Autonomous driving in urban environments requires intelligent systems that are able to deal
with complex and unpredictable scenarios. Traditional modular approaches focus on …

Autonomous driving is an active area of research in artificial intelligence and robotics.
Recent advances in deep reinforcement learning (DRL) show promise for training …

Using reinforcement learning (RL) for torque distribution of skid steering vehicles has
attracted increasing attention recently. Various RL-based torque distribution methods have …

Lane changing behavior has a significant impact on traffic efficiency and may lead to traffic
delays or even accidents. It is important to plan a safe and efficient lane‐changing trajectory …

Driving event detection and driver behavior recognition have been widely explored for many
purposes, including detecting distractions, classifying driver actions, detecting kidnappings …

Rural two-lane highways are the most common road type both in Poland and globally. In
terms of kilometres, their length is by far greater than that of motorways and expressways …

Due to the advantages of their drive configuration form, skid-steering vehicles with
independent wheel drive systems are widely used in various special applications. However …

Nonlinear optimization-based motion planning algorithms have been successfully used for
dynamically feasible trajectory planning of road vehicles. However, the main drawback of …

With the maturity and development of autonomous driving technology, mixed autonomous
and manual vehicle traffic will become the main form of traffic flow in the future. First …

Decision-making is one of the key parts of the research on vehicle longitudinal autonomous
driving. Considering the behavior of human drivers when designing autonomous driving …