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IoT in Traffic Management: Review of Existing Methods of Road Traffic Regulation

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Applied Informatics and Cybernetics in Intelligent Systems (CSOC 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1226))

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Abstract

Internet of Things (IoT) is an important upcoming technology for making infrastructures of our society smart and adaptable to the users’ needs. One such infrastructure is transportation. This article discusses existing methods and algorithms for automated management of traffic flows with a purpose of identifying hot spots and methods for applying IoT in this sector. Advantages and disadvantages of the existing methods are discussed, including evaluation of their effectiveness.

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References

  1. Mirshahi, M., Obenberger, J., Fuhs, C.: Active traffic management: the next step in congestion management (2007)

    Google Scholar 

  2. Wallace, C.E. et al.: TRANSYT-7F user’s manual. No.UF-TRC-U32 FP-06/07 (1984)

    Google Scholar 

  3. Hunt, P.B., et al.: SCOOT-a traffic responsive method of coordinating signals. No. LR 1014 Monograph (1981)

    Google Scholar 

  4. Gartner N.H., Tarnoff P.J., Andrews C.M.: Evaluation of optimized policies for adaptive control strategy. Transportation Research Record. No. 1324 (1991)

    Google Scholar 

  5. Sims, A.G., Dobinson, K.W.: The Sydney coordinated adaptive traffic (SCAT) system philosophy and benefits. IEEE Trans. Veh. Technol. 29(2), 130–137 (1980)

    Article  Google Scholar 

  6. Mauro, V., Di Taranto, C.: Utopia. IFAC Proc. 23(2), 245–252 (1990)

    Article  Google Scholar 

  7. Zhao, Y., Tian, Z.: An overview of the usage of adaptive signal control system in the United States of America. Appl. Mech. Mater. 178, 2591–2598 (2012)

    Article  Google Scholar 

  8. Misbahuddin, S., et al.: IoT based dynamic road traffic management for smart cities. In: 2015 12th International Conference on High-capacity Optical Networks and Enabling/Emerging Technologies (HONET). IEEE (2015)

    Google Scholar 

  9. Chong, H.F., Ng, D.W.K.: Development of IoT device for traffic management system. In: 2016 IEEE Student Conference on Research and Development (SCOReD). IEEE (2016)

    Google Scholar 

  10. Slavin, C., et al.: Statistical study of the impact of adaptive traffic signal control on traffic and transit performance. Transp. Res. Record. 2356(1), 117–126 (2013)

    Article  Google Scholar 

  11. Ozbay, K, et al.: Evaluation of adaptive control strategies for NJ highways. No. FHWA-NJ-2006-001 (2006)

    Google Scholar 

  12. Pavleski, D., Koltovska-Nechoska, D., Ivanjko, E.: Evaluation of adaptive traffic control system UTOPIA using microscopic simulation. In: 2017 International Symposium ELMAR. IEEE (2017)

    Google Scholar 

  13. Leontiadis, I., et al.: On the effectiveness of an opportunistic traffic management system for vehicular networks. IEEE Trans. Intell. Transp. Syst. 12(4), 1537–1548 (2011)

    Article  Google Scholar 

  14. An, S.-H., Lee, B.-H., Shin, D.-R.: A survey of intelligent transportation systems. In: 2011 Third International Conference on Computational Intelligence, Communication Systems and Networks. IEEE (2011)

    Google Scholar 

  15. Kanungo, A., Sharma, A., Singla, C.: Smart traffic lights switching and traffic density calculation using video processing. In: 2014 Recent Advances in Engineering and Computational Sciences (RAECS). IEEE (2014)

    Google Scholar 

  16. Milanes, V., et al.: An intelligent V2I-based traffic management system. IEEE Trans. Intell. Transp. Syst. 13(1), 49–58 (2012)

    Article  Google Scholar 

  17. Wang, H.: A reservation-based smart parking system (2011)

    Google Scholar 

  18. He, W., Yan, G., Da Xu, L.: Developing vehicular data cloud services in the IoT environment. IEEE Trans. Industr. Inf. 10(2), 1587–1595 (2014)

    Article  Google Scholar 

  19. Khanna, A., Anand, R.: IoT based smart parking system. In: 2016 International Conference on Internet of Things and Applications (IOTA). IEEE (2016)

    Google Scholar 

  20. Al-Sakran, H.O.: Intelligent traffic information system based on integration of Internet of Things and Agent technology. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 6(2), 37–43 (2015)

    Google Scholar 

  21. Roess, R.P., Prassas, E.S., McShane, W.R.: Traffic Engineering. Pearson/Prentice Hall, Upper Saddle River (2004)

    Google Scholar 

  22. De Souza, A.M., et al.: Traffic management systems: a classification, review, challenges, and future perspectives. Int. J. Distrib. Sensor Netw. 13(4), 1550147716683612 (2017)

    Article  Google Scholar 

  23. Rizwan, P., Suresh, K., Babu, M.R.: Real-time smart traffic management system for smart cities by using Internet of Things and big data. In: 2016 International Conference on Emerging Technological Trends (ICETT). IEEE (2016)

    Google Scholar 

  24. Choosri, N., et al.: IoT-RFID testbed for supporting traffic light control. Int. J. Inf. Electron. Eng. 5(2), 102 (2015)

    Google Scholar 

  25. Bui, K.H.N., Jung, J.E., Camacho, D.: Game theoretic approach on Real-time decision making for IoT-based traffic light control. Concurrency Comput. Pract. Experience 29(11), e4077 (2017)

    Article  Google Scholar 

  26. Yu, M., et al.: An RFID electronic tag based automatic vehicle identification system for traffic IOT applications. In: 2011 Chinese Control and Decision Conference (CCDC). IEEE (2011)

    Google Scholar 

  27. Miz, V., Hahanov, V.: Smart traffic light in terms of the cognitive road traffic management system (CTMS) based on the Internet of Things. In: Proceedings of IEEE East-West Design & Test Symposium (EWDTS 2014). IEEE (2014)

    Google Scholar 

  28. Thakur, T.T., et al.: Real time traffic management using Internet of Things. In: 2016 International Conference on Communication and Signal Processing (ICCSP). IEEE (2016)

    Google Scholar 

  29. Phan, C.T., et al.: Applying the IoT platform and green wave theory to control intelligent traffic lights system for urban areas in Vietnam. TIIS 13(1), 34–51 (2019)

    MathSciNet  Google Scholar 

  30. Chowdhury, A.: Priority based and secured traffic management system for emergency vehicle using IoT. In: 2016 International Conference on Engineering & MIS (ICEMIS). IEEE (2016)

    Google Scholar 

  31. Mzahm, A.M., Ahmad, M.S., Tang, A.Y.C.: Agents of things (AoT): an intelligent operational concept of the Internet of Things (IoT). In: 2013 13th International Conference on Intellient Systems Design and Applications. IEEE (2013)

    Google Scholar 

  32. Jabbarpour, M.R., Nabaei, A., Zarrabi, H.: Intelligent guardrails: an IoT application for vehicle traffic congestion reduction in smart city. In: 2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). IEEE (2016)

    Google Scholar 

  33. Nor, R.F.A.M., Zaman, F.H.K., Mubdi, S.: Smart traffic light for congestion monitoring using LoRaWAN. In: 2017 IEEE 8th Control and System Graduate Research Colloquium (ICSGRC). IEEE (2017)

    Google Scholar 

  34. Turcu, C.E., Găitan, V.G., Turcu, C.O.: An internet of things-based distributed intelligent system with self-optimization for controlling traffic-light intersections. In: 2012 International Conference on Applied and Theoretical Electricity (ICATE). IEEE (2012)

    Google Scholar 

  35. Masek, P., et al.: A harmonized perspective on transportation management in smart cities: the novel IoT-driven environment for road traffic modeling. Sensors 16(11), 1872 (2016)

    Article  Google Scholar 

  36. Keertikumar, M., Shubham, M., Banakar, R.M.: Evolution of IoT in smart vehicles: an overview. In: 2015 International Conference on Green Computing and Internet of Things (ICGCIoT). IEEE (2015)

    Google Scholar 

  37. Kaminski, N.J., Murphy, M., Marchetti, N.: Agent-based modeling of an IoT network. In: 2016 IEEE International Symposium on Systems Engineering (ISSE). IEEE (2016)

    Google Scholar 

  38. Venkatesh, H., Perur, S.D., Jagadish, M.C.: An approach to make way for intelligent ambulance using IoT. Int. J. Electr. Electron. Res. 3(1), 218–223 (2015)

    Google Scholar 

  39. Tielert, T., et al.: The impact of traffic-light-to-vehicle communication on fuel consumption and emissions. In: 2010 Internet of Things (IOT). IEEE (2010)

    Google Scholar 

  40. Anass, R., Yassine, H., Mohammed, B.: IoT for ITS: a dynamic traffic lights control based on the Kerner three phase traffic theory. Int. J. Comput. Appl. 145(1), 0975–8887 (2016)

    Google Scholar 

  41. Liu, Y., Lei, L., Chen, W.P.: Intelligent traffic light control using distributed multi-agent Q learning. In: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC). IEEE (2017)

    Google Scholar 

  42. Bui, K.-H.N., Jung, J.J.: Internet of agents framework for connected vehicles: a case study on distributed traffic control system. J. Parallel Distrib. Comput. 116, 89–95 (2018)

    Article  Google Scholar 

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Acknowledgments

The reported study was funded by RFBR, project number 19-37-90102.

Author information

Authors and Affiliations

  1. Southern Federal University, Institute of Computer Technologies and Information Security, Chekhova. 2, 347900, Taganrog, Russia

    Dmitry Elkin

  2. Department of Electrical Engineering and Automation, Aalto University, Otakaari 1B, 00076, Aalto, Finland

    Valeriy Vyatkin

  3. Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå, 97187, Sweden

    Valeriy Vyatkin

Authors
  1. Dmitry Elkin
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  2. Valeriy Vyatkin
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Correspondence to Dmitry Elkin .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Elkin, D., Vyatkin, V. (2020). IoT in Traffic Management: Review of Existing Methods of Road Traffic Regulation. In: Silhavy, R. (eds) Applied Informatics and Cybernetics in Intelligent Systems. CSOC 2020. Advances in Intelligent Systems and Computing, vol 1226. Springer, Cham. https://doi.org/10.1007/978-3-030-51974-2_50

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