Detection of Traffic Density on Roads in VANET

Clicks: 1
ID: 313127
2023
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #55 of 705 articles by views in Journal of Computing & Biomedical Informatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 705 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Traffic Congestion is main problem in current traffic system and there are many other traffic issues that desirable to be defeat. VANET have the basis three aspects and it has been defined including Confidentiality, veracity and accessibility. The main problem is the securities how overcome the chances of data outflow, insecure interface, information gathering and sharing. The purpose of the research to analysis of traffic congestion that is related to availability of VANET resource in VANET environment and how can one determine which route has the least amount of traffic among many roads with heavy congestion, and also difficult task to use modern techniques are utilized for identifying the amount of vehicles on the roads. Now a days, forecasting traffic congestion is essential for modern life and travel. As infrastructure is advancing, many nations are dealing with the issue. To combat this, researchers have used Artificial Intelligence and VANNET Techniques to create various models to overcome the traffic problems. We have adopted the most recent technique, as it is much quicker in providing optimal outcomes.
Reference Key
imported_1777059279_69ebc5cfc993d Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zamia Ilyas, Irshad Ahmed Sumra, Tariq Mehboob
Journal Journal of Computing & Biomedical Informatics
Year 2023
DOI
DOI not found
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.