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Automobiles

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Efficient mapping of crash risk at intersections with connected vehicle data and deep learning models.

Accident; analysis and prevention
Traditional methods for identifying crash-prone roadways are mainly based on historical crash data. It usually requires more than three years to collect a sufficient amount of dataset for road safety assessment. However, the emerging connected vehicl...

Application of Deep Learning Methods for Pedestrian Collision Detection Using Dashcam Videos.

Stapp car crash journal
The goal of this study is to clarify the usefulness of deep learning methods for pedestrian collision detection using dashcam videos for advanced automatic collision notification, focusing on pedestrians, as they make up the highest number of traffic...

Effect of pedestrian physique differences on head injury prediction in car-to-pedestrian accidents using deep learning.

Traffic injury prevention
OBJECTIVE: The aim of this study is to identify the effects of pedestrian physique differences on head injury prediction in car-to-pedestrian accidents via deep learning.

Investigating the safety and operational benefits of mixed traffic environments with different automated vehicle market penetration rates in the proximity of a driveway on an urban arterial.

Accident; analysis and prevention
Traffic congestion is monotonically increasing, especially in large cities, due to rapid urbanization. Traffic congestion not only deteriorates traffic operation and degrades traffic safety, but also imposes costs to the road users. The concerns asso...

An Explainable Machine Learning Approach Based on Statistical Indexes and SVM for Stress Detection in Automobile Drivers Using Electromyographic Signals.

Sensors (Basel, Switzerland)
The economic and personal consequences that a car accident generates for society have been increasing in recent years. One of the causes that can generate a car accident is the stress level the driver has; consequently, the detection of stress events...

Camera-LiDAR Multi-Level Sensor Fusion for Target Detection at the Network Edge.

Sensors (Basel, Switzerland)
There have been significant advances regarding target detection in the autonomous vehicle context. To develop more robust systems that can overcome weather hazards as well as sensor problems, the sensor fusion approach is taking the lead in this cont...

Trajectory Planner CDT-RRT* for Car-Like Mobile Robots toward Narrow and Cluttered Environments.

Sensors (Basel, Switzerland)
In order to achieve the safe and efficient navigation of mobile robots, it is essential to consider both the environmental geometry and kinodynamic constraints of robots. We propose a trajectory planner for car-like robots on the basis of the Dual-Tr...

Investigating yielding behavior of heterogeneous vehicles at a semi-controlled crosswalk.

Accident; analysis and prevention
It is well known that pedestrians are vulnerable road users. Their risk of being injured or killed in road traffic crashes is even higher as vehicle drivers often violate traffic rules and do not slow down or yield in front of crosswalks. In order to...

Can AI distinguish a bone radiograph from photos of flowers or cars? Evaluation of bone age deep learning model on inappropriate data inputs.

Skeletal radiology
OBJECTIVE: To evaluate the behavior of a publicly available deep convolutional neural network (DCNN) bone age algorithm when presented with inappropriate data inputs in both radiological and non-radiological domains.

Delicar: A Smart Deep Learning Based Self Driving Product Delivery Car in Perspective of Bangladesh.

Sensors (Basel, Switzerland)
The rapid expansion of a country's economy is highly dependent on timely product distribution, which is hampered by terrible traffic congestion. Additional staff are also required to follow the delivery vehicle while it transports documents or record...