Extracted driving behavior of human driven vehicles can benefit the development of various
applications like trajectory prediction or planning, abnormal driving detection, driving …

How autonomous vehicles and human drivers share public transportation systems is an
important problem, as fully automatic transportation environments are still a long way off …

The ultimate goal of self-driving technologies is to offer a safe and human-like driving
experience. As one of the most important enabling functionalities, trajectory planning has …

In the coming decades, it is a universal consensus that autonomous vehicles (AVs) and
human-driven vehicles will share the traffic roads. Trajectory planning of AVs has been …

Human-like driving is of great significance for safety and comfort of autonomous vehicles,
but existing trajectory planning methods for on-road vehicles rarely take the similarity with …

In this paper, we assess the state of the art in pedestrian trajectory prediction within the
context of generating single trajectories, a critical aspect aligning with the requirements in …

Though automated vehicles (AVs) are believed to play a crucial role in future transport,
human driving vehicles will share the road with automated vehicles for a relatively long …

Trajectory planning has generally been framed as finding the lowest cost one from a set of
trajectory candidates, where the cost function has been hand-crafted with carefully tuned …

Research in the areas related to driving behavior, eg, behavior modeling and prediction,
requires datasets with highly interactive vehicle motions. Existing public vehicle motion …

The development and validation of automated vehicles involves a large number of
challenges to be overcome. Due to the high complexity, many classic approaches quickly …