AI Medical Compendium Journal:
Accident; analysis and prevention

Showing 111 to 120 of 137 articles

Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements.

Accident; analysis and prevention
Proactive traffic safety management systems can monitor traffic conditions in real-time, identify the formation of unsafe traffic dynamics, and implement suitable interventions to bring unsafe conditions back to normal traffic situations. Recent adva...

A hierarchical machine learning classification approach for secondary task identification from observed driving behavior data.

Accident; analysis and prevention
According to NHTSA, more than 3477 people (including 551 non-occupants) were killed and 391,000 were injured due to distraction-related crashes in 2015. The distracted driving epidemic has long been under research to identify its impact on driving be...

A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data.

Accident; analysis and prevention
The primary objective of this study is to investigate how the deep learning approach contributes to citywide short-term crash risk prediction by leveraging multi-source datasets. This study uses data collected from Manhattan in New York City to illus...

Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness.

Accident; analysis and prevention
Monitoring car drivers for drowsiness is crucial but challenging. The high inter-individual variability observed in measurements raises questions about the accuracy of the drowsiness detection process. In this study, we sought to enhance the performa...

Factors influencing unsafe behaviors: A supervised learning approach.

Accident; analysis and prevention
Despite its potential, the use of machine learning in safety studies had been limited. Considering machine learning's advantage in predictive accuracy, this study used a supervised learning approach to evaluate the relative importance of different co...

Psychosocial factors associated with intended use of automated vehicles: A simulated driving study.

Accident; analysis and prevention
This study applied the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) to assess drivers' intended use of automated vehicles (AVs) after undertaking a simulated driving task. In addition, this study explored the potential f...

Market penetration of intersection AEB: Characterizing avoided and residual straight crossing path accidents.

Accident; analysis and prevention
Car occupants account for one third of all junction fatalities in the European Union. Driver warning can reduce intersection accidents by up to 50 percent; adding Autonomous Emergency Braking (AEB) delivers a reduction of up to 70 percent. However, t...

A trial of retrofitted advisory collision avoidance technology in government fleet vehicles.

Accident; analysis and prevention
In-vehicle collision avoidance technology (CAT) has the potential to prevent crash involvement. In 2015, Transport for New South Wales undertook a trial of a Mobileye 560 CAT system that was installed in 34 government fleet vehicles for a period of s...

Modeling when and where a secondary accident occurs.

Accident; analysis and prevention
The occurrence of secondary accidents leads to traffic congestion and road safety issues. Secondary accident prevention has become a major consideration in traffic incident management. This paper investigates the location and time of a potential seco...

Identification of significant factors in fatal-injury highway crashes using genetic algorithm and neural network.

Accident; analysis and prevention
Identification of the significant factors of traffic crashes has been a primary concern of the transportation safety research community for many years. A fatal-injury crash is a comprehensive result influenced by multiple variables involved at the mo...