Evidence map›Paper›PMID 37571602›Full record

ArticleSensors (Basel, Switzerland)2023

Vehicular Traffic Flow Analysis and Minimize the Vehicle Queue Waiting Time Using Signal Distribution Control Algorithm.

Srinivasagam Solaiappan, Bharathi Ramesh Kumar, N Anbazhagan, Yooseung Song, Gyanendra Prasad Joshi, Woong Cho

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Srinivasagam SolaiappanDepartment of Mathematics, Anna University, University College of Engineering, Ramanathapuram 623513, Tamilnadu, India.
Bharathi Ramesh KumarDepartment of Mathematics, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600062, Tamilnadu, India.
N AnbazhaganDepartment of Mathematics, Alagappa University, Karaikudi 630003, Tamilnadu, India.ORCID 0000-0002-9146-2483
Yooseung SongElectronics and Telecommunications Research Institute, Daejeon 34129, Republic of Korea.
Gyanendra Prasad JoshiDepartment of Computer Science and Engineering, Sejong University, Seoul 05006, Republic of Korea.ORCID 0000-0002-5446-288X
Woong ChoDepartment of Electronics, Information and Communication Engineering, Kangwon National University, Samcheok-si, Gangwon State 25913, Republic of Korea.ORCID 0000-0002-9603-8673

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The real-time vehicular traffic system is an integral part of the urban vehicular traffic system, which provides effective traffic signal control for a large multifaceted traffic network and is a highly challenging distributed control problem. Coordinating vehicular traffic enables the network model to deliver an efficient service flow. Consider that there are four lanes of vehicular traffic in this situation, allowing parallel vehicle movements to occur without causing an accident. In this instance, the vehicular system's control parameters are time and vehicle volume. In this work, vehicular traffic flow is examined, and an algorithm to estimate vehicle waiting time in each direction is estimated. The effectiveness of the proposed vehicle traffic signal distribution control system by comparing the experimental results with a real-time vehicular traffic system is verified. This is also illustrated numerically.

Indexed as

data collection interruption JunctionMATLAB codingsignal parametersTSM modevehicular traffic classificationvehicular traffic congestionvehicular traffic detection

Identifiers

PMID37571602
PMCPMC10422242

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.