Real-time forecasting of driver-vehicle dynamics on 3D roads: A deep-learning framework leveraging Bayesian optimisation-Reference-Cited by-同舟云学术

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Real-time forecasting of driver-vehicle dynamics on 3D roads: A deep-learning framework leveraging Bayesian optimisation

Published:2023-11 Issue: Volume:156 Page:104329
ISSN:0968-090X
Container-title:Transportation Research Part C: Emerging Technologies
language:en
Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Paparusso Luca^ORCID,Melzi Stefano^ORCID,Braghin Francesco

Publisher

Elsevier BV

Subject

Management Science and Operations Research,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference41 articles.

1. Robust optimal motion cueing algorithm based on the linear quadratic regulator method and a genetic algorithm;Asadi;IEEE Trans. Syst. Man Cybern.: Syst.,2017

2. A review of high-definition map creation methods for autonomous driving;Bao;Eng. Appl. Artif. Intell.,2023

3. A real time implementation of MPC based motion cueing strategy for driving simulators;Beghi,2012

4. A real-time implementation of an MPC-Based motion cueing strategy with time-varying prediction;Beghi,2013

5. The Multibody Systems Approach to Vehicle Dynamics;Blundell,2004

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