Smart Transportation Systems: Architecture, Enabling Technologies, and Open Issues

Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

With the development of smart sensors, smart vehicles, and vehicular communication technologies, the smart transportation system is proposed and considered to be the future of the transportation critical infrastructure system, aiming to improve traffic efficiency, safety, and security. All vehicles and roadside infrastructures will be deployed with integrated smart sensors and communication units in order that traffic states can be measured and shared via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication networks. With the smart transportation system, diversified services can be provided to customers, including traffic and transportation management, safety management, and others. In addition, the optimal travel for users (e.g., drivers) can be achieved, travel safety can be realized, and road congestion can be reduced in the smart transportation system. Nonetheless, security issues, including illegal access, attacks, unauthorized information sharing, and so on, become challenging in the smart transportation system. In order to understand smart transportation systems such that techniques can be designed to make them secure, this chapter conducts a review of smart transportation systems with respect to architecture, enabling technologies, and open issues. To be specific, a three-layer architecture is first presented for the smart transportation system, including the physical layer, communication layer, and service layer. Then, the detailed components and enabling technologies in each layer are described. Finally, we present some open issues related to security, big data, performance, and evaluation platforms in the smart transportation system.

Notes

Acknowledgements

This work was supported in part by US National Science Foundation (NSF) under grant: CNS 1350145 and USM Wilson H. Elkins Professorship fund. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the agencies.

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Copyright information

© The Author(s) 2017

Authors and Affiliations

  1. 1.Towson UniversityTowsonUSA
  2. 2.Xi’an Jiaotong UniversityXi’anPeople’s Republic of China

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