Evidence map›Paper›PMID 41829651›Full record

ArticleSensors (Basel, Switzerland)2026

Robust Localization and Tracking of VRUs with Radar and Ultra-Wideband Sensors for Traffic Safety.

Mouhamed Aghiad Raslan, Martin Schmidhammer, Ibrahim Rashdan, Fabian de Ponte Müller, Tobias Uhlich, Andreas Becker

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

6 authors.

Mouhamed Aghiad RaslanFaculty of Information Technology, Fachhochschule Dortmund-University of Applied Sciences and Arts, 44139 Dortmund, Germany.ORCID 0000-0003-1202-3202
Martin SchmidhammerGerman Aerospace Center, Institute of Communications and Navigation, (DLR), 82234 Wessling, Germany.ORCID 0000-0002-9345-142X
Ibrahim RashdanGerman Aerospace Center, Institute of Communications and Navigation, (DLR), 82234 Wessling, Germany.ORCID 0000-0001-9208-8078
Fabian de Ponte MüllerGerman Aerospace Center, Institute of Communications and Navigation, (DLR), 82234 Wessling, Germany.ORCID 0000-0002-2215-2174
Tobias UhlichFaculty of Information Technology, Fachhochschule Dortmund-University of Applied Sciences and Arts, 44139 Dortmund, Germany.ORCID 0009-0007-7731-6256
Andreas BeckerFaculty of Information Technology, Fachhochschule Dortmund-University of Applied Sciences and Arts, 44139 Dortmund, Germany.ORCID 0000-0001-7566-669X

Funding

Federal Ministry of Digital and Transport (Germany) 19F2232B
6 · The paper itself

Abstract

The increasing risk to Vulnerable Road Users (VRUs) at urban intersections necessitates advanced safety mechanisms capable of operating effectively under diverse conditions, including adverse weather like heavy rain. While optical sensors such as cameras and LiDAR often degrade in poor visibility, Radio Frequency (RF)-based systems offer resilient, all-weather tracking. This paper presents a novel approach to enhancing VRU protection by fusing two RF modalities: radar sensors and Ultra-Wideband (UWB) technology, a strong candidate for Joint Communication and Sensing (JCS). The research, conducted as part of the VIDETEC-2 project, addresses the limitations of existing vehicle-based and infrastructure-based systems, particularly in scenarios involving occlusions and blind spots. By leveraging radar's environmental robustness alongside UWB's precise, cost-effective short-range communication and localization, the proposed system delivers the framework for continuous vehicle and VRU tracking. The fusion of these sensor modalities, managed through a hybrid Kalman filter approach integrating an Unscented Kalman Filter (UKF) and an Extended Kalman Filter (EKF), allows reliable VRU tracking even in challenging urban scenarios. The experimental results demonstrate a reduction in tracking uncertainty and highlight the system's potential to serve as a more accurate and responsive safety mechanism for VRUs at intersections. This work contributes to the development of intelligent road infrastructures, laying the foundation for future advancements in urban traffic safety.

Indexed as

Kalman filterradarsensor fusiontraffic safetyUWBVulnerable Road User (VRU)

Identifiers

PMID41829651
PMCPMC12987293

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.