An autonomous vehicle can operate itself without any human interaction through the
capacity to sense its surroundings. It requires a navigation plan to travel avoiding collision …

The use of machine learning in the self-driving industry has boosted a number of recent
advancements. In particular, the usage of large deep learning models in the perception and …

This comprehensive review focuses on the Autonomous Driving System (ADS), which aims
to reduce human errors that are the reason for about 95% of car accidents. The ADS …

Recent advancements in self-driving car technologies have enabled them to navigate
autonomously through various environments. However, one of the critical challenges in …

We present a data-driven motion planner for the trajectory generation in a complex
environment based on the global map and the vehicle-centric local view, and demonstrate …

In this manuscript, we introduce a real-time motion planning system based on the Baidu
Apollo (open source) autonomous driving platform. The developed system aims to address …

Path planning plays a vital role in autonomous driving. It is the replication of the reasoning
and decision-making of a human brain. This paper is about analyzing and optimizing a …

We present a framework for robust autonomous driving motion planning system in urban
environments which includes trajectory refinement, trajectory interpolation, avoidance of …

In this paper, we introduce a practical two-layer planning framework for autonomous
vehicles operating in unknown off-road environment. The first layer refers to a global path …

Our research introduces a modular motion planning framework for autonomous vehicles
using a sampling-based trajectory planning algorithm. This approach effectively tackles the …