… and prediction modules in modern autonomous driving … -critical autonomous driving task,
where the autonomous … of traffic participants and their motion behaviors in a highly dynamic …

… for motion prediction from the uncertainty perspective, considering both motion uncertainty
and … degradation of motion prediction models, ie the decrease in the prediction accuracy, by …

… -making for autonomous vehicles (AVs). However, most motion prediction models ignore the
… proposes an interactionaware motion prediction model that is able to predict other agents’ …

… [11], [12] survey human motion prediction, which is obviously … trajectory prediction methods
used by the autonomous driving … use physicsbased methods for trajectory prediction [23]. Next…

… Abstract— Motion prediction of road users in traffic scenes is critical for autonomous driving
… We present a novel motion prediction system for autonomous driving. Our system is based …

… motion prediction. Typically, these two tasks are cascaded; agent tracking output feeds into
motion prediction… can hinder the performance of the motion prediction and planning modules. …

… The motion prediction approach that we propose in this study is shown in Figure 5. This
approach takes advantage of both convolutional and recurrent neural networks (CRNN) to …

… In order to help readers better understand the task of vehicle motion prediction in autonomous
driving, this section first introduces the relevant concepts and terminology. After that, we …

… This paper presents a joint driving behavior prediction and motion planning framework for
autonomous vehicles in complex and interactive environments. To integrate the influence of …

… [47] propose a novel paradigm, named direct perception method, to predict an affordance
for urban autonomous driving scenarios. The affordance represents a BEV format that clearly …