ReviewSensors (Basel, Switzerland)2020
The Perception System of Intelligent Ground Vehicles in All Weather Conditions: A Systematic Literature Review.
Review in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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.
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.
Who cites it
17 citing papers in PubMed.
- Structural, spectroscopic, thermal and biological insights into a new cadmium halide-based organic-inorganic hybrid material.RSC advances · 2026Article
- Enhancing Perception Through Context-Adaptive Visible and SWIR Image Fusion in Harsh Environments.Sensors (Basel, Switzerland) · 2026Article
- Research Progress of Electrically Conductive Asphalt Concrete Deicing and Snowmelt Technology: Material Development and Application Progress.Sensors (Basel, Switzerland) · 2026Review
- Study on real-time warning system of blind path for the visually impaired based on improved deep residual shrinkage network.Scientific reports · 2025Article
- Effects of Dust and Moisture Surface Contaminants on Automotive Radar Sensor Frequencies.Sensors (Basel, Switzerland) · 2025Article
- A Comparative Review of the SWEET Simulator: Theoretical Verification Against Other Simulators.Journal of imaging · 2024Article
- Ego-Vehicle Speed Correction for Automotive Radar Systems Using Convolutional Neural Networks.Sensors (Basel, Switzerland) · 2024Article
- Responsiveness and Precision of Digital IMUs under Linear and Curvilinear Motion Conditions for Local Navigation and Positioning in Advanced Smart Mobility.Micromachines · 2024Article
- A Survey on Data Compression Techniques for Automotive LiDAR Point Clouds.Sensors (Basel, Switzerland) · 2024Review
- Vision System for a Forestry Navigation Machine.Sensors (Basel, Switzerland) · 2024Article
- Object Detection in Adverse Weather for Autonomous Driving through Data Merging and YOLOv8.Sensors (Basel, Switzerland) · 2023Article
- Towards Deep Radar Perception for Autonomous Driving: Datasets, Methods, and Challenges.Sensors (Basel, Switzerland) · 2022Review
- Preferred Sources of Information, Knowledge, and Acceptance of Automated Vehicle Systems: Effects of Gender and Age.Frontiers in psychology · 2022Article
- Real-Time LIDAR-Based Urban Road and Sidewalk Detection for Autonomous Vehicles.Sensors (Basel, Switzerland) · 2021Article
- Multisensory Testing Framework for Advanced Driver Assistant Systems Supported by High-Quality 3D Simulation.Sensors (Basel, Switzerland) · 2021Article
- Sensors and Sensor's Fusion in Autonomous Vehicles.Sensors (Basel, Switzerland) · 2021Article
- Robust Target Detection and Tracking Algorithm Based on Roadside Radar and Camera.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Perception is a vital part of driving. Every year, the loss in visibility due to snow, fog, and rain causes serious accidents worldwide. Therefore, it is important to be aware of the impact of weather conditions on perception performance while driving on highways and urban traffic in all weather conditions. The goal of this paper is to provide a survey of sensing technologies used to detect the surrounding environment and obstacles during driving maneuvers in different weather conditions. Firstly, some important historical milestones are presented. Secondly, the state-of-the-art automated driving applications (adaptive cruise control, pedestrian collision avoidance, etc.) are introduced with a focus on all-weather activity. Thirdly, the most involved sensor technologies (radar, lidar, ultrasonic, camera, and far-infrared) employed by automated driving applications are studied. Furthermore, the difference between the current and expected states of performance is determined by the use of spider charts. As a result, a fusion perspective is proposed that can fill gaps and increase the robustness of the perception system.
Indexed as
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What OpenQuestion holds
Registered trials
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.