AIMC Topic: Automobile Driving

Clear Filters Showing 131 to 140 of 249 articles

Vision-Based Driver's Cognitive Load Classification Considering Eye Movement Using Machine Learning and Deep Learning.

Sensors (Basel, Switzerland) Nov 30, 2021
Due to the advancement of science and technology, modern cars are highly technical, more activity occurs inside the car and driving is faster; however, statistics show that the number of road fatalities have increased in recent years because of drive...
Accidents, Traffic Automobile Driving Cognition Machine Learning Humans Eye Movements Deep Learning
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Vehicle Trajectory Estimation Based on Fusion of Visual Motion Features and Deep Learning.

Sensors (Basel, Switzerland) Nov 29, 2021
Driver situation awareness is critical for safety. In this paper, we propose a fast, accurate method for obtaining real-time situation awareness using a single type of sensor: monocular cameras. The system tracks the host vehicle's trajectory using s...
Automobile Driving Motion Neural Networks, Computer Deep Learning Algorithms
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An Intelligent Multimode Clustering Mechanism Using Driving Pattern Recognition in Cognitive Internet of Vehicles.

Sensors (Basel, Switzerland) Nov 15, 2021
Connected autonomous vehicles can leverage communication and artificial intelligence technologies to effectively overcome the perceived limitations of individuals and enhance driving safety and stability. However, due to the high dynamics of the vehi...
Humans Cluster Analysis Internet Cognition Artificial Intelligence Automobile Driving
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A Review of Deep Learning-Based Methods for Pedestrian Trajectory Prediction.

Sensors (Basel, Switzerland) Nov 13, 2021
Pedestrian trajectory prediction is one of the main concerns of computer vision problems in the automotive industry, especially in the field of advanced driver assistance systems. The ability to anticipate the next movements of pedestrians on the str...
Automobile Driving Signal Processing, Computer-Assisted Deep Learning Accidents, Traffic Humans Technology Pedestrians
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A Hybrid Deep Learning Model for Recognizing Actions of Distracted Drivers.

Sensors (Basel, Switzerland) Nov 8, 2021
With the rapid spreading of in-vehicle information systems such as smartphones, navigation systems, and radios, the number of traffic accidents caused by driver distractions shows an increasing trend. Timely identification and warning are deemed to b...
Humans Neural Networks, Computer Automobile Driving Distracted Driving Accidents, Traffic Deep Learning
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Feasibility of a Neural Network-Based Virtual Sensor for Vehicle Unsprung Mass Relative Velocity Estimation.

Sensors (Basel, Switzerland) Oct 27, 2021
With the automotive industry moving towards automated driving, sensing is increasingly important in enabling technology. The virtual sensors allow data fusion from various vehicle sensors and provide a prediction for measurement that is hard or too e...
Automobile Driving Feasibility Studies Neural Networks, Computer Bayes Theorem
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LiDAR-driven spiking neural network for collision avoidance in autonomous driving.

Bioinspiration & biomimetics Oct 25, 2021
Facilitated by advances in real-time sensing, low and high-level control, and machine learning, autonomous vehicles draw ever-increasing attention from many branches of knowledge. Neuromorphic (brain-inspired) implementation of robotic control has be...
Machine Learning Automobile Driving Neural Networks, Computer Autonomous Vehicles Robotics
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Deep Q-network-based traffic signal control models.

PloS one Sep 2, 2021
Traffic congestion has become common in urban areas worldwide. To solve this problem, the method of searching a solution using artificial intelligence has recently attracted widespread attention because it can solve complex problems such as traffic s...
Automobile Driving Motor Vehicles Neural Networks, Computer Humans Computer Simulation
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Modeling learner-controlled mental model learning processes by a second-order adaptive network model.

PloS one Aug 24, 2021
Learning knowledge or skills usually is considered to be based on the formation of an adequate internal mental model as a specific type of mental network. The learning process for such a mental model conceptualised as a mental network, is a form of (...
Learning Models, Statistical Neural Networks, Computer Adaptation, Physiological Models, Psychological Automobile Driving Humans
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Vehicle Trajectory Prediction Using Hierarchical Graph Neural Network for Considering Interaction among Multimodal Maneuvers.

Sensors (Basel, Switzerland) Aug 9, 2021
Predicting the trajectories of surrounding vehicles by considering their interactions is an essential ability for the functioning of autonomous vehicles. The subsequent movement of a vehicle is decided based on the multiple maneuvers of surrounding v...
Automobile Driving Neural Networks, Computer
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