AIMC Topic: Accidents, Traffic

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A remotely piloted aircraft system in major incident management: concept and pilot, feasibility study.

BMC emergency medicine
BACKGROUND: Major incidents are complex, dynamic and bewildering task environments characterised by simultaneous, rapidly changing events, uncertainty and ill-structured problems. Efficient management, communication, decision-making and allocation of...

Driver's behavioural changes with new intelligent transport system interventions at railway level crossings--A driving simulator study.

Accident; analysis and prevention
Improving safety at railway level crossings is an important issue for the Australian transport system. Governments, the rail industry and road organisations have tried a variety of countermeasures for many years to improve railway level crossing safe...

Application of time dependent probabilistic collision state checkers in highly dynamic environments.

PloS one
When computing the trajectory of an autonomous vehicle, inevitable collision states must be avoided at all costs, so no harm comes to the device or pedestrians around it. In dynamic environments, considering collisions as binary events is risky and i...

Predictive modeling in pediatric traumatic brain injury using machine learning.

BMC medical research methodology
BACKGROUND: Pediatric traumatic brain injury (TBI) constitutes a significant burden and diagnostic challenge in the emergency department (ED). While large North American research networks have derived clinical prediction rules for the head injured ch...

Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

International journal of injury control and safety promotion
Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of road traffic death rate will be helpful in its management. Based on this fact, we used an artificial...

Context-dependent effects of built environment factors on pedestrian-injury severities with imbalanced and high dimensional crash data.

Accident; analysis and prevention
Built environment is an important component that influences pedestrian injury severities in pedestrian-vehicle crashes. Previous studies indicated that the effects of various built environment factors on pedestrian injury severities are heterogeneous...

Ensuring SOTIF: Enhanced object detection techniques for autonomous driving.

Accident; analysis and prevention
Neural networks' insufficient interpretability can lead to unguaranteed Safety of the Intended Functionality (SOTIF) issues when perceptual results are not always met in autonomous driving applications. To address the safety shortcomings in the curre...

Artificial intelligence automated solution for hazard annotation and eye tracking in a simulated environment.

Accident; analysis and prevention
High-fidelity simulators and sensors are commonly used in research to create immersive environments for studying real-world problems. This setup records detailed data, generating large datasets. In driving research, a full-scale car model repurposed ...

Opposing-through crash risk forecasting using artificial intelligence-based video analytics for real-time application: integrating generalized extreme value theory and time series forecasting models.

Accident; analysis and prevention
Recent advancements in artificial intelligence (AI) and traffic sensing technologies provide significant opportunities for real-time crash risk forecasting. While forecasting based on historical crash data yields macroscopic insights into future cras...

Evaluating crash risk factors of farm equipment vehicles on county and non-county roads using interpretable tabular deep learning (TabNet).

Accident; analysis and prevention
Crashes involving farm equipment vehicles are a significant safety concern on public roads, particularly in rural and agricultural regions. These vehicles display unique challenges due to their slow-moving operational speed and interactions with fast...