The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Towards blockchain-based intelligent transportation systems
Abstract
Blockchain, widely known as one of the disruptive technologies emerged in recent years, is experiencing rapid development and has the full potential of revolutionizing the increasingly centralized intelligent transportation systems (ITS) in applications. Blockchain can be utilized to establish a secured, trusted and decentralized autonomous ITS ecosystem, creating better usage of the legacy ITS infrastructure and resources, especially effective for crowdsourcing technology. This paper conducts a preliminary study of Blockchain-based ITS (B2ITS). We outline an ITS-oriented, seven-layer conceptual model for blockchain, and on this basis address the key research issues in B2ITS. We consider that blockchain is one of the secured and trusted architectures for building the newly developed parallel transportation management systems (PtMS) , and thereby discuss the relationship between B2ITS and PtMS. Finally, we present a case study for blockchain-based realtime ride-sharing services. In our viewpoint, B2ITS represents the future trend of ITS research and practice, and this paper is aimed at stimulating further effort and providing helpful guidance and reference for future research works.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Some of them propose new platforms just at a concept level [45,51,52,75,77,83,84,88,89,91], some of them present proofs of their concepts [76,79,81], and only three of them present a real implementation based on real blockchains: [78,80,82].”
From A Review of Blockchain-Based Systems in Transportation (2019) · cites this paper as [52]
In the citing paper
“Lack of trust among the ITS actors”
From A Review of Blockchain-Based Systems in Transportation (2019) · cites this paper as [52]
Citations
Cites
Bitcoin: A Peer-to-Peer Electronic Cash SystemPreprint
Nakamoto, S. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3440802 · Cited by 14,677
(2015) · Cited by 3,471
The internet of things: a survey
Li, S., Xu, L. D., & Zhao, S. (2014) · Information Systems Frontiers · doi:10.1007/s10796-014-9492-7 · Cited by 2,569
Data-Driven Intelligent Transportation Systems: A Survey
Zhang, J., Wang, F.-Y., Wang, K., Lin, W.-H., Xu, X., & Chen, C. (2011) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2011.2158001 · Cited by 1,817
Self-citationWang, F. (2010) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2010.2060218 · Cited by 859
Self-citationParallel system methods for management and control of complex systems
Fei-yue, W. (2004) · Kongzhi yu juece · Cited by 273
Agent-based control for networked traffic management systems
Wang, F. (2005) · IEEE Intelligent Systems · doi:10.1109/mis.2005.80 · Cited by 220
Self-citationIntelligent transportation spaces: vehicles, traffic, communications, and beyond
Qu, F., Wang, F., & Yang, L. (2010) · IEEE Communications Magazine · doi:10.1109/mcom.2010.5621980 · Cited by 219
Self-citationSmart Cars on Smart Roads: An IEEE Intelligent Transportation Systems Society Update
Wang, F., Zeng, D. D., & Yang, L. (2006) · IEEE Pervasive Computing · doi:10.1109/mprv.2006.84 · Cited by 146
Self-citationDynaCAS: Computational Experiments and Decision Support for ITS
Zhang, N., Wang, F.-Y., Zhu, F., Zhao, D., & Tang, S. (2008) · IEEE Intelligent Systems · doi:10.1109/mis.2008.101 · Cited by 134
Self-citationEfficient decentralized consensus protocols
Lakshman, T. V., & Agrawala, A. K. (1986) · IEEE Transactions on Software Engineering · doi:10.1109/tse.1986.6312956 · Cited by 81
A Bibliographic Analysis of the IEEE Transactions on Intelligent Transportation Systems Literature
Li, L., Li, X., Li, Z., Zeng, D. D., & Scherer, W. T. (2010) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2010.2049890 · Cited by 41
Research Collaboration and ITS Topic Evolution: 10 Years at T-ITS
Li, L., Li, X., Cheng, C., Chen, C., Ke, G., Zeng, D. D., & Scherer, W. T. (2010) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2010.2059070 · Cited by 33
Developing Parallel Control and Management for Urban Traffic Systems
Kong, Q., Li, L., Yan, B., Lin, S., Zhu, F., & Xiong, G. (2013) · IEEE Intelligent Systems · doi:10.1109/mis.2013.59 · Cited by 23
The ISO reference model entities
Modiri, N. (1991) · IEEE Network · doi:10.1109/65.93182 · Cited by 22
Autonomous Decentralized Traffic Management System
Kitahara, F., Kera, K., & Bekki, K. (2002) · doi:10.1109/iwads.2000.880891 · Cited by 21
Mori, K. (2001) · Kluwer international series in engineering and computer science · doi:10.1007/978-1-4615-1391-9_5 · Cited by 18
Fei-yue, W. (2004) · Fuza xitong yu fuzaxing kexue · Cited by 7
Flagged first, then by citations
Research works printed but not linked: 14
- 0, Arcade city website
- 0, La'zooz website
- lv, 2009, Computational experiements of evaluating road network traffic conditions based on artificial transportation systems, Journal of Jilin University (Engineering and Technology Edition), 39, 87
- yuan, 2016, Blockchain: the state of the art and future trends, ACTA Automatica Sinica, 42, 481
- wang, 2004, Computational theory and methods for complex systems, China Basic Science, 6, 3
- 2015, Blockchain technology and Internet of things
- wang, 2004, Artificial societies, computational experiments, and parallel systems: an investigation on computational theory of complex socialeconomic systems, Complex Systems and Complexity Science, 1, 25
- 0, Ethereum website
- antonopoulos, 2014, Mastering Bitcoin
- 2015, IBM article
- larimer, 2013, Transactions as proof-of-stake
- 2015, Bitcoinmining article
- larimer, 2014, Delegated proof-of-stake white paper
- 0, Online Report
Cited by
Sorted by citations
Casino, F., Dasaklis, T. K., & Patsakis, C. (2018) · Telematics and Informatics · doi:10.1016/j.tele.2018.11.006 · Cited by 2,954
Designing microgrid energy markets
Mengelkamp, E., Gärttner, J., Rock, K., Kessler, S., Orsini, L., & Weinhardt, C. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.06.054 · Cited by 1,596
Wang, Y., Han, J. H., & Beynon‐Davies, P. (2018) · Supply Chain Management An International Journal · doi:10.1108/scm-03-2018-0148 · Cited by 1,388
Blockchain-Enabled Smart Contracts: Architecture, Applications, and Future Trends
Wang, S., Ouyang, L., Yuan, Y., Ni, X., Han, X., & Wang, F. (2019) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2019.2895123 · Cited by 1,244
Self-citationModeling the blockchain enabled traceability in agriculture supply chain
Kamble, S., Gunasekaran, A., & Sharma, R. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.05.023 · Cited by 881
Metadata
- Authors
- Yuan, Y., & Wang, F.-Y.
- Affiliations
- Chinese Academy of Sciences (CN)
- National University of Defense Technology (CN)
- Venue
- 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)
- Publisher
- IEEE
- Published
- 2016-11
- Pages
- 2663-2668
- OpenAlex
- W2566758857
- Cited by
- 671
- References
- 18
- Citations by year
- 2026: 5 · 2025: 29 · 2024: 41 · 2023: 70 · 2022: 83 · 2021: 142 · 2020: 113 · 2019: 94 · 2018: 77 · 2017: 16 · 2016: 1
- FWCI
- 53.25
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Intelligent Transportation Systems (ITSC) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Keywords
- blockchain, intelligent transportation systems, autonomous decentralized systems, crowdsourcing, ride-sharing, trust and security
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
