Skip to main content

Autonomous Vehicle Communication in V2X Network with LoRa Protocol

  • Conference paper
  • First Online:
Smart Computing and Communication (SmartCom 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11910))

Included in the following conference series:

Abstract

The weakness of short-range wireless signal and security issues will make a bad effect on the communication in Vehicle-to-Vehicle or Vehicle-to-Infrastructure (V2X). In this study, we proposed a system, based on Long Range (LoRa) protocol and Long Range Wide-Area Network (LoRaWAN), to reduce the latency of communication and minimize the data size in V2X networks. Through the experiment, it shows that the proposed system can enhance the overall performance and reduce the latency in V2X networks. Moreover, the security of transmitting data is increased.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Qiu, H., Noura, H., Qiu, M., Ming, Z., Memmi, G.: A user-centric data protection method for cloud storage based on invertible DWT. IEEE Trans. Cloud Comput. (2019)

    Google Scholar 

  2. Haidar, F., Kaiser, A., Lonc, B.: On the performance evaluation of vehicular PKI protocol for V2X communications security. In: Proceeding of IEEE 86th Vehicular Technology Conference (VTC-Fall) (2017)

    Google Scholar 

  3. Petit, J., Shladover, S.: Potential cyber attacks on automated vehicles. IEEE Trans. Intell. Transp. Syst. 16(2), 546–556 (2015)

    Google Scholar 

  4. Lv, Y., Duan, Y., Kang, W., Li, Z., Wangi, F.: Traffic flow prediction with big data: a deep learning approach. IEEE Trans. Intell. Transp. Syst. 16(2), 865–873 (2015)

    Google Scholar 

  5. Qiu, H., Qiu, M., Lu, Z., Memmi, G.: An efficient key distribution system for data fusion in V2X heterogeneous networks. Inf. Fusion 50, 212–220 (2019)

    Article  Google Scholar 

  6. Kontzer, T.: Driving Change: Volvo’s “Drive Me” Project to Make Self-Driving Cars Synonymous with Safety (2016). https://blogs.nvidia.com/blog/2016/04/06/volvo-safety-self-driving/

  7. Wang, X., Mao, S., Gong, M.: An overview of 3GPP cellular vehicle-to-everything standards. GetMobile: Mob. Comput. Commun. 21(3), 19–25 (2017)

    Article  Google Scholar 

  8. Abboud, K., Omar, H., Zhuang, W.: Interworking of DSRC and cellular network technologies for V2X communications: a survey. IEEE Trans. Veh. Technol. 65(12), 9457–9470 (2016)

    Article  Google Scholar 

  9. Atallah, R., Khabbaz, M., Assi, C.: Vehicular networking: a survey on spectrum access technologies and persisting challenges. Veh. Commun. 2(3), 125–149 (2015)

    Google Scholar 

  10. MacHardy, Z., Khan, A., Obana, K., Iwashina, S.: V2X access technologies: regulation, research, and remaining challenges. IEEE Commun. Surv. Tutorials 20(3), 1858–1877 (2018)

    Article  Google Scholar 

  11. Feng, Y., Hu, B., Hao, H., Gao, Y., Li, Z.: Design of distributed cyber-physical systems for connected and automated vehicles with implementing methodologies. IEEE Trans. Ind. Inf. 14(9), 4200–4211 (2018)

    Article  Google Scholar 

  12. Li, L., Ota, K., Dong, M.: Humanlike driving: empirical decision-making system for autonomous vehicles. IEEE Trans. Veh. Technol. 67(8), 6814–6823 (2018)

    Article  Google Scholar 

  13. Zhao, Z., Chen, W., Wu, X., Peter, C.Y., Chen, P.C., Liu, J.: LSTM network: a deep learning approach for short-term traffic forecast. IET Intell. Transp. Syst. 11(2), 68–75 (2017)

    Article  Google Scholar 

  14. Lukosevicius, M., Jaeger, H.: Reservoir computing approaches to recurrent neural network training. Comput. Sci. Rev. 3(3), 127–149 (2009)

    Article  Google Scholar 

  15. Guo, L., et al.: A secure mechanism for big data collection in large scale internet of vehicle. IEEE Internet of Things J. 4(2), 601–610 (2017)

    Article  Google Scholar 

  16. Pacheco, J., Hariri, S.: IoT security framework for smart cyber infrastructures. In: IEEE International Workshops on Foundations and Applications of Self* Systems, pp. 242–247. IEEE, September 2016

    Google Scholar 

  17. Lloret, J., Tomas, J., Canovas, A., Parra, L.: An integrated IoT architecture for smart metering. IEEE Commun. Mag. 54(12), 50–57 (2016)

    Article  Google Scholar 

  18. Sornin, N., Luis, M., Eirich, T., Kramp, T., Hersent, O.: LoRaWAN Specification, pp. 1–82, January 2015

    Google Scholar 

  19. “LoRaWAN Network Server Demonstration: Gateway to Server Interface Definition,” Semtech, Application note, pp. 1–19, July 2015

    Google Scholar 

  20. Augustin, A., Yi, J., Clausen, T., Townsley, W.: A study of LoRa: long range & low power networks for the Internet of Things. Sensors 16(9), 1466 (2016)

    Article  Google Scholar 

Download references

Acknowledgment

This work is supported in by the National Natural Science Foundation of China (No. 61728303) and the Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China (No. ICT1800417).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Meikang Qiu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Cheung, Y., Qiu, M., Liu, M. (2019). Autonomous Vehicle Communication in V2X Network with LoRa Protocol. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2019. Lecture Notes in Computer Science(), vol 11910. Springer, Cham. https://doi.org/10.1007/978-3-030-34139-8_40

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-34139-8_40

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34138-1

  • Online ISBN: 978-3-030-34139-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics