Currently, autonomous vehicles (AVs) have gained considerable research interest in motion
planning (MP) to control driving. Deep learning (DL) is a subset of machine learning …

Self-Driving Vehicles (SDVs) are increasingly popular, with companies like Google, Uber,
and Tesla investing significantly in self-driving technology. These vehicles could transform …

This paper presents an interactive lane keeping model for an advanced driver assistant
system and autonomous vehicle. The proposed model considers not only the lane markers …

Motion planning is an essential part of autonomous vehicles. The planning process should
respond to environmental changes in real time to ensure safety. This paper proposes an …

Abstract Lane Changing Decision Model (LCDM) is a critical component in semi-and fully-
automated driving systems. Recent research has found that Fuzzy Inference System (FIS) is …

The trajectory prediction is crucial for autonomous vehicles to avoid collisions. This paper
optimizes trajectory prediction and lane-changing decisions for autonomous driving using …

Numerous traffic accidents and near-crashes are caused by lane-changing maneuvers. A
merging vehicle (MV) on a freeway acceleration lane (AL) has to merge into the faster …

The adaptive cruise is an important vehicle control process for unmanned vehicles. This
paper studies coordinated adaptive cruise control (ACC) of energy-saving in an intelligent …

Movement intention inference for non-cooperative evasive targets in urban environments is
difficult due to the lack of a priori knowledge of the possible target's movement intentions set …

Autonomous driving has been gaining a lot of attention in the field of transportation
technology in recent years. The use of autonomous vehicles has the potential to reduce the …