… and motion planning of autonomous vehicles. This paper proposes a graph-based spatial-temporal
convolutional network (GSTCN) to predict … classification and motion prediction,” IEEE …

… on motion prediction at multi-lane turn intersections based on information from on-board
sensors in autonomous … The key objectives for motion predictors for autonomous driving are …

… Trajectory planning is a significant component of autonomous vehicle system, … , the motion
prediction of other traffic participants is considered. We use Monte Carlo simulation to predict …

… We propose GenAD, a generative framework that casts autonomous driving into a generative
… model autonomous driving as a future generation problem and conduct motion prediction …

… In summary, the presented state of the art in motion prediction is extensively investigated
with prediction competitions on large-scale datasets. In contrast, the feature of scenario …

… While evaluating the importance of our proposed pretext tasks, we wish to underline that
motion prediction for autonomous driving is a safety-critical task, especially at intersections …

… We also discuss the availability of these input data in autonomous driving applications. …
Laugier, “A survey on motion prediction and risk assessment for intelligent vehicles,” …

… , including but not limited to motion prediction, behavior analysis and modeling, decisionmaking,
planning, interactive behavior recognition, and driving behavior generation. We used …

… and a 2-Stage prediction model to improve the accuracy in predicting the intention of …
points based on the experience of human drivers. Using the prediction results, we design a new …

… is crucial for the safety of autonomous driving. Recent motion prediction approaches
attempt to achieve such multimodal motion prediction by implicitly regularizing the feature or …