This paper focuses on the real-time trajectory planning problem for autonomous vehicles
driving in realistic urban environments. To solve the complex navigation problem, we adopt …

In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …

This paper considers the problem of path planning for autonomous ground vehicles on
highways with regular traffic. The goal is to select a desired trajectory from a set of …

Diverse passengers have various driving habits and driving preferences, thus the function of
personalized driving is one of the most important features for autonomous vehicles (AVs). In …

For driving safely and comfortably, the long-term trajectory prediction of surrounding
vehicles is essential for autonomous vehicles. For handling the uncertain nature of trajectory …

The personal mobility of the future will be changed significantly by autonomous driving. To
realize this vision, the complex task of trajectory planning needs to be solved. In this article …

Motion planning for autonomous vehicles becomes more challenging when both driver
comfort and collision risk are considered. To overcome this challenge, a human-like motion …

To make autonomous vehicles consider driver's personalized characteristics, this paper
proposes an integrated model and learning combined (IMLC) algorithm to realize human …

Highly automated and fully autonomous vehicles are much more likely to be accepted if they
react in the same way as human drivers do, especially in a hybrid traffic situation, which …

In this article, a hierarchical real-time motion planning system is proposed to solve complex
navigation problem in realistic dynamic traffic environments. First, a longitudinal safety …