… prediction learning and also the only method that ensures kinematic and environmental
feasibility in data-driven trajectory prediction… x(s(t),d(t)) is formed by every combinations in Tlon × …

… , we establish a data-driven car-following model based on CNN-BiLSTM-Attention, for CAV to
predict trajectory, by referring to … Combined with the idea of the GM car-following model, the …

… In this paper, we addressed the safety–critical task of vehicle trajectory prediction also known
… work will pave the way to more methods combining the best of knowledge and data driven …

… of purely data-driven methods (eg, Gaussian mixture models … prediction accuracy at the level
of individual vehicles by … of when model-based and model-free approaches should be used …

… Spielberg et al. presented a neural network vehicle model based on a … DNN modeling
approach for predicting the vehicle dynamics. … The mean square error (MSE) combined with L2 …

… estimation method realized by combining model-based and data-driven methods based on
a … can not only estimate the current capacity of LIBs, but can also predict the decay trajectory …

… the value of the unknown functions for a given trajectory. … Our method attempts to utilize the
capabilities of model-based (MPC) and data-driven (machine learning algorithm) approaches…

… In addition, the nonlinear model-based control algorithms … Combining the prediction results
of lateral velocity and yaw rate… for autonomous automobile path tracking with uncertain dis…

… prediction. In general, these algorithms can be divided into model-based and data-driven
approaches[3]. … Then, FI and F-II are combined to obtain a new F-III feature. Therefore, F-III is a …

… , which is a revised model based on our previous work [31]. … , combining one feature with
the data-driven features from the … of features as the datadriven features from the prior learning-…