Integrating Modular Pipelines with End-to-End Learning: A Hybrid Approach for Robust and Reliable Autonomous Driving Systems

Integrating Modular Pipelines with End-to-End Learning: A Hybrid Approach for Robust and Reliable Autonomous Driving Systems

Autonomous driving navigation relies on diverse approaches, each with advantages and limitations depending on various factors. For HD maps, modular systems excel, while end-to-end methods dominate mapless scenarios. However, few leverage the strengths of both. This paper innovates by proposing a hyb...

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Bibliographic Details
Main Authors: Luis Alberto Rosero, Iago Pachêco Gomes, Júnior Anderson Rodrigues da Silva, Carlos André Przewodowski, Denis Fernando Wolf, Fernando Santos Osório
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Sensors
Subjects:
autonomous driving
hybrid architecture
modular
end-to-end
path planning
CARLA simulator
Online Access:https://www.mdpi.com/1424-8220/24/7/2097

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