AIMC Topic: Accidents, Traffic
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Identification of the best machine learning model for the prediction of driver injury severity.
International journal of injury control and safety promotion
Apr 4, 2024
Predicting the injury severities sustained by drivers engaged in road traffic accidents is a key topic of research in road traffic safety. The current study analyzed the driver injury severity (DIS) using twelve machine learning (ML) algorithms. Thes...
Machine-Learning-Accelerated Simulations for the Design of Airbag Constrained by Obstacles at Rest.
Stapp car crash journal
Mar 3, 2024
Predicting airbag deployment geometries is an important task for airbag and vehicle designers to meet safety standards based on biomechanical injury risk functions. This prediction is also an extraordinarily complex problem given the number of discip...
Perceptions of vulnerable roadway users on autonomous vehicle regulations.
Journal of safety research
Feb 23, 2024
INTRODUCTION: Development and implementation of autonomous vehicle (AV) related regulations are necessary to ensure safe AV deployment and wide acceptance among all roadway users. Assessment of vulnerable roadway users' perceptions on AV regulations ...
A spatiotemporal deep learning approach for pedestrian crash risk prediction based on POI trip characteristics and pedestrian exposure intensity.
Accident; analysis and prevention
Feb 8, 2024
Pedestrians represent a population of vulnerable road users who are directly exposed to complex traffic conditions, thereby increasing their risk of injury or fatality. This study first constructed a multidimensional indicator to quantify pedestrian ...
Lane-change intention recognition considering oncoming traffic: Novel insights revealed by advances in deep learning.
Accident; analysis and prevention
Feb 6, 2024
Lane-changing (LC) intention recognition models have seen limited real-world application due to a lack of research on two-lane two-way road environments. This study constructs a high-fidelity simulated two-lane two-way road to develop a Transformer m...
Forward dynamics computational modelling of a cyclist fall with the inclusion of protective response using deep learning-based human pose estimation.
Journal of biomechanics
Jan 19, 2024
Single bicycle crashes, i.e., falls and impacts not involving a collision with another road user, are a significantly underestimated road safety problem. The motions and behaviours of falling people, or fall kinematics, are often investigated in the ...
Investigating mental workload caused by NDRTs in highly automated driving with deep learning.
Traffic injury prevention
Jan 19, 2024
OBJECTIVE: This study aimed to examine the impact of non-driving-related tasks (NDRTs) on drivers in highly automated driving scenarios and sought to develop a deep learning model for classifying mental workload using electroencephalography (EEG) sig...
Predicting pedestrian-involved crash severity using inception-v3 deep learning model.
Accident; analysis and prevention
Jan 13, 2024
This research leverages a novel deep learning model, Inception-v3, to predict pedestrian crash severity using data collected over five years (2016-2021) from Louisiana. The final dataset incorporates forty different variables related to pedestrian at...
Can we trust our eyes? Interpreting the misperception of road safety from street view images and deep learning.
Accident; analysis and prevention
Jan 12, 2024
Road safety is a critical concern that impacts both human lives and urban development, drawing significant attention from city managers and researchers. The perception of road safety has gained increasing research interest due to its close connection...
Advancing proactive crash prediction: A discretized duration approach for predicting crashes and severity.
Accident; analysis and prevention
Dec 5, 2023
Driven by advancements in data-driven methods, recent developments in proactive crash prediction models have primarily focused on implementing machine learning and artificial intelligence. However, from a causal perspective, statistical models are pr...
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