AIMC Topic: Automobile Driving

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Guided Depth Completion with Instance Segmentation Fusion in Autonomous Driving Applications.

Sensors (Basel, Switzerland) Dec 7, 2022
Pixel-level depth information is crucial to many applications, such as autonomous driving, robotics navigation, 3D scene reconstruction, and augmented reality. However, depth information, which is usually acquired by sensors such as LiDAR, is sparse....
Neural Networks, Computer Robotics Augmented Reality Automobile Driving
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Deep Deterministic Policy Gradient-Based Autonomous Driving for Mobile Robots in Sparse Reward Environments.

Sensors (Basel, Switzerland) Dec 7, 2022
In this paper, we propose a deep deterministic policy gradient (DDPG)-based path-planning method for mobile robots by applying the hindsight experience replay (HER) technique to overcome the performance degradation resulting from sparse reward proble...
Computer Simulation Policy Robotics Reward Automobile Driving
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A Study on Object Detection Performance of YOLOv4 for Autonomous Driving of Tram.

Sensors (Basel, Switzerland) Nov 21, 2022
Recently, autonomous driving technology has been in the spotlight. However, autonomous driving is still in its infancy in the railway industry. In the case of railways, there are fewer control elements than autonomous driving of cars due to the chara...
Artificial Intelligence Automobiles Automobile Driving Visual Perception Motor Vehicles
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SNAL: sensitive non-associative learning network configuration for the automatic driving strategy.

Scientific reports Nov 21, 2022
Nowadays, there is a huge gap between autonomous vehicles and mankind in terms of the decision response against some dangerous scenarios, which would has stressed the potential users out and even made them nervous. To efficiently identify the possibl...
Humans Neural Networks, Computer Algorithms Computer Simulation Automobile Driving
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Adverse Weather Target Detection Algorithm Based on Adaptive Color Levels and Improved YOLOv5.

Sensors (Basel, Switzerland) Nov 7, 2022
With the continuous development of artificial intelligence and computer vision technology, autonomous vehicles have developed rapidly. Although self-driving vehicles have achieved good results in normal environments, driving in adverse weather can st...
Artificial Intelligence Algorithms Weather Automobile Driving
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Predicting intersection crash frequency using connected vehicle data: A framework for geographical random forest.

Accident; analysis and prevention Nov 4, 2022
Accurate crash frequency prediction is critical for proactive safety management. The emerging connected vehicles technology provides us with a wealth of vehicular motion data, which enables a better connection between crash frequency and driving beha...
Humans Artificial Intelligence Random Forest Accidents, Traffic Automobile Driving Geography
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Building a Real-Time Testing Platform for Unmanned Ground Vehicles with UDP Bridge.

Sensors (Basel, Switzerland) Nov 4, 2022
Perception and vehicle control remain major challenges in the autonomous driving domain. To find a proper system configuration, thorough testing is needed. Recent advances in graphics and physics simulation allow researchers to build highly realistic...
Computer Simulation Reactive Oxygen Species Robotics Automobile Driving Uridine Diphosphate
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A Deep Learning Framework for Accurate Vehicle Yaw Angle Estimation from a Monocular Camera Based on Part Arrangement.

Sensors (Basel, Switzerland) Oct 20, 2022
An accurate object pose is essential to assess its state and predict its movements. In recent years, scholars have often predicted object poses by matching an image with a virtual 3D model or by regressing the six-degree-of-freedom pose of the target...
Deep Learning Data Collection Automobile Driving Movement
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A real-time driver fatigue identification method based on GA-GRNN.

Frontiers in public health Oct 20, 2022
It is of great practical and theoretical significance to identify driver fatigue state in real time and accurately and provide active safety warning in time. In this paper, a non-invasive and low-cost method of fatigue driving state identification ba...
Humans Neural Networks, Computer Algorithms Cluster Analysis Automobile Driving Fatigue
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Vehicle Driving Risk Prediction Model by Reverse Artificial Intelligence Neural Network.

Computational intelligence and neuroscience Oct 7, 2022
The popularity of private cars has brought great convenience to citizens' travel. However, the number of private cars in society is increasing yearly, and the traffic pressure on the road is also increasing. The number of traffic accidents is increas...
Neural Networks, Computer Artificial Intelligence Automobiles Accidents, Traffic Automobile Driving
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