Acceleration control strategy for Battery Electric Vehicle based on Deep Reinforcement Learning in V2V driving-Reference-Cited by-同舟云学术

Acceleration control strategy for Battery Electric Vehicle based on Deep Reinforcement Learning in V2V driving

Published:2022-06-15 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Transportation Electrification Conference & Expo (ITEC)
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Author:

Acquarone Matteo¹,Borneo Angelo²,Misul Daniela Anna¹

Affiliation:

1. Politecnico di Torino Center for Automotive Research and Sustainable Mobility (CARS), Politecnico di Torino,Department of Energetic (DENERG),Torino,IT

2. Politecnico di Torino MCA Engineering s.r.l., Torino,Department of Energetic (DENERG),Torino,IT

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9813698/9813746/09813785.pdf?arnumber=9813785

Reference15 articles.

1. Cooperative Adaptive Cruise Control: A Reinforcement Learning Approach

2. A Reinforcement Learning-Based Vehicle Platoon Control Strategy for Reducing Energy Consumption in Traffic Oscillations

3. Safe, Efficient, and Comfortable Velocity Control based on Reinforcement Learning for Autonomous Driving;zhu,2019

4. Data on Cars used for Testing Fuel Economy,0

5. Continuous control with deep reinforcement learning;lillicrap,2015

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1. Enhancing Longitudinal Velocity Control With Attention Mechanism-Based Deep Deterministic Policy Gradient (DDPG) for Safety and Comfort;IEEE Access;2024

2. Platooning Cooperative Adaptive Cruise Control for Dynamic Performance and Energy Saving: A Comparative Study of Linear Quadratic and Reinforcement Learning-Based Controllers;Applied Sciences;2023-09-19

3. Cooperative Adaptive Cruise Control Based on Reinforcement Learning for Heavy-Duty BEVs;IEEE Access;2023