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Performance Analysis with Traffic Accident for Cooperative Active Safety Driving in VANET/ITS

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Abstract

Recently, by using vehicle-to-vehicle and vehicle-to-infrastructure communications for VANET/ITS, the cooperative active safety driving (ASD) providing vehicular traffic information sharing among vehicles significantly prevents accidents. Clearly, the performance analysis of ASD becomes difficult because of high vehicle mobility, diverse road topologies, and high wireless interference. An inaccurate analysis of packet connectivity probability significantly affects and degrades the VANET/ITS performance. Especially, most of related studies seldom concern the impact factors of vehicular accidents for the performance analyses of VANET/ITS. Thus, this paper proposes a two-phase approach to model a distributed VANET/ITS network with considering accidents happening on roads and to analyze the connectivity probability. Phase 1 proposes a reliable packet routing and then analyzes an analytical model of packet connectivity. Moreover, the analysis is extended to the cases with and without exhibiting transportation accidents. In phase 2, by applying the analysis results of phase 1 to phase 2, an adaptive vehicle routing, namely adaptive vehicle routing (AVR), is proposed for accomplishing dynamic vehicular navigation, in which the cost of a road link is defined in terms of several critical factors: traffic density, vehicle velocity, road class, etc. Finally, the path with the least path cost is selected as the optimal vehicle routing path. Numerical results demonstrate that the analytical packet connectivity probability and packet delay are close to that of simulations. The yielded supreme features justify the analytical model. In evaluations, the proposed approach outperforms the compared approaches in packet connectivity probability, average travel time, average exhausted gasoline. However, the proposed approach may lead to a longer travel distance because it enables the navigated vehicle to avoid traversing via the roads with a higher traffic density.

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References

  1. Taiwan National Police Agency, Ministry of The Interior, http://www.npa.gov.tw

  2. Vehicle Information and Communication System (VICS), http://www.vics.or.jp/

  3. National Intelligent Transport Systems Center of Engineering and Technology (ITSC) (2008). ITS situation and development in China. High Technology and Industrialization 6, 38–43.

    Google Scholar 

  4. Huang, C.-M., & Chang, Y.-C. (2009). Telematcis communication technologies and vehicular networks. Hershey: IGI Global.

    Book  Google Scholar 

  5. Nzouonta, J., Rajgure, N., Wang, G., & Borcea, C. (2009). VANET routing on city roads using real-time vehicular traffic information. IEEE Transactions on Vehicular Technology, 58(7), 3609–3626.

    Article  Google Scholar 

  6. Broustis, I., & Faloutsos, M. (2009). Routing in vehicular networks: feasibility, security, and modeling issues. International Journal of Vehicular Technology, 2008(267513), 1–8.

    Google Scholar 

  7. Sommer, C., Schmidt, A., Chen, Y., German, R., Koch, W., & Dressler, F. (2010). On the feasibility of UMTS-based traffic information systems. Ad Hoc Networks, 8(5), 506–517.

    Article  Google Scholar 

  8. Adler, C. J., Eichler, S., Kosch, T., Schroth, C., & Strassberger, M. (2006). The scalability problem of vehicular ad hoc networks and how to solve it. IEEE Wireless Communications, 13, 22–28.

    Google Scholar 

  9. Schroth, C., Strassberger, M., Eigner, R. & Eichler, S. (2006). A framework for network utility maximization in VANETs. In The 3rd ACM international workshop on vehicular, ad hoc networks, (pp. 86–87).

  10. Standard for wireless local area networks providing wireless communications while in vehicular environment, IEEE P802.11p/D2.01, Mar. 2007.

  11. CAR 2 CAR Communication Consortium, http://www.car-to-car.org/

  12. IEEE P1609.1/D17, Trial-use standard for WAVE—Resource manager, July 2006.

  13. IEEE P1609.2, Trial-use standard for WAVE management messages, June 2006.

  14. IEEE P1609.3/Dl 8, Standard for WAVE—Networking services, Dec. 2005.

  15. Yang, Y., & Bagrodia, R. (2009). Evaluation of VANET-based advanced intelligent transportation systems. In VANET 2009, (pp. 3–12).

  16. Ho, L. W. H., Leung, K. K., Polak, J. W., & Mangharam, R. (2007). Node connectivity in vehicular ad hoc networks with structured mobility. In IEEE local computer network workshop on user mobility and vehicular, networks, (pp. 635–642).

  17. Yang, Q., Lim, A., Li, S., Fang, J., & Agrawal, P. (2008). ACAR: adaptive connectivity aware routing protocol for vehicular ad hoc networks. In International conference on computer communications and networks (ICCCN’08), (pp 1–6).

  18. Panichpapiboon, S., & Pattara-atikom, W. (2008). Connectivity requirements for self-organizing traffic information systems. IEEE Transactions on Vehicular Technology, 57(6), 3333–3340.

    Article  Google Scholar 

  19. Viriyasitavat, W., Tonguz, O. K., & Bai, F. (2009). Network connectivity of VANETs in urban areas. In IEEE communications society conference on sensor, mesh, and ad hoc communications and networks (SECON), (pp. 1–9).

  20. Harri, J., Filali, F., & Bonnet, C. (2009). Mobility models for vehicular ad hoc networks: A survey and taxonomy. IEEE Communications Surveys & Tutorials, 11(4), fourth quater.

  21. Kafsi, M., Dousse, O., Papadimitratos, P., Alpcan, T., & Hubaux, J.-P. (2008). VANET connectivity analysis. EPFL/T-Labs, technical report.

  22. Khabazian, M., & Ali, M. K. M. (2008). A performance modeling of connectivity in vehicular ad hoc networks. IEEE Transactions on Vehicular Technology, 57(4), 2440–2450.

    Article  Google Scholar 

  23. Kesting, A., Treiber, M., & Helbing, D. (2010). Connectivity statistics of store-and-forward intervehicle communication. IEEE Transactions on Intelligent Transportation Systems, 11(1), 172–181.

    Google Scholar 

  24. Taleb, T., Benslimane, A., & Letaief, K. B. (2010). Toward an effective risk-conscious and collaborative vehicular collision avoidance system. IEEE Transactions on Vehicular Technology, 59(3), 1474–1486.

    Google Scholar 

  25. Mohimani, G. H., Ashtiani, F., Javanmard, A., & Hamdi, M. (2009). Mobility modeling, spatial traffic distribution, and probability of connectivity for sparse and dense vehicular ad hoc networks. IEEE Transactions on Vehicular Technology, 58(4), 1998–2007.

    Article  Google Scholar 

  26. Javanmard, A., & Ashtiani, F. (2009). Analytical evaluation of average delay and maximum stable throughput along a typical two-way street for vehicular ad hoc networks in sparse situations. Computer Communications, 32(16), 1768–1780.

    Article  Google Scholar 

  27. Jin, W.-L., & Recker, W. W. (2010). An analytical model of multihop connectivity of inter-vehicle communication systems. IEEE Transactions on Wireless Communications, 9(1), 106–112.

    Google Scholar 

  28. Liu, N., Liu, M., Lou, W., Chen, G., & Cao, J. (2011). PVA in VANETs: Stopped cars are not silent. IEEE Infocom, 2011, 431–435.

    Google Scholar 

  29. Tan, W. L., Lau, W. C., Yue, O. C., & Hui, T. H. (2011). Analytical models and performance evaluation of drive-thru internet systems. IEEE Journal on Selected Areas in Communications, 29(1), 207–222.

    Article  Google Scholar 

  30. PaPaGo, http://www.papago.com.tw

  31. GARMIN, http://www.garmin.com.tw

  32. Clegg, A. H. (1993). An overview of the USA radio broadcast data system (RBDS). In IEEE 1993 international conference, (pp. 192–193).

  33. de Pedro, L. (1995). Traffic information center: a real experience. In Vehicle navigation and information systems conference, 1995. Proceedings. In conjunction with the Pacific Rim TransTech conference. 6th international VNIS, (pp. 475–477).

  34. Schoch, E., Kargl, F., Weber, M., & Leinmuller, T. (2008). Communication patterns in VANETs. IEEE Communications Magazine, 46(11), 119–125.

    Article  Google Scholar 

  35. Intanagonwiwat, C., Govindan, R., & Estrin, D. (2000). Directed diffusion: A scalable and robust communication paradigm for sensor networks. Boston, MA: ACM Mobicom.

    Google Scholar 

  36. Li, M., Liu, Y., Zhao, J., Zhang, Q., & Liu, Y. (2008). Signature-file-based approach for query answering over wireless sensor networks. IEEE Transactions on Vehicular Technology, 57, 3146–3154.

    Article  Google Scholar 

  37. Liu, K., Guo, J., Lu N., & Liu, F. (2009). RAMC: A RSU-assisted multi-channel coordination MAC protocol for VANET. In GLOBECOM Workshops, (pp. 1–6).

  38. Taipei City ATIS Web, http://its.taipei.gov.tw/atis_index/

  39. Marfia, G., Mack, D., Pau, G., Mascolo, C., & Gerla, M. (2011). On the effectiveness of an opportunistic traffic management system for vehicular networks. IEEE Transactions on Intelligent Transportation Systems, 12(4), 1537–1548.

    Article  Google Scholar 

  40. Lu, E. H.-C., Lin, C.-C., & Tseng, V. S. (2008). Mining the shortest path within a travel time Constraint in road network environments. In Proceedings of the 11th international IEEE conference on intelligent transportation systems, (pp. 593–598).

  41. Chang, B.-J., Huang, B.-J., & Liang, Y.-H. (2008). Wireless sensor network-based adaptive vehicle navigation in multihop-relay WiMAX networks. In IEEE AINA 2008, (pp. 56–63).

  42. Papoulis, A., & Pillai, S. U. (2002). Probability, random variables and stochastic processes (4th ed.). New York: McGraw-Hill.

    Google Scholar 

  43. Levy, H. (1982). Stochastic dominance rules for truncated normal distributions: A note. Journal of Finance, 37(5), 1299–1303.

    Article  Google Scholar 

  44. Ertico— GDF, http://www.ertico.com/en/page_archive/gdf_-_geographic_data_files.htm

  45. West, B. H., McGill, R. N., Hodgson, J. W., Sluder, S. S., & Smith, D. E. (1997). Development and verification of light-duty modal emissions and fuel consumption values for traffic models, Federal Highway Administration. U.S. Department of Transportation.

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Acknowledgments

This research was supported in part by the National Science Council of Taiwan, ROC, under Grants: NSC-101-2221-E-224-021-MY2, NSC-101-2221-E-224-022-MY3 and NSC-101-2221-E-252 -008.

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Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Yunlin, Taiwan, ROC

    Ben-Jye Chang

  2. Department of Multimedia Animation and Application, Nan Kai University of Technology, Nantou, Taiwan, ROC

    Ying-Hsin Liang

  3. Department of Information and Communication Engineering, Chaoyang University of Technology, Taichung, Taiwan, ROC

    Houng-Jer Yang

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  1. Ben-Jye Chang
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Correspondence to Ben-Jye Chang.

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Chang, BJ., Liang, YH. & Yang, HJ. Performance Analysis with Traffic Accident for Cooperative Active Safety Driving in VANET/ITS. Wireless Pers Commun 74, 731–755 (2014). https://doi.org/10.1007/s11277-013-1318-2

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