Image-based traffic signal control via world models-Reference-Cited by-同舟云学术

Image-based traffic signal control via world models

Published:2022-12 Issue:12 Volume:23 Page:1795-1813
ISSN:2095-9184
Container-title:Frontiers of Information Technology & Electronic Engineering
language:en
Short-container-title:Front Inform Technol Electron Eng

Author:

Dai Xingyuan^ORCID,Zhao Chen,Wang Xiao,Lv Yisheng,Lin Yilun,Wang Fei-Yue^ORCID

Publisher

Zhejiang University Press

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing

Link

https://link.springer.com/content/pdf/10.1631/FITEE.2200323.pdf

Reference39 articles.

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2. Bertsekas D, 2021. Multiagent reinforcement learning: roll-out and policy iteration. IEEE/CAA J Autom Sin, 8(2):249–272. https://doi.org/10.1109/JAS.2021.1003814

3. Dai XY, Fu R, Zhao EM, et al., 2019. DeepTrend 2.0: a light-weighted multi-scale traffic prediction model using detrending. Transp Res Part C Emerg Technol, 103:142–157. https://doi.org/10.1016/j.trc.2019.03.022

4. Guo QQ, Li L, Ban XG, 2019. Urban traffic signal control with connected and automated vehicles: a survey. Transp Res Part C Emerg Technol, 101:313–334. https://doi.org/10.1016/j.trc.2019.01.026

5. Hafner D, Lillicrap T, Fischer I, et al., 2019. Learning latent dynamics for planning from pixels. Proc 36th Int Conf on Machine Learning, p.2555–2565.

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