Virtual Validation and Uncertainty Quantification of an Adaptive Model Predictive Controller-Based Motion Planner for Autonomous Driving Systems

Virtual Validation and Uncertainty Quantification of an Adaptive Model Predictive Controller-Based Motion Planner for Autonomous Driving Systems

In the context of increasing research on algorithms for different modules of the autonomous driving stack, the development and evaluation of these algorithms for deployment onboard vehicles is the next critical step. In the development and verification phases, simulations play a pivotal role in achi...

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Bibliographic Details
Main Authors: Mohammed Irshadh Ismaaeel Sathyamangalam Imran, Satyesh Shanker Awasthi, Michael Khayyat, Stefano Arrigoni, Francesco Braghin
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Future Transportation
Subjects:
autonomous vehicle
model predictive control
optimal control problem
control barrier functions
obstacle avoidance
uncertainty analysis
Online Access:https://www.mdpi.com/2673-7590/4/4/74
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