In this paper we propose a novel end-to-end learnable network that performs joint
perception, prediction and motion planning for self-driving vehicles and produces …

For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

In a mixed traffic environment of human and autonomous driving, it is crucial for an
autonomous vehicle to predict the lane change intentions and trajectories of vehicles that …

End-to-end autonomous driving has great potential in the transportation industry. However,
the lack of transparency and interpretability of the automatic decision-making process …

Vehicle taillight detection is essential to analyze and predict driver intention in collision
avoidance systems. In this article, we propose an end-to-end framework that locates the rear …

Automobiles are the primary means of transportation and increased traffic leads to the
emphasis on techniques for safe transportation. Vehicle brake light detection is essential to …

Abstract Systems and methods for determining object intentions through visual attributes are
provided. A method can include determining, by a computing system, one or more regions of …

Autonomous vehicles (AVs) are widely believed to be good for improving transportation
safety and efficiency. However, recent fatal accidents by some of their prototypes remind us …

Vehicle taillight intention detection is an important application for perception and decision
making by intelligent vehicles. However, effectively improving detection precision with …

Predicting future events accurately is a task of great importance for autonomous vehicles. In
this work we focus on lane change events. For this, we propose a novel attention …