AIMC Topic: Automobile Driving

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The Modeling of Super Deep Learning Aiming at Knowledge Acquisition in Automatic Driving.

Computational intelligence and neuroscience Apr 9, 2022
In this paper, we proposed a new theory of solving the multitarget control problem by introducing a machine learning framework in automatic driving and implementing the acquisition of excellent drivers' knowledge. Nowadays, there still exist some cor...
Automobile Driving Machine Learning Deep Learning Accidents, Traffic
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DGInet: Dynamic graph and interaction-aware convolutional network for vehicle trajectory prediction.

Neural networks : the official journal of the International Neural Network Society Apr 4, 2022
This paper investigates vehicle trajectory prediction problems in real traffic scenarios by fully harnessing the spatio-temporal dependencies between multiple vehicles. The existing GCN-based trajectory predictions are often considered in a single tr...
Automobile Driving Neural Networks, Computer
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A Survey of End-to-End Driving: Architectures and Training Methods.

IEEE transactions on neural networks and learning systems Apr 4, 2022
Autonomous driving is of great interest to industry and academia alike. The use of machine learning approaches for autonomous driving has long been studied, but mostly in the context of perception. In this article, we take a deeper look on the so-cal...
Surveys and Questionnaires Automobile Driving Machine Learning Neural Networks, Computer
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Farm Vehicle Following Distance Estimation Using Deep Learning and Monocular Camera Images.

Sensors (Basel, Switzerland) Apr 2, 2022
This paper presents a comprehensive solution for distance estimation of the following vehicle solely based on visual data from a low-resolution monocular camera. To this end, a pair of vehicles were instrumented with real-time kinematic (RTK) GPS, an...
Automobile Driving Deep Learning Motor Vehicles Farms Accidents, Traffic
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Daily motionless activities: A dataset with accelerometer, magnetometer, gyroscope, environment, and GPS data.

Scientific data Mar 25, 2022
The dataset presented in this paper presents a dataset related to three motionless activities, including driving, watching TV, and sleeping. During these activities, the mobile device may be positioned in different locations, including the pants pock...
Humans Portugal Activities of Daily Living Accelerometry Machine Learning Movement Automobile Driving
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Multimodal driver state modeling through unsupervised learning.

Accident; analysis and prevention Mar 24, 2022
Naturalistic driving data (NDD) can help understand drivers' reactions to each driving scenario and provide personalized context to driving behavior. However, NDD requires a high amount of manual labor to label certain driver's state and behavioral p...
Heart Rate Automobile Driving Accidents, Traffic Unsupervised Machine Learning Bayes Theorem Humans
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Discriminative Transfer Learning for Driving Pattern Recognition in Unlabeled Scenes.

IEEE transactions on cybernetics Mar 11, 2022
Driving pattern recognition based on features, such as GPS, gear, and speed information, is essential to develop intelligent transportation systems. However, it is usually expensive and labor intensive to collect a large amount of labeled driving dat...
Machine Learning Algorithms Humans Pattern Recognition, Automated Automobile Driving
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A Hybrid Model for Driver Emotion Detection Using Feature Fusion Approach.

International journal of environmental research and public health Mar 6, 2022
Machine and deep learning techniques are two branches of artificial intelligence that have proven very efficient in solving advanced human problems. The automotive industry is currently using this technology to support drivers with advanced driver as...
Accidents, Traffic Automobile Driving Emotions Neural Networks, Computer Machine Learning Artificial Intelligence Humans
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Deep-Learning-Based Parking Area and Collision Risk Area Detection Using AVM in Autonomous Parking Situation.

Sensors (Basel, Switzerland) Mar 3, 2022
In this paper, I propose a bird eye view image detection method for parking areas and collision risk areas at the same time in parking situations. Deep learning algorithms using area detection and semantic segmentation were used. The main architectur...
Automobile Driving Deep Learning Humans Algorithms Neural Networks, Computer
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E2DR: A Deep Learning Ensemble-Based Driver Distraction Detection with Recommendations Model.

Sensors (Basel, Switzerland) Feb 26, 2022
The increasing number of car accidents is a significant issue in current transportation systems. According to the World Health Organization (WHO), road accidents are the eighth highest top cause of death around the world. More than 80% of road accide...
Automobile Driving Distracted Driving Accidents, Traffic Attention Deep Learning
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