… This paper studies neural network models of vehicle dynamics. We consider both models
with a generic layer architecture and models with specialised topologies that hard-wire physics …

… Neural networks can be trained with recorded vehicle data to represent the vehicle’s
dynamic behavior. We present a neural network architecture that has advantages over a physics…

… real vehicle and the associated hybrid learning scheme. The NN vehicle models the actual
vehicle dynamic behavior with the architecture of a real-time recurrent network. The NN was …

… dynamics is investigated in Section 5. Online training of a neural network to model nonlinear
vehicle dynamics … Because vehicle dynamics are time variant the neural network structure …

… In this part of the study, we examine how ANNs can be used in the area of road vehicle
dynamics. One of the most famous examples involving self-learning systems was carried out for …

… dynamics of a Mercedes-Benz experimental lorry. In the FEM approximation of vehicle dynamics
… [9], and a multilayer perceptron neural network. In Section V experimental results with a …

… vehicles, it is necessary to acquire precise vehicle dynamics for … vehicle dynamics due to
the presence of uncertainty and nonlinearities [1], [2], [3]. The nonlinear behavior in the vehicle …

… neural network vehicle dynamics model. The feedback connection of a network can describe
complex dynamics. The … and strong coupling characteristics of a vehicle. The test results of …

… neural network (DNN) based model to predict longitudinal-lateral dynamics of an autonomous
vehicle… to develop a vehicle dynamics model. The equations of motion of the closed-loop …

… neural network (RNN), one of the most well-known methods for sequential time-series data
applications, because the vehicle dynamic … The raw data from the vehicle dynamics from …