AIMC Topic: Accidents, Traffic

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The use of machine learning improves the assessment of drug-induced driving behaviour.

Accident; analysis and prevention Oct 27, 2020
RATIONALE: Car-driving performance is negatively affected by the intake of alcohol, tranquillizers, sedatives and sleep deprivation. Although several studies have shown that the standard deviation of the lateral position on the road (SDLP) is sensiti...
Female Young Adult Adult Machine Learning Computer Simulation Driving Under the Influence Male Accidents, Traffic Psychomotor Performance Humans
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Traffic Crash Severity Prediction-A Synergy by Hybrid Principal Component Analysis and Machine Learning Models.

International journal of environmental research and public health Oct 19, 2020
The accurate prediction of road traffic crash (RTC) severity contributes to generating crucial information, which can be used to adopt appropriate measures to reduce the aftermath of crashes. This study aims to develop a hybrid system using principal...
Humans Neural Networks, Computer Accidents, Traffic Male Machine Learning Support Vector Machine Principal Component Analysis Female
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Prediction of pedestrian-vehicle conflicts at signalized intersections based on long short-term memory neural network.

Accident; analysis and prevention Oct 17, 2020
Pedestrian protection is an important component of road safety. Intersections are dangerous locations for pedestrians with mixed traffic. This paper aims to predict potential traffic conflicts between pedestrians and vehicles at signalized intersecti...
Pattern Recognition, Automated Built Environment Pedestrians Accidents, Traffic Safety Humans Neural Networks, Computer
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Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network.

International journal of environmental research and public health Oct 14, 2020
A better understanding of circumstances contributing to the severity outcome of traffic crashes is an important goal of road safety studies. An in-depth crash injury severity analysis is vital for the proactive implementation of appropriate mitigatio...
Humans Neural Networks, Computer Algorithms Logistic Models Accidents, Traffic Wounds and Injuries Risk Factors Severity of Illness Index Saudi Arabia
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Review on big data applications in safety research of intelligent transportation systems and connected/automated vehicles.

Accident; analysis and prevention Sep 4, 2020
The era of Big Data has arrived. Recently, under the environment of intelligent transportation systems (ITS) and connected/automated vehicles (CAV), Big Data has been applied in various fields in transportation including traffic safety. In this study...
Accidents, Traffic Safety Automobile Driving Automation Transportation Artificial Intelligence Research Design Big Data Humans
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Predicting Crash Injury Severity with Machine Learning Algorithm Synergized with Clustering Technique: A Promising Protocol.

International journal of environmental research and public health Jul 30, 2020
Predicting crash injury severity is a crucial constituent of reducing the consequences of traffic crashes. This study developed machine learning (ML) models to predict crash injury severity using 15 crash-related parameters. Separate ML models for ea...
United Kingdom Algorithms Humans Wounds and Injuries Cluster Analysis Accidents, Traffic Machine Learning
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An integrated architecture for intelligence evaluation of automated vehicles.

Accident; analysis and prevention Jul 24, 2020
Increasing automation calls for evaluating the effectiveness and intelligence of automated vehicles. This paper proposes a framework for quantitatively evaluating the intelligence of automated vehicles. Firstly, we establish the evaluation environmen...
Automation Humans Artificial Intelligence Accidents, Traffic Algorithms Automobile Driving
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Machine-learning approach to predict on-road driving ability in healthy older people.

Psychiatry and clinical neurosciences Jul 20, 2020
AIM: In Japan, fatal traffic accidents due to older drivers are on the rise. Considering that approximately half the older drivers who have caused fatal accidents are cognitively normal healthy people, it has been required to detect older drivers who...
Neuropsychological Tests Aging Support Vector Machine Aged Accidents, Traffic Aged, 80 and over Japan Humans Male Automobile Driving Female Psychomotor Performance
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Adopting Machine Learning and Spatial Analysis Techniques for Driver Risk Assessment: Insights from a Case Study.

International journal of environmental research and public health Jul 18, 2020
Traffic violations usually caused by aggressive driving behavior are often seen as a primary contributor to traffic crashes. Violations are either caused by an unintentional or deliberate act of drivers that jeopardize the lives of fellow drivers, pe...
Spatial Analysis Humans Machine Learning Pedestrians Risk Assessment Accidents, Traffic Geographic Information Systems Automobile Driving China
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Efficient mapping of crash risk at intersections with connected vehicle data and deep learning models.

Accident; analysis and prevention Jul 16, 2020
Traditional methods for identifying crash-prone roadways are mainly based on historical crash data. It usually requires more than three years to collect a sufficient amount of dataset for road safety assessment. However, the emerging connected vehicl...
Deep Learning Automobiles Accidents, Traffic Data Collection Risk Michigan Neural Networks, Computer Technology Reproducibility of Results Humans
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