KSVTs: Towards Knowledge-Based Self-Adaptive Vehicle Trajectory Service

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 253)

Abstract

The most of very large traffic system by growing the variety of services, the relationships between the vehicle network and the infrastructure are more complex. Moreover, intelligent transportation systems are getting more and more to develop a better combination of travel safety and efficiency since long time ago. Vehicle is being evolved and traffic environment is especially also organized well-defined schedules priorities, which is real time based wireless network traffic condition, variable traffic condition, and traffic pattern from the vehicle navigation system. Accordingly, we propose to Knowledge-based Self-adaptive Vehicle Trajectory Service using genetic algorithm in this paper.

Keywords

Vehicle network Intelligent transportation system (ITS) Knowledge-based trajectory data (KTD) Self-adaptive trajectory service (STS) 

References

  1. 1.
    Carter A (2005) The status of vehicle-to-vehicle communication as a means of improving crash prevention performance, Tech. Rep. 05-0264Google Scholar
  2. 2.
    Naumov V, Gross TR (2007) Connectivity-aware routing (CAR) in vehicular ad hoc networks. In: INFOCOM, IEEEGoogle Scholar
  3. 3.
    Zhao J, Cao G (2008) VADD: vehicle-assisted data delivery in vehicular ad hoc networks. IEEE Trans Veh Technol 57(3):1910–1922CrossRefMathSciNetGoogle Scholar
  4. 4.
    Jeong J, Guo S, Gu Y, He T, Du D (2008) TBD: trajectory-based data forwarding for light-traffic vehicular networks, Tech. Rep. 08-040Google Scholar
  5. 5.
    Wu H, Fujimoto R, Guensler R, Hunter M (2004) MDDV: a mobility-centric data dissemination algorithm for vehicular networks. In: VANETACMGoogle Scholar
  6. 6.
    Michalewicz Z (1992) Genetic algorithms + data structures = evolutionary programs. Springer-Verlag, AI Series, New YorkGoogle Scholar
  7. 7.
    Spears W, DeJong K (1991) An analysis of multi-point crossover. In: Rawlins G (ed) Foundations of genetic algorithms. Morgan-Kaufmann, San FranciscoGoogle Scholar
  8. 8.
    Starkweather T, Whitley D, Mathias K (1991) Optimization using distributed genetic algorithms. In: Parallel problem solving from nature. Springer Verlag, BerlinGoogle Scholar
  9. 9.
    Kim J-H, Kim S-C (2013) Toward hybrid model for architecture-oriented semantic schema of self-adaptive system. In: International conference on green and human information technology (ICGHIT 2013), LNCS. Springer-VerlagGoogle Scholar
  10. 10.
    Navarro LDB, Sdholt M, Douence R, Menaud JM (2007) Invasive patterns for distributed applications. In Proceedings of the 9th international symposium on distributed objects, middleware, and applications (DOA’07), LNCS. Springer VerlagGoogle Scholar
  11. 11.
    Grace P, Lagaisse B, Truyen E, Joosen W (2008) A reflective framework for fine-grained adaptation of aspect-oriented compositions. In: 7th international symposium on software composition (SC), LNCS, vol 4954, Budapest, Hungary.Springer Verlag, pp 215–230Google Scholar
  12. 12.
    Kim J-H, Kim S-C (2013) Design of architectural smart vehicle middleware. Inform Int Interdiscipl J (III), ISSN 1343-4500Google Scholar
  13. 13.
    Sharma PK, Loyall JP, Heineman GT, Schantz RE, Shapiro R, Duzan G (2004) Component-based dynamic QoS adaptations in distributed real-time and embedded systems. In: 6th international OTM conference on distributed objects and applications (DOA), LNCS, vol 3291, Larnaca, Cyprus. Springer, pp 1208–1224Google Scholar
  14. 14.
    Hoh B, Gruteser M, Xiong H, Alrabady A (2010) Achieving guaranteed anonymity in GPS traces via uncertainty-aware path cloaking. IEEE Trans Mob Comput 9(8):1089–1107CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Computer EngineeringHanSung UniversitySeongbuk-guKorea
  2. 2.College of Information and Communication EngineeringSungKyunKwan UniversitySuownKorea

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