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Cooperative Intelligence of Vehicles for Intelligent Transportation Systems (ITS)

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Abstract

The aim of Intelligent Transportation Systems (ITS) is to automate the interactions among vehicles and infrastructure to accomplish high levels of safety measures, comfort, and competence in vehicular communication. To utilize the future trends of increasing traffic safety and efficiency in ITS, integrating vehicles and infrastructures with the cooperative vehicular technique will be the feasible solution. In order to demonstrate the importance of cooperative communication in vehicular networks, a spectral efficient architecture has been proposed for cooperative centralized and distributed spectrum sensing in vehicular networks. We discuss the possibilities of Cognitive Radio in the cooperative vehicular environment. In order to exhibit cooperative vehicular networks, hardware modules are designed for a vehicle to vehicle, vehicle to infrastructure and infrastructure to infrastructure communications. Furthermore, quantitative analysis is made in order to calculate the energy optimization, connectivity failure probability and traffic management in cooperative vehicular networks. In addition, we test the results of the cooperative vehicular network by simulating it in NS2. In this respect, we have considered three different cases, Emergency vehicles, VIP vehicles, and normal vehicles. It is inferred from the results that end-to-end delay for emergency vehicles in the cooperative environment is considerably less as compared to VIP and normal vehicles.

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References

  1. World-Health-Organization. (2009). Global status report on road safety: Time for action. Geneva: WHO.

    Google Scholar 

  2. U.S. Department of Transportation. (2009). Technical Report, Transforming Transportation through Connectivity—ITS strategic research plan, 2010–2014.

  3. Felice, M. D., Chowdhury, K. R., & Bononi, L. (2010). Analyzing the potential of cooperative cognitive radio technology on inter-vehicle communication. IEEE Wireless Days (WD) IFIP (pp. 1–6).

  4. Singh, K. D., Rawat, P., & Bonnin, J.-M. (2014). Cognitive radio for vehicular ad hoc networks (CR-VANETs): Approaches and challenges. Springer EURASIP Journal on Wireless Communications and Networking, 5(3).

  5. Alam, N., & Dempster, A. G. (2013). Cooperative positioning for vehicular networks: Facts and future. IEEE Transactions on Intelligent Transportation Systems, 14(4), 1708–1717.

    Article  Google Scholar 

  6. Higuera, J., Kartsakli, E., Valenzuela, J. L., Alonso, L., Laya, A., Martínez, R., et al. (2012). Experimental study of Bluetooth, ZigBee and IEEE 802.15.4 technologies on board high-speed trains. In IEEE Vehicular Technology Conference (VTC Spring) (pp. 1–5).

  7. Wang, J., Ghosh, M., & Challapali, K. (2011). Emerging cognitive radio applications: A survey. IEEE Communications Magazine, 49(3), 74–81.

    Article  Google Scholar 

  8. Felice, M. D., Chowdhury, K. R., & Bononi, L. (2011). Cooperative spectrum management in cognitive vehicular ad hoc networks. In IEEE Vehicular Networking Conference (VNC) (pp. 47–54).

  9. Li, H., & Irick, D. K. (2010). Collaborative spectrum sensing in cognitive radio vehicular ad hoc networks: Belief propagation on highway. In: IEEE Vehicular Technology Conference (pp. 1–5).

  10. Felice, M. D., Doost-Mohammady, R., Chowdhury, K. R., & Bononi, L. (2012). Smart radios for smart vehicles: Cognitive vehicular networks. IEEE Vehicular Technology Magazine, 7(2), 26–33.

    Article  Google Scholar 

  11. Pagadarai, S., Wyglinski, A., & Vuyyuru, R. (2009) Characterization of vacant UHF TV channels for vehicular dynamic spectrum access. In IEEE Vehicular Networking Conference (VNC) (pp. 1–8).

  12. Niyato, D., Hossain, E., & Wang, P. (2011). Optimal channel access management with QoS support for cognitive vehicular networks. IEEE Transaction on Mobile Computing, 10(4), 573–591.

    Article  Google Scholar 

  13. Kim, W., Gerla, M., Oh, S. Y., Lee, K., & Kassler, A. (2011). CoRoute: A new cognitive any path vehicular routing protocol. ACM Journal on Wireless Communication & Mobile Computing, 11(12), 1588–1602.

    Article  Google Scholar 

  14. Stiller, C., Farber, G., & Kammel, S. (2007). Cooperative cognitive automobile. In IEEE Proceedings of Symposium on Intelligent Vehicles, Turkey (pp. 215–220).

  15. Maurizio, M., & Vlad, P. (2011). Cognitive radio communications for vehicular technology-wavelet applications. In IEEE Symposium on communication and vehicular technology (pp. 1–6).

  16. Ghandour, A. J., Fawaz, K., & Artail, H. (2011). Data delivery guarantees in congested vehicular ad hoc networks using cognitive networks. In International IEEE wireless communications and mobile computing conference (IWCMC) (pp. 871–876).

  17. Akyildiz, I. F., Lo, B. F., & Balakrishnan, R. (2011). Cooperative spectrum sensing in cognitive radio networks: A survey. ACM Journal on Physical Communication, 4(1), 40–62.

    Article  Google Scholar 

  18. Marfia, G., Roccetti, M., Amoroso, A., Gerla, M., Pau, G., & Lim, J.-H. (2011). Cognitive cars: constructing a cognitive playground for VANET research testbeds. In ACM proceedings of the 4th international conference on cognitive radio and advanced spectrum management. Article No. 29.

  19. Caballero-Gil, P., Molina-Gil, J., Hernandez-Goya, C., & Caballero-Gil, C. (2009). Stimulating cooperation in self-organized vehicular networks. In ACM proceedings of the 15th Asia-Pacific conference on communications (APCC) (pp. 346–349).

  20. He, L., Ma, S., Wu, Y.-C., & Ng, T.-S. (2010). Data detection for cooperative vehicular communication systems with unknown channels. In IEEE international conference on electronics, circuits, and systems (ICECS) (pp. 359–362).

  21. Sepulcre, M., Mittag, J., Santi, P., Hartenstein, H., & Gozalvez, J. (2011).Congestion and awareness control in cooperative vehicular systems. In IEEE proceedings (pp. 1260–1279).

  22. Stephenson, S., et al. (2013). Network RTK for intelligent vehicles: Accurate, reliable, available, continuous positioning for cooperative driving. GPS World, 24(2), 61–67.

    MathSciNet  Google Scholar 

  23. Wang, Z., & Chigan, C. (2007). Cooperation enhancement for message transmission in VANETs. Springer Journal on Wireless Personal Communications, 43(1), 141–156.

    Article  Google Scholar 

  24. Hartenstein, H., & Laberteaux, K. (2010). VANET: Vehicular applications and inter-networking technologies. New York: Wiley.

    Book  Google Scholar 

  25. Alam, N., Balaei, A. T., & Dempster, A. G. (2013). Relative positioning enhancement in VANETs, a tight integration approach. IEEE Transaction on Intelligent Transportation System, 14(1), 47–55.

    Article  Google Scholar 

  26. Yin, J. (2004). Performance evaluation of safety applications over DSRC vehicular ad hoc networks. In Proceedings of the 1st ACM international workshop on Vehicular ad hoc networks, USA (pp. 1–9). 01–01 Oct 2004.

  27. Ho, Y. H., Ho, A. H., Hamza-Lup, G. L. & Hua, K. A. (2008). Cooperation enforcement in vehicular networks. In: International conference on communication theory, reliability, and quality of service (pp. 7–12).

  28. Abuelela, M., Olariu, S., & Weigle, M. C. (2008). Notice: An architecture for the notification of traffic incidents. In IEEE Vehicular technology conference (pp. 3001–3005).

  29. Rawat, D. B., Bista, B. B., Yan, G., & Olariu, S. (2014). Vehicle-to-vehicle connectivity and communication framework for vehicular ad-hoc networks. In IEEE International Conference on Complex, Intelligent and Software Intensive Systems (pp. 44–49).

  30. Brickley, O., & Pesch, D. (2013). Communication management for cooperative vehicular systems. In IEEE international symposium on personal, indoor and mobile radio communications (pp. 3507–3512).

  31. Demmel, S. (2013). Building an augmented map for road risk assessment, Ph.D. dissertation, Queensland University of Technology, Australia.

  32. Paul, A., Daniel, A., Ahmad, A., & Rho, S. (2015) Cooperative cognitive intelligence for internet of vehicles. IEEE Systems Journal. 8th April 2015 (available online).

  33. Malinowski, A., & Yu, H. (2011). Comparison of embedded system design for industrial applications. IEEE Transactions on Industrial Informatics, 7(2), 244–254.

    Article  Google Scholar 

  34. Gerla, M., & Kleinrock, L. (2011). Vehicular networks and the future of the mobile internet. ACM Journal on Computer Networks: The International Journal of Computer and Telecommunications, 55(2), 457–469.

    Article  Google Scholar 

  35. Paul, A., & Rho, S. (2015). Probabilistic model for M2M in IoT networking and communication. Springer Telecommunication Systems Journal.

  36. Paul, A. (2013). Graph based M2M optimization in an IoT environment. In ACM proceeding on research in adaptive and convergent systems conference (ACM RACS), Canada (pp. 45–46).

  37. Daniels, R. C., & Heath, R. W. (2012). Link adaptation with position/motion information in vehicle-to-vehicle networks. IEEE Transactions on Wireless Communications, 11(2), 505–509.

    Article  Google Scholar 

  38. Krasteva, R., Boneva, A., Vesselin, G., & Stoianov, I. (2005). Application of wireless protocols bluetooth and ZigBee in telemetry system development. Problems of Engineering, Cybernetics, and Robotics, 55, 30–38.

  39. Bhoi, S. K., & Khilar, P. M. (2013). Vehicular communication: A survey. IET Network Journal, 3(3), 204–217.

    Article  Google Scholar 

  40. Rawat, D. B., Treeumnuk, D., Popescu, D., Abuelela, M., & Olariu, S. (2008) Challenges and perspectives in the implementation of notice architecture for vehicular communications. IEEE International Conference on Mobile Ad Hoc and Sensor Systems, (MASS) (pp. 707–711).

  41. Saurabh, S., Chakole, V. R., & Suryawanshi, Y. A. (2013). ARM hardware platform for vehicular monitoring and tracking. In IEEE international conference on communication systems and network technologies (pp. 757–761).

  42. Chang, K.-L., Chang, J. S., Gwee, B.-H., & Chong, K.-S. (2013). Synchronous-logic and asynchronous-logic 8051 microcontroller cores for realizing the internet of things: A comparative study on dynamic voltage scaling and variation effects. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 3(1), 23–34.

    Article  Google Scholar 

  43. Paul, A., Chen, B.-W., Bharanitharan, K., Jeong, J. & Wang, J.-F. (2013). Video search and indexing with reinforcement agent for interactive multimedia services. ACM Transaction on Embedded Computing Systems, 12(2), Article no: 25. ISSN: 1539-9087.

  44. Paul, A. (2014). Real-time power management for embedded M2M using intelligent learning methods. ACM Transaction on Embedded Computing Systems, 13(5). Article No: 148.

  45. Paul, A. Victorie, T. A. A., & Jeyakumar, A. E. (2003). Particle swarm approach for retiming in VLSI. In 2003, 46th IEEE Midwest Symposium on Circuits and Systems, (MWSCAS 2003), (pp. 1532–1545). December 27–30c, Cairo, Egypt.

  46. Paul, A. (2013). Dynamic power management for ubiquitous network devices. Advance Science Letters, 19(7), 2046–2049. ISSN: 1936-6612.

  47. Shih, P.-Y., Paul, A., Wang, J.-F., & Chen, Y.-H. (2014). Speech-driven talking fast using embedded confusable systems for real time multimedia. Multimedia Tools and Application, 73(1), 417–437.

    Article  Google Scholar 

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Acknowledgments

This study was supported by the Brain Korea 21 Plus project (SW Human Resource Development Program for Supporting Smart Life) funded by Ministry of Education, School of Computer Science and Engineering, Kyungpook National University, Korea (21A20131600005). This work is also supported by IT R&D Program of MSIP/IITP. [10041145, Self-Organized Software platform(SoSp) for Welfare Devices]. And also partially supported by Kyungpook National University Research Fund 2015.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Kyungpook National University, Daegu, Korea

    Alfred Daniel, Anand Paul & Awais Ahmad

  2. Department of Multimedia, Sungkyul University, Anyang-si, Korea

    Seungmin Rho

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  1. Alfred Daniel
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  2. Anand Paul
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  3. Awais Ahmad
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  4. Seungmin Rho
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Correspondence to Anand Paul.

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Daniel, A., Paul, A., Ahmad, A. et al. Cooperative Intelligence of Vehicles for Intelligent Transportation Systems (ITS). Wireless Pers Commun 87, 461–484 (2016). https://doi.org/10.1007/s11277-015-3078-7

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