Evidence map›Paper›PMID 39599059›Full record

ArticleSensors (Basel, Switzerland)2024

Highway Safety with an Intelligent Headlight System for Improved Nighttime Driving.

Jacob Kwaku Nkrumah, Yingfeng Cai, Ammar Jafaripournimchahi, Hai Wang, Vincent Akolbire Atindana

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. 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

5 authors.

Jacob Kwaku NkrumahAutomotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0001-8489-7350
Yingfeng CaiAutomotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China.
Ammar JafaripournimchahiAutomotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0002-9401-861X
Hai WangSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0002-9136-8091
Vincent Akolbire AtindanaAutomotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0001-8778-7181

Funding

Key Project for the Development of Strategic Emerging Industries of Jiangsu Province BE2020083-3, BE2020083-2National Key Research and Development Program of China 2022YFB2503302National Natural Science Foundation of China 52225212, U20A20333, U20A20331, 52072160, 52272418
6 · The paper itself

Abstract

Automotive headlights are crucial for nighttime driving, but accidents frequently occur when drivers fail to dim their high beams in the presence of oncoming vehicles, causing temporary blindness and increasing the risk of collisions. To address this problem, the current study developed an intelligent headlight system using a sensor-based approach to control headlight beam intensity. This system is designed to distinguish between various light sources, including streetlights, building lights, and moving vehicle lights. The primary goal of the study was to create an affordable alternative to machine-learning-based intelligent headlight systems, which are limited to high-end vehicles due to the high cost of their components. In simulations, the proposed system achieved a 98% success rate, showing enhanced responsiveness, particularly when detecting an approaching vehicle at 90°. The system's effectiveness was further validated through real-vehicle implementation, confirming the feasibility of the approach. By automating headlight control, the system reduces driver fatigue, enhances safety, and minimizes nighttime highway accidents, contributing to a safer driving environment.

Indexed as

accident preventionhigh beamshighway safetyintelligent headlightmachine-learning-based technologysensor-based technology

Identifiers

PMID39599059
PMCPMC11598802

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.