In current years, the improvement of deep learning has brought about tremendous changes:
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …

Predicting diverse yet admissible trajectories that adhere to the map constraints is
challenging. Graph-based scene encoders have been proven effective for preserving local …

Intelligent vehicle technology has made tremendous progress due to Artificial Intelligence
(AI) techniques. Accurate behavior prediction of surrounding traffic actors is essential for the …

An architectural floorplan is a class of drawings that reflects the layout of rooms. The
difference between a floorplan and a natural image and its dual features as both a vector …

Occlusion is a critical problem in the Autonomous Driving System. Solving this problem
requires robust collaboration among autonomous vehicles traveling on the same roads …

In this work, we propose a novel approach for integrating rules into traffic agent trajectory
prediction. Consideration of rules is important for understanding how people behave-yet, it …

Trajectory prediction is an important task to support safe and intelligent behaviours in
autonomous systems. Many advanced approaches have been proposed over the years with …

Predicting a vehicle's trajectory is an essential ability for autonomous vehicles navigating
through complex urban traffic scenes. Bird's-eye-view roadmap information provides …

We develop a deep generative model built on a fully differentiable simulator for multi-agent
trajectory prediction. Agents are modeled with conditional recurrent variational neural …

We present a learning-based planner that aims to robustly drive a vehicle by mimicking
human drivers' driving behavior. We leverage a mid-to-mid approach that allows us to …