Multi-Task End-to-End Self-Driving Architecture for CAV Platoons

Multi-Task End-to-End Self-Driving Architecture for CAV Platoons

Connected and autonomous vehicles (CAVs) could reduce emissions, increase road safety, and enhance ride comfort. Multiple CAVs can form a CAV platoon with a close inter-vehicle distance, which can further improve energy efficiency, save space, and reduce travel time. To date, there have been few det...

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Bibliographic Details
Main Authors: Sebastian Huch, Aybike Ongel, Johannes Betz, Markus Lienkamp
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Sensors
Subjects:
connected and autonomous vehicles
artificial neural networks
end-to-end learning
multi-task learning
urban vehicle platooning
simulation
Online Access:https://www.mdpi.com/1424-8220/21/4/1039

Internet

https://www.mdpi.com/1424-8220/21/4/1039

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