A Deep Reinforcement Learning Approach for Efficient, Safe and Comfortable Driving

A Deep Reinforcement Learning Approach for Efficient, Safe and Comfortable Driving

Sensing, computing, and communication advancements allow vehicles to generate and collect massive amounts of data on their state and surroundings. Such richness of information fosters data-driven decision-making model development that considers the vehicle’s environmental context. We propose a data-...

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Bibliographic Details
Main Authors: Dinesh Cyril Selvaraj, Shailesh Hegde, Nicola Amati, Francesco Deflorio, Carla Fabiana Chiasserini
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Applied Sciences
Subjects:
connected vehicles
vehicle dynamics
adaptive cruise control
traffic simulation
machine learning
Online Access:https://www.mdpi.com/2076-3417/13/9/5272

Internet

https://www.mdpi.com/2076-3417/13/9/5272

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