Skip to main content
SpringerLink
Log in

Roads of the Future: A Survey on the Usage of Smart Traffic Sensor Networks in Autonomous Driving

  • Conference paper
  • First Online:
Soft Computing Applications (SOFA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1438))

Included in the following conference series:

  • 87 Accesses

Abstract

Recent transportation studies consider IoT (Internet of Things) as an important source of solutions to solve common road traffic issues like traffic congestion, reduction of travel times, etc. For this reason, road networks integrate many sensor networks that monitor real-time traffic conditions. Usually, the retrieved data are used in many cases as inputs for TMCs (Traffic Monitoring Centers) where intelligent algorithms are employed in the green interval setting for traffic signals. This paper conducts a study on the usage of these sensor networks as inputs also for autonomous driving systems. Furthermore, the paper identifies the main challenges in this direction on the basis of a comparison between approaches in this field. The final part of the paper aims to show a projection of a possible evolution of future trends in the use of road infrastructure sensors compared to the development of IoT.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
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. Ross, H.-L.: Automated driving and control. In: Safety for Future Transport and Mobility, pp. 307–390. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-54883-4_6

    Chapter  Google Scholar 

  2. Chai, Z., Nie, T., Becker, J.: Technologies for autonomous driving. In: Chai, Z., Nie, T., Becker, J. (eds.) Autonomous Driving Changes the Future, pp. 17–61. Springer Singapore, Singapore (2021). https://doi.org/10.1007/978-981-15-6728-5_2

    Chapter  Google Scholar 

  3. Pop, M.-D., Proștean, O.: A comparison between smart city approaches in road traffic management. Procedia. Soc. Behav. Sci. 238, 29–36 (2018). https://doi.org/10.1016/j.sbspro.2018.03.004

    Article  Google Scholar 

  4. Nikitas, A., Michalakopoulou, K., Njoya, E.T., Karampatzakis, D.: Artificial intelligence, transport and the smart city: definitions and dimensions of a new mobility era. Sustainability 12, 2789 (2020). https://doi.org/10.3390/su12072789

    Article  Google Scholar 

  5. Kiss, G., Berecz, C.: Priority levels and danger in usage of artificial intelligence in the world of autonomous vehicle. In: Balas, V.E., Jain, L.C., Balas, M.M., Shahbazova, S.N. (eds.) Soft Computing Applications: Proceedings of the 8th International Workshop Soft Computing Applications (SOFA 2018), vol. I, pp. 307–316. Springer International Publishing, Cham (2021). https://doi.org/10.1007/978-3-030-51992-6_24

    Chapter  Google Scholar 

  6. Mondal, M.A., Rehena, Z.: An IoT-based congestion control framework for intelligent traffic management system. In: Chiplunkar, N.N., Fukao, T. (eds.) Advances in Artificial Intelligence and Data Engineering: Select Proceedings of AIDE 2019, pp. 1287–1297. Springer Nature Singapore, Singapore (2021). https://doi.org/10.1007/978-981-15-3514-7_96

    Chapter  Google Scholar 

  7. Guevara, L., Auat Cheein, F.: The role of 5G technologies: challenges in smart cities and intelligent transportation systems. Sustainability 12, 6469 (2020). https://doi.org/10.3390/su12166469

    Article  Google Scholar 

  8. Antonakoglou, K., et al.: On the needs and requirements arising from connected and automated driving. J. Sens. Actuator Netw. 9, 24 (2020). https://doi.org/10.3390/jsan9020024

    Article  Google Scholar 

  9. Jung, C., Lee, D., Lee, S., Shim, D.H.: V2X-communication-aided autonomous driving: system design and experimental validation. Sensors 20, 2903 (2020). https://doi.org/10.3390/s20102903

    Article  Google Scholar 

  10. El Mrini, A., Ghacham Amrani, A.: Wireless sensors network for traffic surveillance and management in smart cities. MATEC Web Conf. 200, 00024 (2018). https://doi.org/10.1051/matecconf/201820000024

    Article  Google Scholar 

  11. Viloria, A., Varela, N., Herazo-Beltran, Y., Lezama, O.B.P.: Design of a network with sensor-cloud technology applied to traffic accident prevention. In: Gunjan, V.K., Zurada, J.M. (eds.) Proceedings of International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications: ICMISC 2020, pp. 911–919. Springer Singapore, Singapore (2021). https://doi.org/10.1007/978-981-15-7234-0_86

    Chapter  Google Scholar 

  12. Ali, S.S.M., George, B., Vanajakshi, L.: A simple multiple loop sensor configuration for vehicle detection in an undisciplined traffic. In: 2011 Fifth International Conference on Sensing Technology, pp. 644–649 (2011). https://doi.org/10.1109/ICSensT.2011.6137062

  13. Bhaskar, L., Sahai, A., Sinha, D., Varshney, G., Jain, T.: Intelligent traffic light controller using inductive loops for vehicle detection. In: 2015 1st International Conference on Next Generation Computing Technologies (NGCT), pp. 518–522. IEEE, Dehradun, India (2015). https://doi.org/10.1109/NGCT.2015.7375173

  14. Favorskaya, M.: Advances in urban video-based surveillance systems: a survey. In: Balas, V.E., Jain, L.C., Kovačević, B. (eds.) Soft Computing Applications: Proceedings of the 6th International Workshop Soft Computing Applications (SOFA 2014), vol. 1, pp. 87–102. Springer International Publishing, Cham (2016). https://doi.org/10.1007/978-3-319-18296-4_7

    Chapter  Google Scholar 

  15. Olaverri-Monreal, C.: Autonomous vehicles and smart mobility related technologies. Infocommun. J. 8(2), 17–24 (2016)

    Google Scholar 

  16. Yaqoob, I., Khan, L.U., Kazmi, S.M.A., Imran, M., Guizani, N., Hong, C.S.: Autonomous driving cars in smart cities: recent advances, requirements, and challenges. IEEE Netw. 34, 174–181 (2020). https://doi.org/10.1109/MNET.2019.1900120

    Article  Google Scholar 

  17. Pop, M.-D., Pandey, J., Ramasamy, V.: Future networks 2030: challenges in intelligent transportation systems. In: 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), pp. 898–902. IEEE, Noida, India (2020). https://doi.org/10.1109/ICRITO48877.2020.9197951

  18. Lim, H., Taeihagh, A.: Autonomous vehicles for smart and sustainable cities: an in-depth exploration of privacy and cybersecurity implications. Energies 11, 1062 (2018). https://doi.org/10.3390/en11051062

    Article  Google Scholar 

  19. Katrakazas, C., Quddus, M., Chen, W.-H., Deka, L.: Real-time motion planning methods for autonomous on-road driving: state-of-the-art and future research directions. Transport. Res. Part C: Emerg. Technol. 60, 416–442 (2015). https://doi.org/10.1016/j.trc.2015.09.011

    Article  Google Scholar 

  20. Grigorescu, S., Trasnea, B., Cocias, T., Macesanu, G.: A survey of deep learning techniques for autonomous driving. J. Field Robot. 37, 362–386 (2020). https://doi.org/10.1002/rob.21918

    Article  Google Scholar 

  21. Bachute, M.R., Subhedar, Javed M.: Autonomous driving architectures: insights of machine learning and deep learning algorithms. Mach. Learn. Appl. 6, 100164 (2021). https://doi.org/10.1016/j.mlwa.2021.100164

    Article  Google Scholar 

  22. Balasubramaniam, A., Pasricha, S.: Object Detection in Autonomous Vehicles: Status and Open Challenges. arXiv.org (2022). https://doi.org/10.48550/arXiv.2201.07706

  23. Fang, J., Meng, H., Zhang, H., Wang, X.: A low-cost vehicle detection and classification system based on unmodulated continuous-wave radar. In: 2007 IEEE Intelligent Transportation Systems Conference (2007). https://doi.org/10.1109/itsc.2007.4357739

  24. Ahmed, S.A., et al.: Active and passive infrared sensors for vehicular traffic control. In: Proceedings of IEEE Vehicular Technology Conference (VTC), pp. 1393–97. IEEE (1994). https://doi.org/10.1109/VETEC.1994.345323

  25. Wang, J., et al.: The road traffic microwave sensor (RTMS). In: The 3rd International Conference on Vehicle Navigation and Information Systems, pp. 83–90. IEEE (1992). https://doi.org/10.1109/VNIS.1992.639938

  26. Bommes, M., Fazekas, A., Volkenhoff, T., Oeser, M.: Video based intelligent transportation systems – state of the art and future development. Transport. Res. Procedia 14, 4495–4504 (2016). https://doi.org/10.1016/j.trpro.2016.05.372

    Article  Google Scholar 

  27. Gavanas, N.: Autonomous road vehicles: challenges for urban planning in European cities. Urban Sci. 3(2), 61 (2019). https://doi.org/10.3390/urbansci3020061

    Article  Google Scholar 

  28. Jun, H., Kim, J., Lee, S., Kim, W.: Memory management in the DDS for CPS. In: Park, J.J., Jeong, Y.-S., Park, S.O., Chen, H.-C. (eds.) Embedded and Multimedia Computing Technology and Service: EMC 2012, pp. 277–283. Springer Netherlands, Dordrecht (2012). https://doi.org/10.1007/978-94-007-5076-0_32

    Chapter  Google Scholar 

  29. Rekik, R., Hasnaoui, S.: Application of a CAN BUS transport for DDS middleware. In: 2009 Second International Conference on the Applications of Digital Information and Web Technologies, pp. 766–771 (2009). https://doi.org/10.1109/ICADIWT.2009.5273919

  30. Abdellaoui, Z., Hasnaoui, S.: DDS middleware on top of FlexRay networks: Simulink blockset implementation of electrical vehicle using FlexRay protocol and its adaptation to DDS concept. Soft. Comput. 23, 11539–11556 (2019). https://doi.org/10.1007/s00500-018-03694-6

    Article  Google Scholar 

  31. OMG DDS Security Standard: OMG | Object Management Group. https://www.omg.org/spec/DDS-SECURITY/1.1/PDF. Last accessed 25 Nov 2020

  32. Zheng, K., et al.: Reliable and efficient autonomous driving: the need for heterogeneous vehicular networks. IEEE Commun. Mag. 53(12), 72–79 (2015). https://doi.org/10.1109/MCOM.2015.7355569

    Article  Google Scholar 

  33. Morgado, A., et al.: A survey of 5G technologies: regulatory, standardization and industrial perspectives. Dig. Commun. Netw. 4(2), 87–97 (2018). https://doi.org/10.1016/j.dcan.2017.09.010

    Article  Google Scholar 

  34. Maglaras, L., Al-Bayatti, A., He, Y., Wagner, I., Janicke, H.: Social internet of vehicles for smart cities. J. Sens. Actuator Netw. 5(1), 3 (2016). https://doi.org/10.3390/jsan5010003

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Politehnica University of Timișoara, 2 Vasile Pârvan Blvd., 300223, Timișoara, Romania

    Cosmin Laurențiu Husariu & Mădălin-Dorin Pop

Authors
  1. Cosmin Laurențiu Husariu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mădălin-Dorin Pop
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mădălin-Dorin Pop .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  2. Aurel Vlaicu University of Arad, Arad, Romania

    Lakhmi C. Jain

  3. Faculty of Engineering, Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Marius Mircea Balas

  4. Cankaya University, Ankara, Türkiye

    Dumitru Baleanu

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Husariu, C.L., Pop, MD. (2023). Roads of the Future: A Survey on the Usage of Smart Traffic Sensor Networks in Autonomous Driving. In: Balas, V.E., Jain, L.C., Balas, M.M., Baleanu, D. (eds) Soft Computing Applications. SOFA 2020. Advances in Intelligent Systems and Computing, vol 1438. Springer, Cham. https://doi.org/10.1007/978-3-031-23636-5_27

Download citation

Publish with us

Policies and ethics

Search

Navigation