Resilient Fog-Based Adaptive Traffic Control System

Traffic congestion is a growing problem in India, largely caused by the increasing number of vehicles. To address this, creating an adaptive traffic control system has become essential. To present a solution, this paper aims to create a resilient, adaptive traffic control system that dynamically adj...

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Vydáno v:International Conference on Computing, Communication, and Networking Technologies (Online) s. 1 - 7
Hlavní autoři: Matange, Ashwini, Taneja, Varun, Chaumal, Aarya, Buwa, Pallavi, Abraham, Jibi
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 06.07.2023
Témata:
Adaptive systems
Cameras
Cloud computing
Computer vision
Distributed databases
Feeds
Fog computing
Process control
Real-time systems
Simulation
Traffic control
ISSN:2473-7674
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Abstract Traffic congestion is a growing problem in India, largely caused by the increasing number of vehicles. To address this, creating an adaptive traffic control system has become essential. To present a solution, this paper aims to create a resilient, adaptive traffic control system that dynamically adjusts signal timings based on the current traffic density. The paper proposes introducing a Fog layer at each traffic junction to capture real-time video feeds and process them locally, with the final decision about dynamic signal control being taken in the Cloud. The validity of the solution is tested through simulations in SUMO. A Machine Learning model is trained in the Cloud to predict expected vehicle numbers to set adaptive signal times for contingency situations. The paper aims to demonstrate the resilience and performance of the system with the adaptive traffic signal control algorithm, potentially offering a solution to traffic congestion in India.
AbstractList Traffic congestion is a growing problem in India, largely caused by the increasing number of vehicles. To address this, creating an adaptive traffic control system has become essential. To present a solution, this paper aims to create a resilient, adaptive traffic control system that dynamically adjusts signal timings based on the current traffic density. The paper proposes introducing a Fog layer at each traffic junction to capture real-time video feeds and process them locally, with the final decision about dynamic signal control being taken in the Cloud. The validity of the solution is tested through simulations in SUMO. A Machine Learning model is trained in the Cloud to predict expected vehicle numbers to set adaptive signal times for contingency situations. The paper aims to demonstrate the resilience and performance of the system with the adaptive traffic signal control algorithm, potentially offering a solution to traffic congestion in India.
Author Matange, Ashwini
Buwa, Pallavi
Taneja, Varun
Chaumal, Aarya
Abraham, Jibi
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  givenname: Jibi
  surname: Abraham
  fullname: Abraham, Jibi
  email: ja.comp@coep.ac.in
  organization: COEP Tech,Dept. of Computer Engineering and Information Technology,Pune,India
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Snippet Traffic congestion is a growing problem in India, largely caused by the increasing number of vehicles. To address this, creating an adaptive traffic control...
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SubjectTerms Adaptive systems
Cameras
Cloud computing
Computer vision
Distributed databases
Feeds
Fog computing
Process control
Real-time systems
Simulation
Traffic control
Title Resilient Fog-Based Adaptive Traffic Control System
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