Intelligent vehicles have increased their capabilities for highly and, even fully, automated
driving under controlled environments. Scene information is received using onboard …

One of the most challenging problems in autonomous driving is trajectory planning for lane
changes. Conventional trajectory planning is generally realized by optimizing a specific cost …

The planning of semi-autonomous vehicles in traffic scenarios is a relatively new problem
that contributes towards the goal of making road travel by vehicles free of human drivers. An …

Driving space for autonomous vehicles (AVs) is a simplified representation of real driving
environments that helps facilitate driving decision processes. Existing literatures present …

Navigating automated driving systems (ADSs) through complex driving environments is
difficult. Predicting the driving behavior of surrounding human-driven vehicles (HDVs) is a …

A novel trajectory planning method is proposed in this paper for lane change of autonomous
vehicle. Since it is difficult to accurately capture the trajectory of other vehicles, which means …

Sampling-based motion planning (SBMP) is a major algorithmic trajectory planning
approach in autonomous driving given its high efficiency and outstanding performance in …

Planning a feasible, and safe trajectory is a crucial procedure for autonomous parking which
remains to be fully solved. Generally, a trajectory is depicted by a sequence of …

This work aims to solving global path planning for multiple mobile robots. In order to get a
collision free path, an accurate map model is always essential. A roadmap is made based …

Swarm robotics is a diligence of swarm intelligence, it deals with natural and artificial
systems in an environment composed of many individuals that co-ordinate using …