AIMC Topic: Accidents, Traffic

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Anomaly Detection in Traffic Surveillance Videos Using Deep Learning.

Sensors (Basel, Switzerland) Aug 31, 2022
In the recent past, a huge number of cameras have been placed in a variety of public and private areas for the purposes of surveillance, the monitoring of abnormal human actions, and traffic surveillance. The detection and recognition of abnormal act...
Accidents, Traffic Algorithms Neural Networks, Computer Cities Deep Learning Humans
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Accident Liability Determination of Autonomous Driving Systems Based on Artificial Intelligence Technology and Its Impact on Public Mental Health.

Journal of environmental and public health Aug 31, 2022
With the rise of self-driving technology research, the establishment of a scientific and perfect legal restraint and supervision system for self-driving vehicles has been gradually paid attention to. The determination of tort liability subject of tra...
Accidents, Traffic Automobile Driving Technology Mental Health Artificial Intelligence
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Comparison of Eye and Face Features on Drowsiness Analysis.

Sensors (Basel, Switzerland) Aug 30, 2022
Drowsiness is one of the leading causes of traffic accidents. For those who operate large machinery or motor vehicles, incidents due to lack of sleep can cause property damage and sometimes lead to grave consequences of injuries and fatality. This st...
Sleep Cluster Analysis Attention Accidents, Traffic Humans Neural Networks, Computer
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A data-centric weak supervised learning for highway traffic incident detection.

Accident; analysis and prevention Aug 19, 2022
Using the data from loop detector sensors for near-real-time detection of traffic incidents on highways is crucial to averting major traffic congestion. While recent supervised machine learning methods offer solutions to incident detection by leverag...
Humans Support Vector Machine Supervised Machine Learning Data Collection Accidents, Traffic
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A Bayesian deep learning method for freeway incident detection with uncertainty quantification.

Accident; analysis and prevention Aug 16, 2022
Incident detection is fundamental for freeway management to reduce non-recurrent congestions and secondary incidents. Recently, machine learning technologies have made considerable progress in the incident detection field, but many still face challen...
Uncertainty Accidents, Traffic Neural Networks, Computer Humans Deep Learning Bayes Theorem
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Analysis on Risk Characteristics of Traffic Accidents in Small-Spacing Expressway Interchange.

International journal of environmental research and public health Aug 12, 2022
Many small-spacing interchanges (SSI) appear when the density of the expressway interchanges increases. However, the characteristics of traffic accidents in SSI have not been explained clearly. Therefore, this paper systematically takes the G3001 exp...
Risk Factors Logistic Models Accidents, Traffic Support Vector Machine
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Risky-Driving-Image Recognition Based on Visual Attention Mechanism and Deep Learning.

Sensors (Basel, Switzerland) Aug 5, 2022
Risky driving behavior seriously affects the driver's ability to react, execute and judge, which is one of the major causes of traffic accidents. The timely and accurate identification of the driving status of drivers is particularly important, since...
Deep Learning Automobile Driving Recognition, Psychology Data Collection Accidents, Traffic
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Vehicle Safety-Assisted Driving Technology Based on Computer Artificial Intelligence Environment.

Computational intelligence and neuroscience Jun 18, 2022
In this paper, we propose an assisted driving system implemented with a Jetson nano-high-performance embedded platform by using machine vision and deep learning technologies. The vehicle dynamics model is established under multiconditional assumption...
Technology Accidents, Traffic Computers Artificial Intelligence Automobile Driving
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Research on Vehicle Lane Change Warning Method Based on Deep Learning Image Processing.

Sensors (Basel, Switzerland) Apr 26, 2022
In order to improve vehicle driving safety in a low-cost manner, we used a monocular camera to study a lane-changing warning algorithm for highway vehicles based on deep learning image processing technology. We improved the mask region-based convolut...
Accidents, Traffic Automobile Driving Image Processing, Computer-Assisted Algorithms Humans Deep Learning
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A hybrid deep learning approach for driver anomalous lane changing identification.

Accident; analysis and prevention Apr 21, 2022
Reliable knowledge of driving states is of great importance to ensure road safety. Anomaly detection in driving behavior means recognizing anomalous driving states as a direct result of either environmental or psychological factors. This paper provid...
Humans Deep Learning Automobile Driving Algorithms Accidents, Traffic
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