Transportation Data Fusion is a computational framework that integrates heterogeneous data sources from multiple transportation systems to generate a unified, more accurate, and comprehensive representation of traffic conditions, thereby enabling enhanced situational awareness and decision-making in intelligent transportation applications.
205
Publications
9K
Citations
703
Authors
313
Institutions
Publications per year
2017–2026
114
Publications
205
Big Data for Social Transportation
Xinhu Zheng, Wei Chen, Pu Wang et al. · IEEE Transactions on Intelligent Transportation Systems · 2015 · 248 citations
1–5 of 205
Authors
703
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- YL
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- LH
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1–5 of 703
Institutions
313
Central South University
Changsha, China
10 h-index
28 publications
1.5K citations
Chinese Academy of Sciences
Beijing, China
9 h-index
20 publications
3.6K citations
Beijing Jiaotong University
Beijing, China
8 h-index
18 publications
503 citations
Zhejiang University
Hangzhou, China
7 h-index
13 publications
550 citations
Shandong Institute of Automation
Jinan, China
7 h-index
15 publications
3.2K citations
University of Illinois Chicago
Chicago, United States
6 h-index
5 publications
214 citations
KTH Royal Institute of Technology
Stockholm, Sweden
5 h-index
10 publications
311 citations
Southeast University
Nanjing, China
5 h-index
20 publications
720 citations
1–8 of 313
Venues
- Transportation Research Part C Emerging Technologies
15 publications · 1.3K citations
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- IEEE Transactions on Intelligent Transportation Systems
12 publications · 1.6K citations
13
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- Transportation Research Record Journal of the Transportation Research Board
TRR · 9 publications · 227 citations
9
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- IEEE Access
5 publications · 193 citations
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- IET Intelligent Transport Systems
5 publications · 262 citations
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