AIMC Topic: Automobile Driving
Clear Filters Showing 181 to 190 of 249 articles
Movement time and guidance accuracy in teleoperation of robotic vehicles.
Ergonomics
Feb 27, 2019
Two experiments are reported on the steering of a tracked vehicle through straight-line courses and corners to determine the relationships between movement time and control accuracy with the geometry of the course, such as the vehicle width, the trac...
Predicting Future Driving Risk of Crash-Involved Drivers Based on a Systematic Machine Learning Framework.
International journal of environmental research and public health
Jan 25, 2019
The objective of this paper is to predict the future driving risk of crash-involved drivers in Kunshan, China. A systematic machine learning framework is proposed to deal with three critical technical issues: 1. defining driving risk; 2. developing r...
Expressway crash risk prediction using back propagation neural network: A brief investigation on safety resilience.
Accident; analysis and prevention
Jan 17, 2019
This study presents the work in predicting crash risk on expressways with consideration of both the impact of safety critical events and traffic conditions. The traffic resilience theory is introduced to learn safety problems from the standpoint of 1...
EEG-Based Spatio-Temporal Convolutional Neural Network for Driver Fatigue Evaluation.
IEEE transactions on neural networks and learning systems
Jan 10, 2019
Driver fatigue evaluation is of great importance for traffic safety and many intricate factors would exacerbate the difficulty. In this paper, based on the spatial-temporal structure of multichannel electroencephalogram (EEG) signals, we develop a no...
Faster R-CNN and Geometric Transformation-Based Detection of Driver's Eyes Using Multiple Near-Infrared Camera Sensors.
Sensors (Basel, Switzerland)
Jan 7, 2019
Studies are being actively conducted on camera-based driver gaze tracking in a vehicle environment for vehicle interfaces and analyzing forward attention for judging driver inattention. In existing studies on the single-camera-based method, there are...
Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness.
Accident; analysis and prevention
Sep 20, 2018
Monitoring car drivers for drowsiness is crucial but challenging. The high inter-individual variability observed in measurements raises questions about the accuracy of the drowsiness detection process. In this study, we sought to enhance the performa...
Evaluating the influence of road lighting on traffic safety at accesses using an artificial neural network.
Traffic injury prevention
Aug 7, 2018
OBJECTIVES: This article focuses on the effect of road lighting on road safety at accesses to quantitatively analyze the relationship between road lighting and road safety.
Psychosocial factors associated with intended use of automated vehicles: A simulated driving study.
Accident; analysis and prevention
Apr 6, 2018
This study applied the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) to assess drivers' intended use of automated vehicles (AVs) after undertaking a simulated driving task. In addition, this study explored the potential f...
Market penetration of intersection AEB: Characterizing avoided and residual straight crossing path accidents.
Accident; analysis and prevention
Mar 30, 2018
Car occupants account for one third of all junction fatalities in the European Union. Driver warning can reduce intersection accidents by up to 50 percent; adding Autonomous Emergency Braking (AEB) delivers a reduction of up to 70 percent. However, t...
A trial of retrofitted advisory collision avoidance technology in government fleet vehicles.
Accident; analysis and prevention
Mar 13, 2018
In-vehicle collision avoidance technology (CAT) has the potential to prevent crash involvement. In 2015, Transport for New South Wales undertook a trial of a Mobileye 560 CAT system that was installed in 34 government fleet vehicles for a period of s...
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