In driving scenes, road agents often engage in frequent interaction and strive to understand
their surroundings. Ego-agent (each road agent itself) predicts what behavior will be …

Accurate prediction of agent motion trajectories is crucial for autonomous driving,
contributing to the reduction of collision risks in human-vehicle interactions and ensuring …

Social relations have substantial impacts on the potential trajectories of each individual.
Modeling these dynamics has been a central solution for more precise and accurate …

Ensuring that intelligent vehicles do not cause fatal collisions remains a persistent challenge
due to pedestrians' unpredictable movements and behavior. The potential for risky situations …

Safe, socially compliant, and efficient navigation of low-speed autonomous vehicles (AVs) in
pedestrian-rich environments necessitates considering pedestrians' future positions and …

Predicting the trajectory of pedestrians in crowd scenarios is indispensable in self-driving or
autonomous mobile robot field because estimating the future locations of pedestrians …

This paper proposes a novel prediction model termed the social and spatial attentive
generative adversarial network (SSA-GAN). The SSA-GAN framework utilizes a generative …

Accurate pedestrian trajectory prediction is essential for the advancement of intelligent robot
or autonomous vehicle, which is a challenging and interesting task. In this paper, a Scene …

Traffic incidents involving vulnerable road users (VRUs) constitute a significant proportion of
global road accidents. Advances in traffic communication ecosystems, coupled with …

The concept of Prosumer has enabled consumers to actively participate in Peer-to-Peer
(P2P) energy trading, particularly as Renewable Energy Source (RES) s and Electric …