Intelligent Automation (IA) in automobiles combines robotic process automation and artificial
intelligence, allowing digital transformation in autonomous vehicles. IA can completely …

For the last few decades, a lot of attention has been given to intelligent vehicle systems, and
in particular to automated safety and collision avoidance solutions. In this paper, we present …

Machine Learning is a significant technique to realize Artificial Intelligence. The Random
Forest Algorithm can be considered as one of the Machine Learning's representative …

Identifying and evaluating the potential risks in the surrounding environment is critical for
intelligent vehicles' safety and user experience. This paper provides a comprehensive …

Lane-changing (LC) is a critical task for autonomous driving, especially in complex dynamic
environments. Numerous automatic LC algorithms have been proposed. This topic …

Nowadays, machine learning (ML), which is one of the most rapidly growing technical tools,
is extensively used to solve critical challenges in various domains. Vehicular ad hoc network …

Numerous recent innovations have been achieved with the goal of enhancing electric
vehicles and the parts that go into them, particularly in the areas of managing energy, battery …

Predicting lane-changing behaviour is an integral part of lane-changing decision models
and has a significant impact on both traffic flow characteristics and traffic safety. A variety of …

Predicting the trajectories of surrounding vehicles is important to avoid or mitigate collision
with traffic participants. However, due to limited past information and the uncertainty in future …

With the concept of Internet-of-Things, autonomous vehicles can provide higher driving
efficiency, traffic safety, and freedom for the driver to perform other tasks. This paper first …