AIMC Topic: Automobile Driving
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Machine-learning approach to predict on-road driving ability in healthy older people.
Psychiatry and clinical neurosciences
Jul 20, 2020
AIM: In Japan, fatal traffic accidents due to older drivers are on the rise. Considering that approximately half the older drivers who have caused fatal accidents are cognitively normal healthy people, it has been required to detect older drivers who...
Adopting Machine Learning and Spatial Analysis Techniques for Driver Risk Assessment: Insights from a Case Study.
International journal of environmental research and public health
Jul 18, 2020
Traffic violations usually caused by aggressive driving behavior are often seen as a primary contributor to traffic crashes. Violations are either caused by an unintentional or deliberate act of drivers that jeopardize the lives of fellow drivers, pe...
Evaluation of mental workload during automobile driving using one-class support vector machine with eye movement data.
Applied ergonomics
Jul 6, 2020
The aim of this study is to investigate the usefulness of the anomaly detection method by one-class support vector machine (OCSVM) for the evaluation of mental workload (MWL) during automobile driving. Twelve students (six males and six females) part...
Fuzzy Inspired Deep Belief Network for the Traffic Flow Prediction in Intelligent Transportation System Using Flow Strength Indicators.
Big data
Jul 6, 2020
Intelligent transportation system (ITS) is an advance leading edge technology that aims to deliver innovative services to different modes of transport and traffic management. Traffic flow prediction (TFP) is one of the key macroscopic parameters of t...
Inferring transportation mode from smartphone sensors: Evaluating the potential of Wi-Fi and Bluetooth.
PloS one
Jul 2, 2020
Understanding which transportation modes people use is critical for smart cities and planners to better serve their citizens. We show that using information from pervasive Wi-Fi access points and Bluetooth devices can enhance GPS and geographic infor...
Beyond safety drivers: Applying air traffic control principles to support the deployment of driverless vehicles.
PloS one
May 21, 2020
By adopting and extending lessons from the air traffic control system, we argue that a nationwide remote monitoring system for driverless vehicles could increase safety dramatically, speed these vehicles' deployment, and provide employment. It is bec...
Trajectory-level fog detection based on in-vehicle video camera with TensorFlow deep learning utilizing SHRP2 naturalistic driving data.
Accident; analysis and prevention
May 11, 2020
Providing drivers with real-time weather information and driving assistance during adverse weather, including fog, is crucial for safe driving. The primary focus of this study was to develop an affordable in-vehicle fog detection method, which will p...
Detecting lane change maneuvers using SHRP2 naturalistic driving data: A comparative study machine learning techniques.
Accident; analysis and prevention
May 11, 2020
Lane change has been recognized as a challenging driving maneuver and a significant component of traffic safety research. Developing a real-time continuous lane change detection system can assist drivers to perform and deal with complex driving tasks...
Doppler-Spectrum Feature-Based Human-Vehicle Classification Scheme Using Machine Learning for an FMCW Radar Sensor.
Sensors (Basel, Switzerland)
Apr 2, 2020
In this paper, we propose a Doppler-spectrum feature-based human-vehicle classification scheme for an FMCW (frequency-modulated continuous wave) radar sensor. We introduce three novel features referred to as the scattering point count, scattering poi...
Improve Aggressive Driver Recognition Using Collision Surrogate Measurement and Imbalanced Class Boosting.
International journal of environmental research and public health
Mar 31, 2020
Real-time recognition of risky driving behavior and aggressive drivers is a promising research domain, thanks to powerful machine learning algorithms and the big data provided by in-vehicle and roadside sensors. However, since the occurrence of aggre...
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