Design of Intelligent Transportation Control System Based on Blockchain Technology


Xia Wei, Journal of Information Processing Systems Vol. 18, No. 6, pp. 763-769, Dec. 2022  

https://doi.org/10.3745/JIPS.04.0259
Keywords: Blockchain Technology, genetic algorithm, objective function, Transportation Control
Fulltext:

Abstract

Transportation allocation requires information such as storage location and order information. In order to guarantee the safe transmission and real-time sharing of information in all links, an intelligent transportation control system based on blockchain technology is designed. Firstly, the technical architecture of intelligent transportation information traceability blockchain and the overall architecture of intelligent transportation control system were designed. Secondly, the transportation management demand module and storage demand management module were designed, and the control process of each module was given. Then, the type of intelligent transportation vehicle was defined, the objective function of intelligent transportation control was designed, and the objective function of intelligent transportation control was constructed. Finally, the intelligent transportation control was realized by genetic algorithm. It was found that when the transportation order volume was 50×103, and the CPU occupancy of the designed system was only 11.8%. The reliability attenuation of the code deletion scheme was lower, indicating better performance of the designed system.


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Cite this article
[APA Style]
Wei, X. (2022). Design of Intelligent Transportation Control System Based on Blockchain Technology. Journal of Information Processing Systems, 18(6), 763-769. DOI: 10.3745/JIPS.04.0259.

[IEEE Style]
X. Wei, "Design of Intelligent Transportation Control System Based on Blockchain Technology," Journal of Information Processing Systems, vol. 18, no. 6, pp. 763-769, 2022. DOI: 10.3745/JIPS.04.0259.

[ACM Style]
Xia Wei. 2022. Design of Intelligent Transportation Control System Based on Blockchain Technology. Journal of Information Processing Systems, 18, 6, (2022), 763-769. DOI: 10.3745/JIPS.04.0259.