Mandatory Lane-Changing Decision-Making in Dense Traffic for Autonomous Vehicles based on Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Mandatory Lane-Changing Decision-Making in Dense Traffic for Autonomous Vehicles based on Deep Reinforcement Learning

Published:2022-10-28 Issue: Volume: Page:
ISSN:
Container-title:2022 6th CAA International Conference on Vehicular Control and Intelligence (CVCI)
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Author:

Gu Yuxiao¹,Yuan Kang²,Yang Shuo¹,Ning Minghao³,Huang Yanjun¹

Affiliation:

1. School of Automotive Studies, Tongji University,Shanghai,China

2. College of Electronic and Information Engineering, Tongji University,Shanghai,China

3. University of Waterloo,Department of Mechanical and Mechatronics Engineering,Waterloo,ON,Canada

Funder

Science and Technology Commission of Shanghai Municipality

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9964479/9964492/09964906.pdf?arnumber=9964906

Reference25 articles.

1. Gated branch neural network for mandatory lane changing suggestion at the on‐ramps of highway

2. Forecasting Freeway On-Ramp Lane-Changing Behavior Based on GRU

3. Comparative evaluation of adaptive fuzzy inference system and adaptive neuro-fuzzy inference system for mandatory lane changing decisions on freeways;vechione;Journal of Intelligent Transportation Systems,2021

4. Game theoretic model for lane changing: Incorporating conflict risks

5. A Game Theory-based Model Predictive Controller For Mandatory Lane Change Of Multiple Vehicles

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