AIMC Topic: Accidents, Traffic

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Improving traffic accident severity prediction using MobileNet transfer learning model and SHAP XAI technique.

PloS one Apr 9, 2024
Traffic accidents remain a leading cause of fatalities, injuries, and significant disruptions on highways. Comprehending the contributing factors to these occurrences is paramount in enhancing safety on road networks. Recent studies have demonstrated...
Neural Networks, Computer Machine Learning Accidents, Traffic
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Real-time crash prediction on express managed lanes of Interstate highway with anomaly detection learning.

Accident; analysis and prevention Apr 5, 2024
To facilitate efficient transportation, I-4 Express is constructed separately from general use lanes in metropolitan area to improve mobility and reduce congestion. As this new infrastructure would undoubtedly change the traffic network, there is a n...
Area Under Curve Accidents, Traffic Neural Networks, Computer Automobile Driving Machine Learning Humans Environment Design
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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...
Young Adult Adult Humans Male Machine Learning Algorithms Accidents, Traffic Automobile Driving Middle Aged Female Wounds and Injuries India
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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...
Humans Machine Learning Equipment Design Accidents, Traffic Finite Element Analysis Computer Simulation Models, Theoretical Air Bags
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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 ...
Pedestrians Adult Aged Surveys and Questionnaires Male Humans Young Adult Accidents, Traffic Adolescent Female Safety Automobiles Perception Middle Aged Bicycling Walking
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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 ...
Built Environment Wounds and Injuries Deep Learning Pedestrians Accidents, Traffic Humans Risk Factors
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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...
Automobile Driving Accidents, Traffic Intention Algorithms Deep Learning Humans
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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 ...
Bicycling Deep Learning Accidents, Traffic Humans Motion Computer Simulation
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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...
Humans Electroencephalography Workload Deep Learning Task Performance and Analysis Accidents, Traffic Automobile Driving
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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...
Deep Learning Models, Statistical Accidents, Traffic Wounds and Injuries Pedestrians Humans Algorithms
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