… the simulation and motion prediction tasks. We show that motion prediction can be formulated
as the a priori simulation, hence it is a legit surrogate task for the evaluation of simulation …

… motion and estimate risk. A survey targeting techniques for modeling and predicting human
driver … a framework for comparing different driver models with motion prediction as one core …

… Specifically, we identify and classify motion prediction literature for two road user classes ie
… and vehicle motion prediction literature and is built on three dimensions ie motion modelling …

… As the overall Argoverse dataset is biased towards simple straight line trajectories, we also
evaluate prediction performance on the BT subset (results summarized in Table 2), which …

… The autonomous vehicle motion prediction literature is reviewed. Motion prediction is the
most challenging task in autonomous vehicles and self-drive cars. These challenges have …

… dataset for motion modelling, consisting of 1,118 hours of recorded self-driving perception
data … we present the largest self-driving dataset for motion prediction to date, containing over …

… , including driver or pilot experience, control of motion and motion … in simulator sickness
(SS) during exposure to simulated … of motion predictability on SS while in a driving simulator. …

… However, the prediction models have been assumed simply or omitted in the previous MPC-…
, a motion planning framework based on target motion prediction for autonomous driving at …

… In this work, we propose a motion prediction scheme based … The proposed scheme is
capable of predicting collision-free, … behavior most drivers exhibit in typical driving scenarios, ie, …

… Thus, we do not learn to predict but learn to drive like the recorded agents. Note that the …
Hence, our method blurs the line between motion prediction and end-to-end driving, with our …