The motion planners used in self-driving vehicles need to generate trajectories that are safe,
comfortable, and obey the traffic rules. This is usually achieved by two modules: behavior …

Autonomous Vehicles have wide-ranging applications in off-road environments. Off-road
vehicular scenes can be abstracted as multi-agent systems, and trajectory prediction is a …

In this work, we present a decision-making system for automated vehicles driving in highway
environments. The task is modeled as a Partially Observable Markov Decision Process, in …

This paper presents a model predictive trajectory optimization and tracking framework to
avoid collisions for autonomous vehicles in highly constrained environments. Firstly, a …

Vehicle trajectory prediction is a keystone for the application of the internet of vehicles (IoV).
With the help of deep learning and big data, it is possible to understand the between-vehicle …

In this paper, we investigate a novel collision probability-aware human-machine cooperative
planning and tracking method for enhancing safety of automated vehicles. Firstly, a long …

Despite the advancements in the technologies of autonomous driving, it is still challenging to
study the safety of a self-driving vehicle. Trajectory prediction is one core function of an …

This paper outlines a predictive maneuver-planning method for autonomous vehicle
navigating public highway traffic. The method integrates discrete maneuvering decisions, ie …

Autonomous driving is one of the promising technologies to tackle traffic accident and
congestion problems nowadays. Even though an autonomous vehicle is operated without …

This paper presents a segmented trajectory planning strategy for active collision avoidance
system. Considering the longitudinal and lateral movement of the obstacle vehicle, as well …