In this paper, we propose a deep learning based vehicle trajectory prediction technique
which can generate the future trajectory sequence of surrounding vehicles in real time. We …

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 …

Predicting the trajectories of surrounding vehicles is important to avoid or mitigate collision
with traffic participants. However, due to limited past information and the uncertainty in future …

In order to drive safely and efficiently on public roads, autonomous vehicles will have to
understand the intentions of surrounding vehicles, and adapt their own behavior …

Self-driving vehicles need to continuously analyse the driving scene, understand the
behavior of other road users and predict their future trajectories in order to plan a safe …

In order to safely and efficiently drive through the complex traffic scenarios, predicting the
trajectory of the forward vehicle accurately is important for intelligent vehicles. Accurate and …

It is of great interest for autonomous vehicles to predict the trajectory of other vehicles when
planning a safe trajectory. To accurately predict the trajectory of the target vehicle, the …

In vehicle trajectory prediction, the difficulty in modeling the interaction relationship between
vehicles lies in constructing the interaction structure between the vehicles in the traffic …

As autonomous vehicles (AVs) need to interact with other road users, it is of importance to
comprehensively understand the dynamic traffic environment, especially the future possible …

Accurate trajectory prediction of surrounding road users is critical to autonomous driving
systems. In mixed traffic flows, road users with different kinds of behaviors and styles bring …