No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

With the significant advancement of sensor and communication technology and the reliable
application of obstacle detection techniques and algorithms, automated driving is becoming …

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …

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 …

Simultaneous trajectory prediction for multiple heterogeneous traffic participants is essential
for safe and efficient operation of connected automated vehicles under complex driving …

Intelligent Automation (IA) in automobiles combines robotic process automation and artificial
intelligence, allowing digital transformation in autonomous vehicles. IA can completely …

In this paper, we propose HOME, a framework tackling the motion forecasting problem with
an image output representing the probability distribution of the agent's future location. This …

The ability to predict, anticipate and reason about future outcomes is a key component of
intelligent decision-making systems. In light of the success of deep learning in computer …

Forecasting the trajectories of neighbor vehicles is a crucial step for decision making and
motion planning of autonomous vehicles. This paper proposes a graph-based spatial …

Dynamic machine vision requires recognizing the past and predicting the future of a moving
object based on present vision. Current machine vision systems accomplish this by …