Related papers: Methods and Tools for Monitoring Driver's Behavior
Driving is a complex daily activity indicating age and disease related cognitive declines. Therefore, deficits in driving performance compared with ones without mild cognitive impairment (MCI) can reflect changes in cognitive functioning.…
Alertness monitoring in the context of driving improves safety and saves lives. Computer vision based alertness monitoring is an active area of research. However, the algorithms and datasets that exist for alertness monitoring are primarily…
The increasing number of accidents caused by alcohol-impaired driving has prompted the development of integrated safety systems in vehicles to monitor driver behavior and prevent crashes. This paper explores how drivers perceive these…
Risky drivers account for 70% of fatal accidents in the United States. With recent advances in sensors and intelligent vehicular systems, there has been significant research on assessing driver behavior to improve driving experiences and…
We introduce scenario-based cognitive status identification in older drivers from naturalistic driving videos, leveraging large vision models. In recent times, cognitive decline including Dementia and Mild Cognitive Impairment (MCI), is…
A traffic monitoring system is an integral part of Intelligent Transportation Systems (ITS). It is one of the critical transportation infrastructures that transportation agencies invest a huge amount of money to collect and analyze the…
In light of growing attention of intelligent vehicle systems, we propose developing a driver model that uses a hybrid system formulation to capture the intent of the driver. This model hopes to capture human driving behavior in a way that…
Both assistant driving and self-driving have attracted a great amount of attention in the last few years. However, the majority of research efforts focus on safe driving; few research has been conducted on in-vehicle climate control, or…
The future of transportation is being shaped by technology, and one revolutionary step in improving road safety is the incorporation of robotic systems into driver monitoring infrastructure. This literature review explores the current…
About 30% of all traffic crash fatalities in the United States involve drunk drivers, making the prevention of drunk driving paramount to vehicle safety in the US and other locations which have a high prevalence of driving while under the…
A smart vehicle should be able to monitor the actions and behaviors of the human driver to provide critical warnings or intervene when necessary. Recent advancements in deep learning and computer vision have shown great promise in…
Road traffic accidents remain a significant global concern, with human error, particularly distracted and impaired driving, among the leading causes. This study introduces a novel driver behaviour classification system that uses external…
Drivers cognitive and physiological states affect their ability to control their vehicles. Thus, these driver states are important to the safety of automobiles. The design of advanced driver assistance systems (ADAS) or autonomous vehicles…
Given the rapid advance in ITS technologies, future mobility is pointing to vehicular autonomy. However, there is still a long way before full automation, and human intervention is required. This work sheds light on understanding human…
The last decade's market has been characterized by wearable devices, mainly smartwatches, edge, and cloud computing. A possible application of these technologies is to improve the safety of dangerous activities, especially driving motor…
Manual traffic surveillance can be a daunting task as Traffic Management Centers operate a myriad of cameras installed over a network. Injecting some level of automation could help lighten the workload of human operators performing manual…
Despite the continual advances in Advanced Driver Assistance Systems (ADAS) and the development of high-level autonomous vehicles (AV), there is a general consensus that for the short to medium term, there is a requirement for a human…
We present a novel approach to automatically identify driver behaviors from vehicle trajectories and use them for safe navigation of autonomous vehicles. We propose a novel set of features that can be easily extracted from car trajectories.…
Assessing the driver's attention and detecting various hazardous and non-hazardous events during a drive are critical for driver's safety. Attention monitoring in driving scenarios has mostly been carried out using vision (camera-based)…
Driving is a daily routine for many individuals across the globe. This paper presents the configuration and methodologies used to transform a vehicle into a connected ecosystem capable of assessing driver physiology. We integrated an array…