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 …

Road traffic accidents involving collisions between vehicles and pedestrians are a major
cause of death and injury globally. With recent technological progress in the field of …

With the ongoing development of automated driving systems, the crucial task of predicting
pedestrian behavior is attracting growing attention. The prediction of future pedestrian …

In this paper, we delve into the pedestrian behavior understanding problem from the
perspective of three different tasks: intention estimation, action prediction, and event risk …

A traffic scene graph effectively models relationships among traffic entities and holds
significant importance in enhancing the high-level scene-understanding capabilities of …

This study introduces the crossing intention and trajectory with the Transformer networks
(CITraNet) prediction model to process multimodal input data of vulnerable road users …

Accurate prediction of whether pedestrians will cross the street is prevalently recognized as
an indispensable function of autonomous driving systems, especially in urban environments …

The article explores the potential of integrating the YOLOv3 detection algorithm with
trajectory prediction in ADAS systems. It presents the concept and analyzes the …