… prediction horizon. Through evaluation on the Waymo Open Motion Dataset and a variety of
other common urban driving … -modal motion prediction in autonomous driving application,” …

… Pioneers have predicted the motion of dynamic objects with Kalman filter [1], linear trajectory
avoidance model [2], and social force model [3]. Compared to these traditional modeling …

… Autonomous vehicles. Spurred by this expanded fame, we give Deep-learning based ways
to deal with vehicle motion prediction … vehicle models for autonomous driving control design. …

… A survey on motion prediction and risk assessment for intelligent vehicles. ROBOMECH
journal, 1(1):1–14, 2014. [23] Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel. …

… III-A we perform further refinement of the motion predictions for the detected objects, where
… Metaxas, “Motionnet: Joint perception and motion prediction for autonomous driving based …

… deal with motion prediction mission for high-resolution videos. ALVINN’s autonomous vehicle
… in [36], was the first attempt to recognize driving action from pixel inputs. The efficiency of a …

… Abstract—This paper presents a planning system for autonomous driving among many
pedestrians. A key ingredient of our approach is PORCA, a pedestrian motion prediction model …

… that the predicted semantic maps allow our motion planning module to handle objects with
low probability, thus improving the safety of autonomous driving. Fig. 5 presents a driving …

… to multimodal predictions so that various future trajectories are predicted. … Predicting
the future motion of surrounding vehicles is a crucial task for path planning by autonomous …

… and multivariate vehicle motion information. To further improve the prediction accuracy and
… the short-term prediction results of the vehicle model and the driving motion characteristics. …