Evidence map›Paper›PMID 34884154›Full record

ArticleSensors (Basel, Switzerland)2021

Experimental Validation of LiDAR Sensors Used in Vehicular Applications by Using a Mobile Platform for Distance and Speed Measurements.

Ionuț Vasile, Emil Tudor, Ion-Cătălin Sburlan, Marius-Alin Gheți, Gabriel Popa

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Feature Papers in Vehicular Sensing.Sensors (Basel, Switzerland) · 2023
    Article
  2. Review
  3. 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

5 authors.

Ionuț VasileNational Institute for Research and Development in Electrical Engineering, Department of Renewable Energy Sources and Energy Efficiency, 313 Splaiul Unirii, 030138 Bucharest, Romania.
Emil TudorNational Institute for Research and Development in Electrical Engineering, Department of Renewable Energy Sources and Energy Efficiency, 313 Splaiul Unirii, 030138 Bucharest, Romania.ORCID 0000-0001-7186-2124
Ion-Cătălin SburlanNational Institute for Research and Development in Electrical Engineering, Department of Renewable Energy Sources and Energy Efficiency, 313 Splaiul Unirii, 030138 Bucharest, Romania.
Marius-Alin GhețiDepartment of Railway Vehicles, University POLITEHNICA of Bucharest, 313 Splaiul Independenței, 060042 Bucharest, Romania.
Gabriel PopaDepartment of Railway Vehicles, University POLITEHNICA of Bucharest, 313 Splaiul Independenței, 060042 Bucharest, Romania.

Funding

This work was supported by a grant of the Romanian Ministry of Education and Research CCCDI - UEFISCDI Project PN-III-P2-2.1-PED-2019-1762, within PNCDI III
6 · The paper itself

Abstract

LiDAR sensors are needed for use in vehicular applications, particularly due to their good behavior in low-light environments, as they represent a possible solution for the safety systems of vehicles that have a long braking distance, such as trams. The testing of long-range LiDAR dynamic responses is very important for vehicle applications because of the presence of difficult operation conditions, such as different weather conditions or fake targets between the sensor and the tracked vehicle. The goal of the authors in this paper was to develop an experimental model for indoor testing, using a scaled vehicle that can measure the distances and the speeds relative to a fixed or a moving obstacle. This model, containing a LiDAR sensor, was developed to operate at variable speeds, at which the software functions were validated by repeated tests. Once the software procedures are validated, they can be applied on the full-scale model. The findings of this research include the validation of the frontal distance and relative speed measurement methodology, in addition to the validation of the independence of the measurements to the color of the obstacle and to the ambient light.

Indexed as

automated driving and autonomous vehiclescontrol strategiesdistance sensorLiDAR sensorrelative speed sensorsafety distancevehicle dynamics

Identifiers

PMID34884154
PMCPMC8662451

What OpenQuestion holds

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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.