AIMC Topic: Automobile Driving

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Minimalistic optic flow sensors applied to indoor and outdoor visual guidance and odometry on a car-like robot.

Bioinspiration & biomimetics
Here we present a novel bio-inspired optic flow (OF) sensor and its application to visual  guidance and odometry on a low-cost car-like robot called BioCarBot. The minimalistic OF sensor was robust to high-dynamic-range lighting conditions and to var...

Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research.

Computational intelligence and neuroscience
The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortco...

Driving a Semiautonomous Mobile Robotic Car Controlled by an SSVEP-Based BCI.

Computational intelligence and neuroscience
Brain-computer interfaces represent a range of acknowledged technologies that translate brain activity into computer commands. The aim of our research is to develop and evaluate a BCI control application for certain assistive technologies that can be...

Does assisted driving behavior lead to safety-critical encounters with unequipped vehicles' drivers?

Accident; analysis and prevention
With Intelligent Transport Systems (e.g., traffic light assistance systems) assisted drivers are able to show driving behavior in anticipation of upcoming traffic situations. In the years to come, the penetration rate of such systems will be low. The...

Can cyclist safety be improved with intelligent transport systems?

Accident; analysis and prevention
In recent years, Intelligent Transport Systems (ITS) have assisted in the decrease of road traffic fatalities, particularly amongst passenger car occupants. Vulnerable Road Users (VRUs) such as pedestrians, cyclists, moped riders and motorcyclists, h...

Evaluation of Strategies for Integrated Classification of Visual-Manual and Cognitive Distractions in Driving.

Human factors
BACKGROUND: Prior studies have demonstrated unique driver behavior outcomes when visual and cognitive distraction occurs simultaneously as compared to the occurrence of one form of distraction alone. This situation implies additional complexity for t...

Investigating driver injury severity patterns in rollover crashes using support vector machine models.

Accident; analysis and prevention
Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is important to investigate the factors that affect rollover crashes and their influence on driver injury severity outcomes. This study employs support vector ...

The utility of automated measures of ocular metrics for detecting driver drowsiness during extended wakefulness.

Accident; analysis and prevention
Slowed eyelid closure coupled with increased duration and frequency of closure is associated with drowsiness. This study assessed the utility of two devices for automated measurement of slow eyelid closure in a standard poor performance condition (al...

Brain Dynamics in Predicting Driving Fatigue Using a Recurrent Self-Evolving Fuzzy Neural Network.

IEEE transactions on neural networks and learning systems
This paper proposes a generalized prediction system called a recurrent self-evolving fuzzy neural network (RSEFNN) that employs an on-line gradient descent learning rule to address the electroencephalography (EEG) regression problem in brain dynamics...