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Open Access

Shaping the future of the application of quantum computing in intelligent transportation system

Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai 200444, China
Department of Information Engineering, Gannan University of Science and Technology, Ganzhou 341000, China
Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
Show Author Information

Abstract

The intelligent transportation system (ITS) integrates a variety of advanced science and technology to support and monitor road traffic systems and accelerate the urbanization process of various countries. This paper analyzes the shortcomings of ITS, introduces the principle of quantum computing and the performance of universal quantum computer and special-purpose quantum computer, and shows how to use quantum advantages to improve the existing ITS. The application of quantum computer in transportation field is reviewed from three application directions: path planning, transportation operation management, and transportation facility layout. Due to the slow development of the current universal quantum computer, the D-Wave quantum machine is used as a breakthrough in the practical application. This paper makes it clear that quantum computing is a powerful tool to promote the development of ITS, emphasizes the importance and necessity of introducing quantum computing into intelligent transportation, and discusses the possible development direction in the future.

Keywords

quantum computingintelligent transportationquantum annealingD-wave quantum computer

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Intelligent and Converged Networks
Volume 2 Issue 4,
December 2021
Pages 259-276
DOI: 10.23919/ICN.2021.0019
Cite this article:
Wang S, Pei Z, Wang C, et al. Shaping the future of the application of quantum computing in intelligent transportation system. Intelligent and Converged Networks, 2021, 2(4): 259-276. https://doi.org/10.23919/ICN.2021.0019

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Received: 15 November 2021
Accepted: 16 December 2021
Published: 30 December 2021
© All articles included in the journal are copyrighted to the ITU and TUP.

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