The technology stack of connected and autonomous vehicles (CAV) consists of sensing,
perception, motion prediction, and motion planning Layers. With much success, the sensing …

For the autonomous driving safety, it is important to know the future trajectories of
surrounding vehicles, especially during the transition period where the autonomous and non …

As the number of various positioning sensors and location-based devices increase, a huge
amount of spatial and temporal information data is collected and accumulated. These data …

In this paper, we propose an efficient vehicle trajectory prediction framework based on
recurrent neural network. Basically, the characteristic of the vehicle's trajectory is different …

Innovative technologies and naturalistic driving data sources provide a great potential to
develop reliable autonomous driving systems. Understanding the behaviors of surrounding …

Trajectory prediction aims to estimate future location by exploring driving behavior and
historical trajectory, which is essential for driving decision-making and local motion planning …

Autonomous vehicles need the ability to predict the trajectory of surrounding vehicles, so as
to make a rational decision planning, improve driving safety and ride comfort. In this paper, a …

Vehicle route prediction is one of the significant tasks in vehicles mobility. It is one of the
means to reduce the accidents and increase comfort in human life. The task of route …

Prediction of the movement of all traffic participants is a very important task in autonomous
driving. Well-predicted behavior of other cars and actors is crucial for safety. A sequence of …

Multi-step vehicle trajectory prediction has been of great significance for location-based
services, eg, actionable advertising. Prior works focused on adopting pattern-matching …