Skip to main content

New Advances in Intelligent Intersection Management with Connected and Automated Vehicle Technology

  • Conference paper
  • First Online:
  • 1161 Accesses

Part of the book series: Lecture Notes in Mobility ((LNMOB))

Abstract

Considerable research studies coupled with several deployment projects have been conducted recently to investigate potential effects of different cooperative automation technologies in controlling signalized junctions. The focus has been on how vehicles and infrastructure can cooperate toward safer and more efficient intersection operations. In this chapter, a brief review of some ongoing research projects as well as real world implementations that were presented during the Automated Vehicles Symposium (AVS) 2018 are discussed. The review includes the specifications of the projects and the challenges in implementation of the new technology. Three of the near future possible deployments are presented as well.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

References

  1. University of Arizona, University of California PATH Program, Savari Networks, Inc., Econolite, MMITSS – Phase II: System Development, Deployment and Field Test – Final Report (2016). http://www.cts.virginia.edu/wp-content/uploads/2014/04/53-MMITSS-Phase-2-Final-Report-FINAL-092520161.pdf

  2. Feng, Y., Head, K.L., Khoshmagham, S., Zamanipour, M.: A real-time adaptive signal control in a connected vehicle environment. Transp. Res. Part C: Emerg. Technol. 55, 460–473 (2015)

    Article  Google Scholar 

  3. Zamanipour, M., Head, K.L., Feng, Y., Khoshmagham, S.: Efficient priority control model for multimodal traffic signals. Transp. Res. Rec.: J. Transp. Res. Board 2557, 86–99 (2016)

    Article  Google Scholar 

  4. Beak, B., Zamanipour, M., Head, K.L., Leonard, B.: Peer-to-peer priority signal control strategy in a connected vehicle environment. Transp. Res. Rec.: J. Transp. Res. Board 2672, 15–26 (2018)

    Article  Google Scholar 

  5. Ahn, K., Rakha, H.A., Kang, K., Vadakpat, G.: Multimodal intelligent traffic signal system simulation model development and assessment. Transp. Res. Rec.: J. Transp. Res. Board 2558, 92–102 (2016)

    Article  Google Scholar 

  6. Zamanipour, M., Head, L., Ding, J.: Priority system for multimodal traffic signal control. In: Presented at the Transportation Research Board 93rd Annual Meeting (2014)

    Google Scholar 

  7. Leonard, B.: Strong signal; Utah breaks new ground with connected vehicles. https://www.roadsbridges.com/strong-signal

  8. SPaT challenge overview (2018). https://transportationops.org/spatchallenge

  9. Hartman, K.: Connected Vehicle Pilot Deployment Program. U.S. Department of Transportation (2018). https://its.dot.gov/pilots/

  10. Li, Z., Elefteriadou, L., Ranka, S.: Signal control optimization for automated vehicles at isolated signalized intersections. Transp. Res. Part C: Emerg. Technol. 49, 1–18 (2014)

    Article  Google Scholar 

  11. Pourmehrab, M., Elefteriadou, L., Ranka, S., Martin-Gasulla, M.: Optimizing signalized intersections performance under conventional and automated vehicles traffic. arXiv e-prints arXiv:1707.01748 (2017)

  12. Omidvar, A., Pourmehrab, M., Emami, P., Kiriazes, R., Esposito, J.C., Letter, C., Elefteriadou, L., Crane III, C.D., Ranka, S.: Deployment and testing of optimized autonomous and connected vehicle trajectories at a closed-course signalized intersection. Transp. Res. Rec.: J. Transp. Res. Board 2672(19), 45–54 (2018)

    Article  Google Scholar 

  13. Quain, J.R.: With cameras that know dogs from Dodges, Honda is making intersections safer, Digital Trends (2018). https://www.digitaltrends.com/cool-tech/honda-smart-intersection-marysville/

  14. Kan, X., Lu, X., Skabardonis, A.: Increasing freeway capacity by efficiently timing its nearby arterial traffic signals. Transp. Res. Rec.: J. Transp. Res. Board 2672(18), 27–34 (2018)

    Article  Google Scholar 

  15. Malikopoulos, A., Cassandras, C., Zhang, Y.A.: Decentralized energy-optimal control framework for connected automated vehicles at signal-free intersections, automatica. arXiv:1602.03786 (2017)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mehdi Zamanipour .

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

Zamanipour, M., Feng, Y., Vadakpat, G. (2019). New Advances in Intelligent Intersection Management with Connected and Automated Vehicle Technology. In: Meyer, G., Beiker, S. (eds) Road Vehicle Automation 6. AVS 2018. Lecture Notes in Mobility. Springer, Cham. https://doi.org/10.1007/978-3-030-22933-7_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-22933-7_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22932-0

  • Online ISBN: 978-3-030-22933-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics