Abstract
The traditional vehicle mobility is restricted to the driver habits and the line-of-sight. The new-emerging connected vehicles enable information exchange with each other at vicinity, which will undoubtedly bring a greatly positive effect on the vehicle mobility pattern. In this paper, we propose to modeling and analyzing the vehicle mobility patterns respectively driven by traditional drivers and connected drivers. We perform the extensive simulations to explore the statistical differences between two mobility patterns and the underlying reasons through comparing to the real vehicle trace datasets. The results show that they behave quite diversely at the concerned aspects, e.g. degree distribution, clustering coefficient, topological shortest path, topological coefficient, and vehicle density, and also we find that the connected vehicles are well distributed and contribute a relieved traffic congestion situation.
Similar content being viewed by others
References
Meng, T., Wu, F., Yang, Z., et al. (2015). Spatial reusability-aware routing in multi-hop wireless networks. IEEE Transaction on Computers,. doi:10.1109/TC.2015.2417543.
Jing, Q., Vasilakos, A. V., Wan, J., et al. (2014). Security of the internet of things: Perspectives and challenges. Wireless Networks, 20(8), 2481–2501.
Li, P., Guo, S., Yu, S., et al. (2014). Reliable multicast with pipelined network coding using opportunistic feeding and routing. IEEE Transactions on Parallel and Distributed Systems, 25(12), 3264–3273.
Liu, X. Y., Zhu, Y., Kong, L., et al. (2014). CDC: Compressive data collection for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 26(8), 2188–2197.
Rahimi, M. R., Ren, J., Liu, C. H., et al. (2014). Mobile cloud computing: A survey, state of art and future directions. Mobile Networks and Applications, 19(2), 133–143.
Rahimi, M, R., Venkatasubramanian, N., & Vasilakos, A. V. (2013). Music: Mobility-aware optimal service allocation in mobile cloud computing. In 2013 IEEE Sixth International Conference on Cloud Computing, IEEE (pp. 75–82).
Sheng, Z., Yang, S., Yu, Y., et al. (2013). A survey on the ietf protocol suite for the internet of things: Standards, challenges, and opportunities. IEEE Wireless Communications, 20(6), 91–98.
Camp, T., Boleng, J., & Davies, V. (2002). A survey of mobility models for ad hoc network research. Wireless Communications and Mobile Computing, 2(5), 483–502.
Chu, T., & Nikolaidis, I. (2002). On the artifacts of random waypoint simulations. In International Conference on Internet Computing (pp. 69–76).
Yoon, J., Liu, M., & Noble, B. (2003). Sound mobility models. In Proceedings of the 9th annual international conference on Mobile computing and networking. ACM (pp. 205–216).
Zeng, Y., Xiang, K., Li, D., et al. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless Networks, 19(2), 161–173.
Zhou, L., Zhang, Y., Song, K., et al. (2011). Distributed media services in P2P-based vehicular networks. IEEE Transactions on Vehicular Technology, 60(2), 692–703.
Fiore, M., & Härri, J. (2008). The networking shape of vehicular mobility. In Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing. ACM (pp. 261–272).
Ait Ali, K., Baala, O., & Caminada, A. (2015). On the spatiotemporal traffic variation in vehicle mobility modeling. IEEE Transactions on Vehicular Technology, 64(2), 652–667.
Mahajan, A., et al. (2006). Urban mobility models for VANETs. In 2nd IEEE International Workshop on Next Generation Wireless Networks.
Kumar, D., Dayal, A. K. (2005). Comparative study of mobility models for MANETs & study of vehicular ad-hoc networks. Bachelor of Science thesis, Indian Institute of Technology, New Delhi, India.
Jaap, S., Bechler, M., & Wolf, L. (2005). Evaluation of routing protocols for vehicular ad hoc networks in city traffic scenarios. In International Conference on Intelligent Transportation Systems Telecommunication (ITST), Brest, France.
Viriyasitavat, W., Boban, M., Tsai, H. M., et al. (2015). Vehicular communications: Survey and challenges of channel and propagation models. IEEE Vehicular Technology Magazine, 10(2), 55–66.
Cunha, F. D., Carneiro Vianna, A., Mini, R., et al. (2014). Is it possible to find social properties in vehicular networks? In 2014 IEEE Symposium on Computers and Communication, IEEE (pp. 1–6).
Zhang, X. M., Zhang, Y., Yan, F., et al. (2015). Interference-based topology control algorithm for delay-constrained mobile Ad hoc networks. IEEE Transactions on Mobile Computing, 14(4), 742–754.
Acampora, G., et al. (2010). Interoperable and adaptive fuzzy services for ambient intelligence applications. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 5(2), 1–26.
Yang, M., Li, Y., Jin, D., et al. (2014). Software-defined and virtualized future mobile and wireless networks: A survey. Mobile Networks and Applications, 20(1), 4–18.
Jin, L., Chen, Y., Wang, T., et al. (2013). Understanding user behavior in online social networks: A survey. IEEE Communications Magazine, 51(9), 144–150.
Dvir, A., & Vasilakos, A. V. (2011). Backpressure-based routing protocol for DTNs. ACM SIGCOMM Computer Communication Review, 41(4), 405–406.
Leskovec, J., Kleinberg, J., & Faloutsos, C. (2007). Graph evolution: Densification and shrinking diameters. ACM Transactions on Knowledge Discovery from Data (TKDD), 1(1), 2.
Zhou, L., Naixue, X., Shu, L., et al. (2010). Context-Aware middleware for multimedia services in heterogeneous networks. IEEE Intelligent Systems, 25(2), 40–47.
Loulloudes, N., Pallis, G., & Dikaiakos, M. D. (2010). The dynamics of vehicular networks in urban environments. arXiv:1007.4106.
Liu, X., Li, Z., Li, W. et al. (2012). Exploring social properties in vehicular ad hoc networks. In Proceedings of the Fourth Asia-Pacific Symposium on Internetware. ACM (pp. 1–24).
Davies, V. A. (2000). Evaluating mobility models within an ad hoc network. advisor: Tracy Camp, Department of Mathematical and Computer Sciences. Colorado School of Mines.
Liu, Z., Liu, Y., Wang, J., & Deng, W. (2015). Modeling and simulating traffic congestion propagation in connected vehicles driven by temporal and spatial preference. Wireless Networks,. doi:10.1007/s11276-015-1021-1.
Akhtar, N., Ozkasap, O., & Ergen, S. C. (2013). VANET topology characteristics under realistic mobility and channel models. In IEEE Wireless Communications and Networking Conference (WCNC), IEEE (pp. 1774–1779).
SUVnet-Trace Data. http://wirelesslab.sjtu.edu.cn/taxi_trace_data.html.
Acknowledgments
This work was supported by National Nature Science Foundation [51175215, 61202472, 61373123, 61572229]; International Scholar Exchange Fellowship (ISEF) program of Korea Foundation for Advanced Studies (KFAS); Jilin Provincial Foundation for Young Scholars [20130522116JH]; and Jilin Provincial International Cooperation Foundation [20140414008GH, 20150414004GH].
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, L., Liu, Y., Wang, J. et al. Vehicle mobility driven by traditional drivers versus connected drivers. Wireless Netw 22, 1891–1900 (2016). https://doi.org/10.1007/s11276-015-1078-x
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11276-015-1078-x