AI Medical Compendium Journal:
Accident; analysis and prevention

Showing 131 to 137 of 137 articles

The utility of automated measures of ocular metrics for detecting driver drowsiness during extended wakefulness.

Accident; analysis and prevention
Slowed eyelid closure coupled with increased duration and frequency of closure is associated with drowsiness. This study assessed the utility of two devices for automated measurement of slow eyelid closure in a standard poor performance condition (al...

Support vector machine in crash prediction at the level of traffic analysis zones: Assessing the spatial proximity effects.

Accident; analysis and prevention
In zone-level crash prediction, accounting for spatial dependence has become an extensively studied topic. This study proposes Support Vector Machine (SVM) model to address complex, large and multi-dimensional spatial data in crash prediction. Correl...

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...

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...

Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach.

Accident; analysis and prevention
Although a growing body of literature focuses on the relationship between the built environment and pedestrian crashes, limited evidence is provided about the relative importance of many built environment attributes by accounting for their mutual int...