ReviewSensors (Basel, Switzerland)2019
A Comprehensive Survey of Driving Monitoring and Assistance Systems.
Review in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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.
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Who cites it
26 citing papers in PubMed.
- A Bio-Inspired Physiological-Behavioral Fusion Method for Human-Factor Risk Assessment of Imported Unmanned Intelligent System Operators in Port-Security Scenarios.Biomimetics (Basel, Switzerland) · 2026Article
- Article
- DUIncoder: Learning to Detect Driving Under the Influence Behaviors from Various Normal Driving Data.Sensors (Basel, Switzerland) · 2025Article
- Article
- Review
- Driver Fatigue Detection Using Heart Rate Variability Features from 2-Minute Electrocardiogram Signals While Accounting for Sex Differences.Sensors (Basel, Switzerland) · 2024Article
- Object Detection, Recognition, and Tracking Algorithms for ADASs-A Study on Recent Trends.Sensors (Basel, Switzerland) · 2023Review
- Driver Drowsiness Detection: A Machine Learning Approach on Skin Conductance.Sensors (Basel, Switzerland) · 2023Article
- Vehicle and Driver Monitoring System Using On-Board and Remote Sensors.Sensors (Basel, Switzerland) · 2023Article
- Correlation Analysis of In-Vehicle Sensors Data and Driver Signals in Identifying Driving and Driver Behaviors.Sensors (Basel, Switzerland) · 2022Article
- Risky-Driving-Image Recognition Based on Visual Attention Mechanism and Deep Learning.Sensors (Basel, Switzerland) · 2022Article
- Single Camera Face Position-Invariant Driver's Gaze Zone Classifier Based on Frame-Sequence Recognition Using 3D Convolutional Neural Networks.Sensors (Basel, Switzerland) · 2022Article
- How did COVID-19 impact driving behaviors and crash Severity? A multigroup structural equation modeling.Accident; analysis and prevention · 2022Article
- Urethane-Foam-Embedded Silicon Pressure Sensors including Stress-Concentration Packaging Structure for Driver Posture Monitoring.Sensors (Basel, Switzerland) · 2022Article
- In-Cabin Monitoring System for Autonomous Vehicles.Sensors (Basel, Switzerland) · 2022Article
- Threats Detection during Human-Computer Interaction in Driver Monitoring Systems.Sensors (Basel, Switzerland) · 2022Article
- Design of an Estimator Using the Artificial Neural Network Technique to Characterise the Braking of a Motor Vehicle.Sensors (Basel, Switzerland) · 2022Article
- Hybrid Interacting Multiple Model Filtering for Improving the Reliability of Radar-Based Forward Collision Warning Systems.Sensors (Basel, Switzerland) · 2022Article
- Evaluation of a Fatigue Detector Using Eye Closure-Associated Indicators Acquired from Truck Drivers in a Simulator Study.Sensors (Basel, Switzerland) · 2021Article
- Survey and Synthesis of State of the Art in Driver Monitoring.Sensors (Basel, Switzerland) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Improving a vehicle driver's performance decreases the damage caused by, and chances of, road accidents. In recent decades, engineers and researchers have proposed several strategies to model and improve driving monitoring and assistance systems (DMAS). This work presents a comprehensive survey of the literature related to driving processes, the main reasons for road accidents, the methods of their early detection, and state-of-the-art strategies developed to assist drivers for a safe and comfortable driving experience. The studies focused on the three main elements of the driving process, viz. driver, vehicle, and driving environment are analytically reviewed in this work, and a comprehensive framework of DMAS, major research areas, and their interaction is explored. A well-designed DMAS improves the driving experience by continuously monitoring the critical parameters associated with the driver, vehicle, and surroundings by acquiring and processing the data obtained from multiple sensors. A discussion on the challenges associated with the current and future DMAS and their potential solutions is also presented.
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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.