AIMC Topic: Accidents, Traffic

Clear Filters Showing 211 to 220 of 290 articles

Improve Aggressive Driver Recognition Using Collision Surrogate Measurement and Imbalanced Class Boosting.

International journal of environmental research and public health Mar 31, 2020
Real-time recognition of risky driving behavior and aggressive drivers is a promising research domain, thanks to powerful machine learning algorithms and the big data provided by in-vehicle and roadside sensors. However, since the occurrence of aggre...
Algorithms Female Male Humans Machine Learning Recognition, Psychology Aggression Risk-Taking Big Data Accidents, Traffic Automobile Driving
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A comparison between Artificial Neural Network and Hybrid Intelligent Genetic Algorithm in predicting the severity of fixed object crashes among elderly drivers.

Accident; analysis and prevention Feb 14, 2020
Run-off-road (ROR) crashes have always been a major concern as this type of crash is usually associated with a considerable number of serious injury and fatal crashes. A substantial portion of ROR fatalities occur in collisions with fixed objects at ...
Accidents, Traffic Female California Humans Wounds and Injuries Aged Male Neural Networks, Computer Algorithms Databases, Factual
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The importance of flow composition in real-time crash prediction.

Accident; analysis and prevention Jan 31, 2020
Previous real-time crash prediction models have scarcely used data disaggregated by vehicle type such as light, heavy and motorcycles. Thus, little effort has been made to quantify the impact of flow composition variables as crash precursors. We anal...
Accidents, Traffic Built Environment Motorcycles Support Vector Machine Chile Humans Logistic Models
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Predicting real-time traffic conflicts using deep learning.

Accident; analysis and prevention Jan 10, 2020
Recently, technologies for predicting traffic conflicts in real-time have been gaining momentum due to their proactive nature of application and the growing implementation of ADAS technology in intelligent vehicles. In ADAS, machine learning classifi...
Deep Learning Accidents, Traffic Safety Humans Algorithms Reproducibility of Results Data Collection
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Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis.

Accident; analysis and prevention Dec 20, 2019
Detecting traffic accidents as rapidly as possible is essential for traffic safety. In this study, we use eXtreme Gradient Boosting (XGBoost)-a Machine Learning (ML) technique-to detect the occurrence of accidents using a set of real time data compri...
Built Environment Humans Chicago Machine Learning Accidents, Traffic Models, Statistical Weather Spatial Analysis
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Highway crash detection and risk estimation using deep learning.

Accident; analysis and prevention Dec 13, 2019
Crash Detection is essential in providing timely information to traffic management centers and the public to reduce its adverse effects. Prediction of crash risk is vital for avoiding secondary crashes and safeguarding highway traffic. For many years...
Logistic Models Accidents, Traffic Data Collection Humans Risk Assessment Deep Learning
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Real-time crash risk prediction on arterials based on LSTM-CNN.

Accident; analysis and prevention Nov 26, 2019
Real-time crash risk prediction is expected to play a crucial role in preventing traffic accidents. However, most existing studies only focus on freeways rather than urban arterials. This paper proposes a real-time crash risk prediction model on arte...
Logistic Models Bayes Theorem Accidents, Traffic Humans Neural Networks, Computer
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Being watched over by a conversation robot may enhance safety in simulated driving.

Journal of safety research Nov 21, 2019
INTRODUCTION: In an aging society that is more and more information-oriented, being able to replace human passengers' protective effects on vehicle drivers with those of social robots is both essential and promising. However, the effects of a social ...
Adult Accidents, Traffic Middle Aged Humans Aged Communication Attention Age Factors Young Adult Female Automobile Driving Male Robotics
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Detecting motorcycle helmet use with deep learning.

Accident; analysis and prevention Nov 6, 2019
The continuous motorization of traffic has led to a sustained increase in the global number of road related fatalities and injuries. To counter this, governments are focusing on enforcing safe and law-abiding behavior in traffic. However, especially ...
Humans Adult Male Deep Learning Cities Accidents, Traffic Head Protective Devices Data Collection Motorcycles Myanmar
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Crash prediction based on traffic platoon characteristics using floating car trajectory data and the machine learning approach.

Accident; analysis and prevention Oct 4, 2019
Predicting crash propensity helps study safety on urban expressways in order to implement countermeasures and make improvements. It also helps identify and prevent crashes before they happen. However, collecting real-time wide-coverage traffic inform...
Automobiles Accidents, Traffic Built Environment China Logistic Models Humans Support Vector Machine Risk Assessment
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