AIMC Topic: Automobile Driving

Clear Filters Showing 111 to 120 of 272 articles

Deep Learning with LPC and Wavelet Algorithms for Driving Fault Diagnosis.

Sensors (Basel, Switzerland)
Vehicle fault detection and diagnosis (VFDD) along with predictive maintenance (PdM) are indispensable for early diagnosis in order to prevent severe accidents due to mechanical malfunction in urban environments. This paper proposes an early voicepri...

Real-Time and Efficient Multi-Scale Traffic Sign Detection Method for Driverless Cars.

Sensors (Basel, Switzerland)
Traffic signs detection and recognition is an essential and challenging task for driverless cars. However, the detection of traffic signs in most scenarios belongs to small target detection, and most existing object detection methods show poor perfor...

Accident Liability Determination of Autonomous Driving Systems Based on Artificial Intelligence Technology and Its Impact on Public Mental Health.

Journal of environmental and public health
With the rise of self-driving technology research, the establishment of a scientific and perfect legal restraint and supervision system for self-driving vehicles has been gradually paid attention to. The determination of tort liability subject of tra...

Coordinated Control of Intelligent Fuzzy Traffic Signal Based on Edge Computing Distribution.

Sensors (Basel, Switzerland)
With the development of Internet of Things infrastructures and intelligent traffic systems, the traffic congestion that results from the continuous complexity of urban road networks and traffic saturation has a new solution. In this research, we prop...

Risky-Driving-Image Recognition Based on Visual Attention Mechanism and Deep Learning.

Sensors (Basel, Switzerland)
Risky driving behavior seriously affects the driver's ability to react, execute and judge, which is one of the major causes of traffic accidents. The timely and accurate identification of the driving status of drivers is particularly important, since...

An Effective Approach of Vehicle Detection Using Deep Learning.

Computational intelligence and neuroscience
With the rise of unmanned driving and intelligent transportation research, great progress has been made in vehicle detection technology. The purpose of this paper is employing the method of deep learning to study the vehicle detection algorithm, in w...

Generalized Single-Vehicle-Based Graph Reinforcement Learning for Decision-Making in Autonomous Driving.

Sensors (Basel, Switzerland)
In the autonomous driving process, the decision-making system is mainly used to provide macro-control instructions based on the information captured by the sensing system. Learning-based algorithms have apparent advantages in information processing a...

Intelligent Research Based on Deep Learning Recognition Method in Vehicle-Road Cooperative Information Interaction System.

Computational intelligence and neuroscience
The vehicle-road collaborative information interaction system is an emerging technology system that realizes the sharing of information between vehicles, vehicles and roads between traffic road information, and driving vehicle information. It is of p...

DPSSD: Dual-Path Single-Shot Detector.

Sensors (Basel, Switzerland)
Object detection is one of the most important and challenging branches of computer vision. It has been widely used in people's lives, such as for surveillance security and autonomous driving. We propose a novel dual-path multi-scale object detection ...

Vehicle Safety-Assisted Driving Technology Based on Computer Artificial Intelligence Environment.

Computational intelligence and neuroscience
In this paper, we propose an assisted driving system implemented with a Jetson nano-high-performance embedded platform by using machine vision and deep learning technologies. The vehicle dynamics model is established under multiconditional assumption...