Longitudinal Vehicle Dynamics: A Comparison of Physical and Data-Driven Models Under Large-Scale Real-World Driving Conditions

Longitudinal Vehicle Dynamics: A Comparison of Physical and Data-Driven Models Under Large-Scale Real-World Driving Conditions

Mathematical models of vehicle dynamics will form essential components of future autonomous vehicles. They may be used within inverse or forward control loops, or within predictive learning systems. Often, nonlinear physical models are used in this context, which, though conceptually simple (especia...

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Bibliographic Details
Main Authors: Sebastian S. James, Sean R. Anderson, Mauro Da Lio
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Data-driven
state estimation
linear
neural network
nonlinear
state-space
Online Access:https://ieeexplore.ieee.org/document/9069926/

Internet

https://ieeexplore.ieee.org/document/9069926/

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