Autonomous driving involves multi-timescale and multi-objective tasks coupled with long-
term driving decision and short-term motion planning. However, existing studies tend to …

Motion decision-making is an open-challenging issue for autonomous driving, especially in
the complex and diverse environment. A motion decision-making model based on deep …

Decision-making and motion planning are extremely important in autonomous driving to
ensure safe driving in a real-world environment. This study proposes an online evolutionary …

In recent years, there are more and more studies on reinforcement learning (RL) and RL
algorithms have achieved good performance in autonomous driving simulation experiments …

Lateral lane-changing and longitudinal car-following behavior decision-making is crucial for
the implementation of autonomous driving (AD) in complex and dynamic traffic environment …

In autonomous driving, behavioral decision-making and trajectory planning remain huge
challenges due to the large amount of uncertainty in environments and complex interaction …

Decision-making in autonomous driving is an emerging technology that has rapid progress
over the last decade. In single-lane scenarios, autonomous vehicles should simultaneously …

The autonomous driving technology based on deep reinforcement learning (DRL) has been
confirmed as one of the most cutting-edge research fields worldwide. The agent is enabled …

The three main modules of autonomous vehicles, ie, sensing, decision making, and motion
controlling, have been studied separately in most existing works on autonomous driving …

Decision‐making is an important component of autonomous driving perception, decision‐
making, planning, and control pipeline, which undertakes the task of how the ego vehicle …