Skip to main content

Intersection Traffic Control Method Considering Remaining Distance to Destination and Congestion of Next Road Segment

  • Conference paper
  • First Online:
Advances on Broadband and Wireless Computing, Communication and Applications (BWCCA 2018)

Abstract

In intelligent transportation systems (ITS), researches aimed to alleviate congestion and improve traffic flow are being conducted. This paper proposes intersection traffic control method considering remaining distance to destination and congestion of next road segment (ICDIC) for the purpose of improving the traffic capacity of the entire areas. In ICDIC, each vehicle transmits information about the remaining travel distance to the final destination and the next driving lane to roadside unit (RSU) installed at the intersection of the destination. The RSU classifies the vehicles for each driving lane based on the received information. The RSU calculates intersection traffic priority calculation for each vehicle based on the length of the remaining travel distance and the low congestion degree of the destination lane, and the priority of each lane are calculated by taking the average for each lane for each lane. For these processes, traffic capacity can be improved throughout the area.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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

Similar content being viewed by others

References

  1. Younes, M.B., Boukerche, A.: Intelligent traffic light controlling algorithms using vehicular networks. IEEE Trans. Veh. Technol. 65(8), 5887–5899 (2016)

    Article  Google Scholar 

  2. Xiao, Z., Xiao, Z., Wang, D., Li, X.: An intelligent traffic light control approach for reducing vehicles CO2 emissions in VANET. In: 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 2070–2075, August 2015

    Google Scholar 

  3. Suramardhana, T.A., Jeong, H.Y.: A driver-centric green light optimal speed advisory (DC-GLOSA) for improving road traffic congestion at urban intersections. In: 2014 IEEE Asia Pacific Conference on Wireless and Mobile, pp. 304–309, August 2014

    Google Scholar 

  4. Ding, J., Xu, H., Hu, J., Zhang, Y.: Centralized cooperative intersection control under automated vehicle environment. In: 2017 IEEE Intelligent Vehicles Symposium (IV), pp. 972–977, June 2017

    Google Scholar 

  5. Neudecker, T., An, N., Hartenstein, H.: Verification and evaluation of fail-safe virtual traffic light applications. In: 2013 IEEE Vehicular Networking Conference, pp. 158–165, December 2013

    Google Scholar 

  6. Lemos, L.L., Pasin, M.: Intersection control in transportation networks: opportunities to minimize air pollution emissions. In: 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), pp. 1616–1621, November 2016

    Google Scholar 

  7. Baselt, D., Knorr, F., Scheuermann, B., Schreckenberg, M., Mauve, M.: Merging lanes-fairness through communication. Veh. Commun. 1(2), 97–104 (2014). http://www.sciencedirect.com/science/article/pii/S2214209614000229

    Article  Google Scholar 

  8. Pasin, M., Scheuermann, B., Moura, R.F.d.: VANET-based intersection control with a throughput/fairness tradeoff. In: 2015 8th IFIP Wireless and Mobile Networking Conference (WMNC), pp. 208–215, October 2015

    Google Scholar 

  9. Yanagida, R., Obara, K., Ogawa, K., Shigeno, H.: An analysis of road maps based on voronoi diagram for vehicular broadcast. In: 2015 10th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA), pp. 150–156, November 2015

    Google Scholar 

  10. Mordechai, H., Patrick, W.: OpenStreetMap: user-generated street maps. IEEE Perv. Comput. 7(4), 12–18 (2008)

    Article  Google Scholar 

  11. Krajzewicz, D., Erdmann, J., Behrisch, M., Bieker, L.: Recent development and applications of SUMO - Simulation of Urban MObility. Int. J. Adv. Syst. Meas. 5(3&4), 128–138 (2012)

    Google Scholar 

Download references

Acknowledgments

This work was supported by JSPS KAKENHI Grant Number 16H02811.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Yusuke Okabe , Minato Dan or Hiroshi Shigeno .

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

Okabe, Y., Dan, M., Shigeno, H. (2019). Intersection Traffic Control Method Considering Remaining Distance to Destination and Congestion of Next Road Segment. In: Barolli, L., Leu, FY., Enokido, T., Chen, HC. (eds) Advances on Broadband and Wireless Computing, Communication and Applications. BWCCA 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-030-02613-4_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-02613-4_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02612-7

  • Online ISBN: 978-3-030-02613-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics