Skip to main content

Non-stopping Junctions via Traffic Scheduling

  • 188 Accesses

Part of the Lecture Notes in Computer Science book series (LNCS,volume 13301)


Emergency situations involve massive movements of (logistic and units) platoons to and from focal locations. Platoons may move in different directions and can be blocking each other in junctions causing even deadlocks. The possibility to minimize the delay in junctions, in particular, non-stopping and waiting for a (virtual) green light, may avoid the chain phenomena of cascade stopping and cascade starting to move again when all cars wait for the car in front of them to gain enough velocity. The remote driving system is an opportunity to stream all platoons driving in different directions without stopping, by spacing vehicles to allow conflicting traffic to move in the space between vehicles. In this work, we present briefly the algorithms to identify and control platoons and focus on the real-time junction scheduling towards the non-stopping junction(s). We demonstrate the results that imply road safety as actions are remotely controlled, by using the SUMO simulator [7].


  • Scheduling
  • Platoon
  • Junction
  • Virtual traffic light
  • Autonomous vehicles

This research was partially funded by the Andromeda MAGNET Consortium, by the Lynne and William Frankel Center for Computer Science and by Rita Altura chair in computer science.

This is a preview of subscription content, access via your institution.

Buying options

USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-031-07689-3_19
  • Chapter length: 12 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
USD   79.99
Price excludes VAT (USA)
  • ISBN: 978-3-031-07689-3
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   99.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.


  1. Demonstration video (2022).

  2. Bazzi, A., Zanella, A., Masini, B.M., Pasolini, G.: A distributed algorithm for virtual traffic lights with IEEE 802.11p. In: European Conference on Networks and Communications, EuCNC 2014, Bologna, Italy, 23–26 June 2014. pp. 1–5. IEEE (2014)

    Google Scholar 

  3. Conceição, H., Ferreira, M., Steenkiste, P.: Virtual traffic lights in partial deployment scenarios. In: 2013 IEEE Intelligent Vehicles Symposium (IV), Gold Coast City, Australia, 23–26 June 2013, pp. 988–993. IEEE (2013)

    Google Scholar 

  4. Dolev, S., Gudes, E., Yair, H.: Automatic real time platoon formation using the road graph. In: 2021 IEEE 20th International Symposium on Network Computing and Applications (NCA), November 2021, pp. 1–4. IEEE Computer Society, Los Alamitos, CA, USA (2021)

    Google Scholar 

  5. Dolev, S., Kranakis, E., Krizanc, D.: Baked-potato routing. J. Algorithms 30(2), 379–399 (1999)

    MathSciNet  CrossRef  Google Scholar 

  6. Li, N., Chen, S., Zhu, J., Sun, D.J.: A platoon-based adaptive signal control method with connected vehicle technology. Comput. Intell. Neurosci. 2020, 2764576:1–2764576:10 (2020)

    Google Scholar 

  7. Lopez, P.A., et al.: Microscopic traffic simulation using sumo. In: The 21st IEEE International Conference on Intelligent Transportation Systems. IEEE (2018)

    Google Scholar 

  8. Ng, K.M., Reaz, M.B.I.: Platoon interactions and real-world traffic simulation and validation based on the LWR-IM. PLoS ONE 11(1), 1–17 (2016)

    Google Scholar 

  9. Olaverri-Monreal, C., Gomes, P., Silvéria, M.K., Ferreira, M.: In-vehicle virtual traffic lights: a graphical user interface. In: 7th Iberian Conference on Information Systems and Technologies, CISTI 2012, pp. 1–6 (2012)

    Google Scholar 

  10. Vial, J.J.B., Devanny, W.E., Eppstein, D., Goodrich, M.T.: Scheduling autonomous vehicle platoons through an unregulated intersection. In: Goerigk, M., Werneck, R. (eds.) 16th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems, ATMOS 2016. OpenAccess Series in Informatics (OASIcs), vol. 54, pp. 5:1–5:14. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany (2016)

    Google Scholar 

  11. Viriyasitavat, W., Roldan, J.M., Tonguz, O.K.: Accelerating the adoption of virtual traffic lights through policy decisions. In: International Conference on Connected Vehicles and Expo, ICCVE 2012, Las Vegas, NV, USA, pp. 443–444, 2–6 December 2013. IEEE (2013)

    Google Scholar 

  12. Zhao, W., Ngoduy, D., Shepherd, S., Liu, R., Papageorgiou, M.: A platoon based cooperative eco-driving model for mixed automated and human-driven vehicles at a signalised intersection. Transp. Res. Part C Emerg. Technol. 95, 802–821 (2018)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Hannah Yair .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Dolev, S., Gudes, E., Yair, H. (2022). Non-stopping Junctions via Traffic Scheduling. In: Dolev, S., Katz, J., Meisels, A. (eds) Cyber Security, Cryptology, and Machine Learning. CSCML 2022. Lecture Notes in Computer Science, vol 13301. Springer, Cham.

Download citation

  • DOI:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-07688-6

  • Online ISBN: 978-3-031-07689-3

  • eBook Packages: Computer ScienceComputer Science (R0)