The application of machine learning techniques for driving behavior analysis: A conceptual framework and a systematic literature review
ZE Abou Elassad, H Mousannif… - … Applications of Artificial …, 2020 - Elsevier
Driving Behavior (DB) is a complex concept describing how the driver operates the vehicle
in the context of the driving scene and surrounding environment. Recently, DB assessment …
in the context of the driving scene and surrounding environment. Recently, DB assessment …
Driver distraction detection methods: A literature review and framework
Driver inattention and distraction are the main causes of road accidents, many of which
result in fatalities. To reduce road accidents, the development of information systems to …
result in fatalities. To reduce road accidents, the development of information systems to …
Driver activity recognition for intelligent vehicles: A deep learning approach
Driver decisions and behaviors are essential factors that can affect the driving safety. To
understand the driver behaviors, a driver activities recognition system is designed based on …
understand the driver behaviors, a driver activities recognition system is designed based on …
Driver lane change intention inference for intelligent vehicles: Framework, survey, and challenges
Intelligent vehicles and advanced driver assistance systems (ADAS) need to have proper
awareness of the traffic context, as well as the driver status since ADAS share the vehicle …
awareness of the traffic context, as well as the driver status since ADAS share the vehicle …
Looking at humans in the age of self-driving and highly automated vehicles
E Ohn-Bar, MM Trivedi - IEEE Transactions on Intelligent …, 2016 - ieeexplore.ieee.org
This paper highlights the role of humans in the next generation of driver assistance and
intelligent vehicles. Understanding, modeling, and predicting human agents are discussed …
intelligent vehicles. Understanding, modeling, and predicting human agents are discussed …
Decision-making in driver-automation shared control: A review and perspectives
Shared control schemes allow a human driver to work with an automated driving agent in
driver-vehicle systems while retaining the driverʼ s abilities to control. The human driver, as …
driver-vehicle systems while retaining the driverʼ s abilities to control. The human driver, as …
Driving posture recognition by convolutional neural networks
Driver fatigue and inattention have long been recognised as the main contributing factors in
traffic accidents. This study presents a novel system which applies convolutional neural …
traffic accidents. This study presents a novel system which applies convolutional neural …
Visual human–computer interactions for intelligent vehicles and intelligent transportation systems: The state of the art and future directions
Research on intelligent vehicles has been popular in the past decade. To fill the gap
between automatic approaches and man-machine control systems, it is indispensable to …
between automatic approaches and man-machine control systems, it is indispensable to …
Identification and analysis of driver postures for in-vehicle driving activities and secondary tasks recognition
Driver decisions and behaviors regarding the surrounding traffic are critical to traffic safety. It
is important for an intelligent vehicle to understand driver behavior and assist in driving tasks …
is important for an intelligent vehicle to understand driver behavior and assist in driving tasks …
Distracted driver classification using deep learning
M Alotaibi, B Alotaibi - Signal, Image and Video Processing, 2020 - Springer
One of the most challenging topics in the field of intelligent transportation systems is the
automatic interpretation of the driver's behavior. This research investigates distracted driver …
automatic interpretation of the driver's behavior. This research investigates distracted driver …