AIMC Topic: Automobile Driving

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Outracing champion Gran Turismo drivers with deep reinforcement learning.

Nature Feb 9, 2022
Many potential applications of artificial intelligence involve making real-time decisions in physical systems while interacting with humans. Automobile racing represents an extreme example of these conditions; drivers must execute complex tactical ma...
Video Games Reinforcement, Psychology Sports Humans Competitive Behavior Deep Learning Reward Automobile Driving
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Hybrid Deep Learning Approach for Traffic Speed Prediction.

Big data Feb 2, 2022
Traffic speed prediction plays a fundamental role in traffic management and driving route planning. However, timely accurate traffic speed prediction is challenging as it is affected by complex spatial and temporal correlations. Most existing works c...
Deep Learning Humans Automobile Driving Neural Networks, Computer
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Driver Behavior Profiling and Recognition Using Deep-Learning Methods: In Accordance with Traffic Regulations and Experts Guidelines.

International journal of environmental research and public health Jan 27, 2022
The process of collecting driving data and using a computational model to generate a safety score for the driver is known as driver behavior profiling. Existing driver profiles attempt to categorize drivers as either safe or aggressive, which some ex...
Neural Networks, Computer Deep Learning Humans Recognition, Psychology Accidents, Traffic Automobile Driving
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Fast Panoptic Segmentation with Soft Attention Embeddings.

Sensors (Basel, Switzerland) Jan 20, 2022
Panoptic segmentation provides a rich 2D environment representation by unifying semantic and instance segmentation. Most current state-of-the-art panoptic segmentation methods are built upon two-stage detectors and are not suitable for real-time appl...
Image Processing, Computer-Assisted Automobile Driving Semantics Robotics Attention
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Overtaking risk modeling in two-lane two-way highway with heterogeneous traffic environment of a low-income country using naturalistic driving dataset.

Journal of safety research Dec 29, 2021
INTRODUCTION: Driver behavior related to overtaking maneuvers, which are considered a major safety risk determinant on two-lane two-way highway in low- and middle-income countries (LMIC), are an important subject of further analysis. This study evalu...
Accidents, Traffic Automobile Driving Probability Logistic Models Decision Making Humans
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Delicar: A Smart Deep Learning Based Self Driving Product Delivery Car in Perspective of Bangladesh.

Sensors (Basel, Switzerland) Dec 25, 2021
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...
Humans Computers Bangladesh Automobiles Deep Learning Automobile Driving
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Physiological signal-based drowsiness detection using machine learning: Singular and hybrid signal approaches.

Journal of safety research Dec 13, 2021
INTRODUCTION: Drowsiness is one of the main contributors to road-related crashes and fatalities worldwide. To address this pressing global issue, researchers are continuing to develop driver drowsiness detection systems that use a variety of measures...
Automobile Driving Humans Sleepiness Machine Learning Reproducibility of Results Wakefulness
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LIO-CSI: LiDAR inertial odometry with loop closure combined with semantic information.

PloS one Dec 8, 2021
Accurate and reliable state estimation and mapping are the foundation of most autonomous driving systems. In recent years, researchers have focused on pose estimation through geometric feature matching. However, most of the works in the literature as...
Generalization, Psychological Semantic Web Automobile Driving Semantics Neural Networks, Computer Algorithms Humans
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A Memristive Circuit Implementation of Eyes State Detection in Fatigue Driving Based on Biological Long Short-Term Memory Rule.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
Biological long short-term memory (B-LSTM) can effectively help human process all kinds of received information. In this work, a memristive B-LSTM circuit which mimics a conversion from short-term memory to long-term memory is proposed. That is, the ...
Humans Neural Networks, Computer Algorithms Eye-Tracking Technology Blinking Fatigue Image Processing, Computer-Assisted Automobile Driving Signal Processing, Computer-Assisted Video Recording
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Real-Time Semantic Segmentation with Dual Encoder and Self-Attention Mechanism for Autonomous Driving.

Sensors (Basel, Switzerland) Dec 2, 2021
As the techniques of autonomous driving become increasingly valued and universal, real-time semantic segmentation has become very popular and challenging in the field of deep learning and computer vision in recent years. However, in order to apply th...
Semantics Neural Networks, Computer Image Processing, Computer-Assisted Automobile Driving
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