Simulation of Decision-making Method for Vehicle Longitudinal Automatic Driving Based on Deep Q Neural Network-Reference-Cited by-同舟云学术

Simulation of Decision-making Method for Vehicle Longitudinal Automatic Driving Based on Deep Q Neural Network

Published:2020-07-22 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2020 the 7th International Conference on Automation and Logistics (ICAL)
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Author:

Cheng Xu¹,Jiang Rong¹,Chen Rongjie¹

Affiliation:

1. China automotive technology and research center Co., Ltd. Tianjin, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3412953.3412963

Reference24 articles.

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2. Gao Zhenhai Yan Wei Wang Jun and HuHongyu. 2015. A Mode Switching Logic Imitating Human Driver for Adaptive Cruise Control System. 2015CG-IVT010. 483--486. Gao Zhenhai Yan Wei Wang Jun and HuHongyu. 2015. A Mode Switching Logic Imitating Human Driver for Adaptive Cruise Control System. 2015CG-IVT010. 483--486.

3. Desirability of advanced driver assistance from road safety perspective: the case of ISA

4. Review on the research of longitudinal motion control for intelligent driving vehicles;Yufeng Luo;J. Automobile Applied Technology.,2018

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2. Generalized Single-Vehicle-Based Graph Reinforcement Learning for Decision-Making in Autonomous Driving;Sensors;2022-06-29

3. Driver-like decision-making method for vehicle longitudinal autonomous driving based on deep reinforcement learning;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2021-12-08