Evidence map›Paper›PMID 42430459›Full record

ArticlePloS one2026

Edge-intelligent safelink-V2X: A low-latency cooperative framework for real-time vulnerable road user protection.

Fayez Alanazi, Ammar Armghan, Ahmed Jamal Abdullah Al-Gburi, Amr Yousef

Abstract read
In one paragraph

Article in PloS one, 2026. 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.

Fayez AlanaziCivil Engineering Department, College of Engineering, Jouf University, Sakaka, Saudi Arabia.
Ammar ArmghanDepartment of Electrical Engineering. College of Engineering, Jouf University, Sakaka, Saudi Arabia.ORCID https://orcid.org/0000-0002-9062-7493
Ahmed Jamal Abdullah Al-GburiStrategic Research Institute (SRI), Asia Pacific University, Jalan Teknologi 5, Taman Teknologi Malaysia, Kuala Lumpur, Malaysia.
Amr YousefElectrical Engineering Department, College of Engineering, University of Business and Technology, Jeddah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The protection of Vulnerable Road Users (VRUs) remains a major challenge in modern transportation safety, as onboard line-of-sight and adverse weather conditions limit conventional onboard sensors. Existing systems that rely solely on vehicle-based sensing or on isolated communication struggle to provide timely, accurate alerts in dynamic urban environments. To address these shortcomings, this paper introduces SafeLink-V2X, a comprehensive Vehicle-to-Everything Cooperative Warning Framework designed to enhance safety for pedestrians, cyclists, and scooter riders. SafeLink-V2X employs Cellular Vehicle-to-Everything (C-V2X) and Dedicated Short-Range Communications (DSRC) protocols to enable direct data exchange of location, velocity, and heading between connected vehicles, smart infrastructure, and VRUs via smartphones or wearable tags. By applying sensor fusion and machine learning-based conflict prediction, the system identifies potential collision points and issues real-time, context-aware warnings through vehicle HMIs and VRU devices, promoting immediate evasive action. Evaluation on urban intersection simulations (detailed in Section 5) demonstrates that SafeLink-V2X reduces simulated collision probability by up to 91.4%, increases situational awareness measures by 44%, and lowers end-to-end alert latency by 30% compared to baseline onboard-only and communication-only systems under the same conditions.

Indexed as

Accidents, TrafficSafetyHumansPedestrians

Identifiers

PMID42430459
PMCPMC13354081

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.