Evidence map›Paper›PMID 38894181›Full record

ArticleSensors (Basel, Switzerland)2024

Live Intersection Data Acquisition for Traffic Simulators (LIDATS).

Andrew Renninger, Sinan Ameen Noman, Travis Atkison, Jonah Sussman

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Andrew RenningerComputer Science, College of Engineering, University of Alabama, Tuscaloosa, AL 35401, USA.ORCID 0009-0008-2334-2472
Sinan Ameen NomanComputer Science, College of Engineering, University of Alabama, Tuscaloosa, AL 35401, USA.ORCID 0000-0002-9169-4452
Travis AtkisonComputer Science, College of Engineering, University of Alabama, Tuscaloosa, AL 35401, USA.ORCID 0000-0001-7258-7355
Jonah SussmanComputer Science, College of Engineering, University of Alabama, Tuscaloosa, AL 35401, USA.ORCID 0009-0009-8213-0290

Funding

United States Department of Transportation ACTION-6319
6 · The paper itself

Abstract

Real-time traffic signal acquisition and network transmission are essential components of intelligent transportation systems, facilitating real-time traffic monitoring, management, and analysis in urban environments. In this paper, we introduce a comprehensive system that incorporates live traffic signal acquisition, real-time data processing, and secure network transmission through a combination of hardware and software modules, called LIDATS. LIDATS stands for Live Intersection Data Acquisition for Traffic Simulators. The design and implementation of our system are detailed, encompassing signal acquisition hardware as well as a software platform that is used specifically for real-time data processing. The performance evaluation of our system was conducted by simulation in the lab, demonstrating its capability to reliably capture and transmit data in real time, and to effectively extract the relevant information from noisy and complex traffic data. Supporting a variety of intelligent transportation applications, such as real-time traffic flow management, intelligent traffic signal control, and predictive traffic analysis, our system enables remote data analysis and decisionmaking, providing valuable insights and enhancing the traffic efficiency while reducing the congestion in urban environments.

Indexed as

data acquisitiondigital twinintelligent transportation systemstraffic signal controllertraffic simulation

Identifiers

PMID38894181
PMCPMC11174745

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.