergency vehicles. The evaluation of the proposed system has been carried out in Al-Sader city/Bagdad/Iraq. The intelligent recommendation module for the emergency vehicles module shows that the optimization rate average for the optimal path was in range 67.13% to 92%, where the intelligent traffic light control module shows that the optimization ratio was in range 86% to 91.8%.</span>

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Section: Related Workmentioning

confidence: 99%

Integrated tripartite modules for intelligent traffic light system

Kareem

Hoomod

2022

IJECE

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“…The search is divided into four sections [2], [3]. Section 1 gives a global view about the fuzzy logic, fuzzy logic sets, using the fuzzy logic in traffic systems.…”

Section: Introductionmentioning

confidence: 99%

“…the function as MAX function. By evaluating the fuzzy select rule we will decide which street will open first as four values:[street1, street2, street3, street4] =[3,6,9,12]. Else select in next epochs the max function.…”

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confidence: 99%

A Controlling Traffic Light system using Fuzzy logic

Gdeeb

2023

JQCM

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Automatic control systems are a new advanced system uses computers and hardware controllers to act as a driving system. Increasing in cars numbers while we have the same infrastructure caused a large traffic problem so we need automatic adaptive controllers to control the open and close tasks of traffic light system. Fuzzy Logic is a conversation from classical logic with values of 0 for false and 1 for true to a range of values between 0 and 1. This study aims to create an adaptive traffic control system using fuzzy logic and image processing, we have a camera on each traffic light to calculate the number of cars there and then we feed the number of cars to a fuzzy logic system to decide which traffic light must become on

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Systematic approach to a government‐led technology roadmap for future‐ready adaptive traffic signal control systems

Balaci,

Suh

2024

Systems Engineering

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The economic impact of inefficient traffic control systems is significant owing to prolonged commute durations, and increased energy consumption. Traffic signal control systems (TSCSs) significantly influence traffic flows at intersections. Therefore, adaptive TSCSs (ATSCSs) that can adjust to traffic conditions in real‐time have been proposed as more efficient alternatives. However, the expensive implementation of these systems highlights the need for judicious investments in appropriate technologies and infrastructure. Therefore, a comprehensive technology roadmap should be built that guides the future development of traffic control and the infusion of technologies to address traffic needs. Additionally, as ATSCSs are developed and managed by local governments, the perspective of a government‐led technology roadmap is required to guide the roadmap development and implementation. Although studies have explored technology roadmaps across numerous sectors, the viewpoint of roadmap development guided by government entities is frequently neglected despite the role of these entities in shaping technological policies, underwriting research and development initiatives, and driving nationwide innovation strategies. In this study, a comprehensive framework is proposed for developing technology roadmaps tailored for systems and technologies led by governmental entities. This framework has been adapted from the Advanced Technology Roadmap Architecture (ATRA) and brought original adjustments thereby addressing the research gap. The study also presents strategic recommendations for the ATSCS implementation in South Korea, integrating systems engineering principles for a holistic approach to technological advancements. The framework can be replicated to serve as a guide for governments seeking to implement effective and efficient technology roadmaps for public infrastructure systems.

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Smart Traffic Light based on IoT and mBaaS using High Priority Vehicles Method

Cited by 6 publications

References 8 publications

Integrated tripartite modules for intelligent traffic light system

Integrated tripartite modules for intelligent traffic light system

A Controlling Traffic Light system using Fuzzy logic

Systematic approach to a government‐led technology roadmap for future‐ready adaptive traffic signal control systems

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