Most traffic accidents are caused by bad driving habits. Online monitoring of the abnormal
driving behaviors of drivers can help reduce traffic accidents. Recently, abnormal driving …

Drivers' improper driving behavior plays a vital role in road accidents. Different approaches
have been proposed to classify and evaluate driving performance to ensure road safety …

Physiological signal monitoring and driver behavior analysis have gained increasing
attention in both fundamental research and applied research. This study involved the …

In driver monitoring various data types are collected from drivers and used for interpreting,
modeling, and predicting driver behavior, and designing interactions. Aim of this contribution …

Drivers can be identified through patterns in their routine driving behaviours, as observed by
analysing the timing and sequence of various manoeuvres. In contemporary mobility …

Driver's behavior is expressed by the intentional and unintentional actions the driver
performs while driving a motor vehicle. This behavior could be influenced by several factors …

Driver behaviour modelling is a critical field that addresses complex and dynamic driving
behaviours on roads with the goal of enhancing road safety, reducing air pollution, and …

Autotheft is a crime that can be mitigated using artificial intelligence as a scientific approach.
In this case, we assess the drivers driving pattern using both deep neural network and …

Abnormal drivers are individuals who drive above the speed limit, change speed suddenly,
or change vehicle lateral position incessantly. Monitoring these abnormal driving behaviours …

Millions of lives are lost due to road accidents each year, emphasizing the importance of
improving driver safety measures. In addition, physical vehicle security is a persistent …