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Machine Learning Techniques to Identify Unsafe Driving Behavior by Means of In-Vehicle Sensor Data
8 references·0 citing·37 second hop
Machine Learning Techniques to Identify Unsafe Driving Behavior by Means of In-Vehicle Sensor Data (2021)Machine Learning Techniques to Identify U…Driver behavior detection and classification using deep convolutional neural networks (2020)Driver behavior detection and…Driving Behavior Analysis through CAN Bus Data in an Uncontrolled Environment (2018)Driving Behavior Analysis thr…A hierarchical machine learning classification approach for secondary task identification from observed driving behavior data (2018)A hierarchical machine learni…Driver identification using automobile sensor data from a single turn (2016)Driver identification using a…Modeling of Driver Behavior in Real World Scenarios Using Multiple Noninvasive Sensors (2013)Modeling of Driver Behavior i…CarSafe (2012)CarSafeCamera-based drowsiness reference for driver state classification under real driving conditions (2010)Camera-based drowsiness refer…On more robust estimation of skewness and kurtosis (2004)On more robust estimation of …Effects of visual and cognitive load in real and simulated motorway driving (2005)Real-Time System for Monitoring Driver Vigilance (2006)Driver Inattention Monitoring System for Intelligent Vehicles: A Review (2011)Detecting Drivers' Mirror-Checking Actions and Its Application to Maneuver and Secondary Task Recognition (2015)How does a collision warning system shape driver's brake response time? The influence of expectancy and automation complacency on real-life emergency braking (2015)Deep unsupervised multi-modal fusion network for detecting driver distraction (2020)Subjective and Objective Sleepiness in the Active Individual (1990)Sleepiness, Driving, and Motor Vehicle Crashes (1998)Vehicle accidents related to sleep: a review. (1999)Fusion of Optimized Indicators from Advanced Driver Assistance Systems (ADAS) for Driver Drowsiness Detection (2014)Driver Distraction Using Visual-Based Sensors and Algorithms (2016)Multimodal Features for Detection of Driver Stress and Fatigue: Review (2020)Predicting driver drowsiness using vehicle measures: Recent insights and future challenges (2009)Designing Gamified Applications that Make Safe Driving More Engaging (2017)Deep Learning-Based Drivers Emotion Classification System in Time Series Data for Remote Applications (2020)A Review of Driving Style Recognition Methods From Short-Term and Long-Term Perspectives (2023)Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options (1996)Autoregressive Conditional Skewness (1999)Conditional Skewness in Asset Pricing Tests (2000)Modelling Nonlinear Economic Time Series (2010)Market Skewness Risk and the Cross Section of Stock Returns (2013)Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework (2017)A drowsy driver detection system for heavy vehicles (2002)Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification (2007)Driver classification and driving style recognition using inertial sensors (2013)Large-scale Driver Identification Using Automobile Driving Data (2019)Understanding Individualization Driving States via Latent Dirichlet Allocation Model (2019)A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms (2015)Carer-employees’ travel behaviour: Assisted-transport in time and space (2019)Effect of cellular telephone conversations and other potential interference on reaction time in a braking response (2003)Driver's exposure to distractions in their natural driving environment (2005)The effects of text messaging on young novice driver performance (2005)Proceedings of the International Joint Conference on Neural Networks, 2003. (2003)Proceedings of the Human Factors and Ergonomics Society 2019 Annual Meeting (2019)HCF: A Hybrid CNN Framework for Behavior Detection of Distracted Drivers (2020)A review of driver fatigue detection and its advances on the use of RGB-D camera and deep learning (2022)Automatic driver distraction detection using deep convolutional neural networks (2022)
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References

  • 2004On more robust estimation of skewness and kurtosis523 cited
  • 2020Driver behavior detection and classification using deep convolutional neural networks355 cited
  • 2018Driving Behavior Analysis through CAN Bus Data in an Uncontrolled Environment186 cited
  • 2010Camera-based drowsiness reference for driver state classification under real driving conditions139 cited
  • 2016Driver identification using automobile sensor data from a single turn126 cited
  • 2013Modeling of Driver Behavior in Real World Scenarios Using Multiple Noninvasive Sensors88 cited
  • 2012CarSafe81 cited
  • 2018A hierarchical machine learning classification approach for secondary task identification from observed driving behavior data76 cited

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