A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

Autonomous vehicles (AV) s have become a trending topic nowadays since they have the
potential to solve traffic problems, such as accidents and congestion. Although AV systems …

It is expected that a mixture of autonomous and manual vehicles will persist as a part of the
intelligent transportation system (ITS) for many decades. Thus, addressing the safety issues …

Forecasting the motion of surrounding vehicles is a critical ability for an autonomous vehicle
deployed in complex traffic. Motion of all vehicles in a scene is governed by the traffic …

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 …

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 …

To safely and efficiently navigate through complex traffic scenarios, autonomous vehicles
need to have the ability to predict the future motion of surrounding vehicles. Multiple …

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 …

Reliable prediction of surround vehicle motion is a critical requirement for path planning for
autonomous vehicles. In this paper, we propose a unified framework for surround vehicle …

Making accurate motion prediction of the surrounding traffic agents such as pedestrians,
vehicles, and cyclists is crucial for autonomous driving. Recent data-driven motion prediction …