Parallel Transportation in TransVerse: From Foundation Models to DeCAST-Reference-Cited by-同舟云学术

Parallel Transportation in TransVerse: From Foundation Models to DeCAST

Author:

Zhao Chen¹,Wang Xiao²^ORCID,Lv Yisheng¹^ORCID,Tian Yonglin³^ORCID,Lin Yilun⁴^ORCID,Wang Fei-Yue⁵^ORCID

Affiliation:

1. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China

2. School of Artificial Intelligence, Anhui University, Hefei, China

3. State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

4. Shanghai AI Laboratory, Shanghai, China

5. State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing, China

Funder

Key-Area Research and Development Program of Guangdong Province

Key Research and Development Program 2020 of Guangzhou

National Natural Science Foundation of China

Science and Technology Development Fund, Macau SAR

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

Reference159 articles.

3. DRACULA: Dynamic route assignment combining user learning and microsimulation;liu;Proc 23rd Eur Transp Forum,1995

4. Traffic flow prediction with big data: A deep learning approach;lv;IEEE Trans Intell Transp Syst,2015

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