Abstract
Fatigue driving might affect the traffic safety when the vehicles are on the cruising state in highway. Trying to solve this problem, this paper uses the movement pattern of the fish to the vehicles fleet, and develops a model of vehicle group with realistic restrictions based on the existed fish algorithms, the mobile behavioral model and cluster behavior model, and then demonstrates the feasibility of applying the fish behavior to the cooperative movement of vehicle groups through analyzing the trajectory, velocity and spacing of vehicles.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Chen, G., Guo, D.: Research and development on internet of vehicle. J. Mob. Commun. 17, 23–26 (2011)
Gaamel, A.M., Maratha, B.P., Sheltami, T.R., Shakshuki, E.M.: Fault-tolerance evaluation of VANET under different data dissemination models. Int. J. Veh. Telemat. Infotain. Syst. (IJVTIS) 1(1), 54–68 (2017)
Mir, Z.H., Filali, F.: A simulation-based study on the environment-specific propagation model for vehicular communications. Int. J. Veh. Telemat. Infotain. Syst. (IJVTIS) 1(1), 1–18 (2017)
Cortéspolo, D., Callecancho, J., Carmonamurillo, J., Gonzálezsánchez, J.: Future trends in mobile-fixed integration for next generation networks: classification and analysis. Int. J. Veh. Telemat. Infotain. Syst. (IJVTIS) 1(1), 33–53 (2017)
Zhang, H., Liu, N., Chu, X., Long, K., Aghvami, A.H., Leung, V.C.M.: Network slicing based 5G and future mobile networks: mobility, resource management, and challenges. IEEE Commun. Mag.
Zhang, H., Dong, Y., Cheng, J., Leung, V.C.M.: Fronthauling for 5G LTE-U ultra dense cloud small cell networks. IEEE Wirel. Commun. 23(6), 48–53 (2016)
Chen, S., Zhao, J.: The requirements, challenges and technologies for 5G of terrestrial mobile telecommunication. IEEE Commun. Mag. 52(5), 36–43 (2014)
Chen, S., Hu, J., Shi, Y., Zhao, L.: LTE-V: a TD-LTE based V2X solution for future vehicular network. IEEE Internet Things J. 3(6), 997–1005 (2016)
Zheng, Q., Zheng, K., Zhang, H., Leung, V.C.M.: Delay-optimal virtualized radio resource scheduling in software-defined vehicular networks via stochastic learning. IEEE Trans. Veh. Technol. 65(12), 9479–9492 (2016)
Jiang, C., Zhang, H., Han, Z., Cheng, J., Ren, Y., Leung, V.C.M., Hanzo, L.: Information-sharing outage-probability analysis of vehicular networks. IEEE Trans. Veh. Technol. 65(12), 9479–9492 (2016)
Jiang, C., Zhang, H., Han, Z., Cheng, J., Ren, Y., Hanzo, L.: On the outage probability of information sharing in cognitive vehicular networks. In: Proceedings of IEEE International Conference on Communications (ICC), Kuala Lampur, Malaysia, 23–27 May 2016
Huang, Y., Wang, J., Jiang, C., Zhang, H., Leung, V.C.M.: Vehicular network based reliable traffic density estimation. In: Proceedings of the IEEE Vehicular Technology Conference (VTC), Nanjing, 15–18 May 2016
Pressas, A., Özpolat, M., Sheng, Z., Ali, F.: Performance evaluation of networking protocols for connected vehicles. Int. J. Veh. Telemat. Infotain. Syst. (IJVTIS) 1(1), 1–14 (2017)
Zhu, Y., Chen, H., Shen, H.: Bio-inspired Computing Individual, Swarm and Community Evolution Models and Methods, pp. 35–38. Tsinghua University Press, Beijing (2013)
Huth, A., Wissel, C.: The simulation of the movement in fish schools. J. Theor. Biol. 156, 365–385 (1992)
Wang, J., Ren, Z.: Application if artificial fish algorithm in vehicle behavior under serious traffic incident. J. Syst. Simul. 23 (2011)
Jiang, S., Ji, Y.: Artificial fish swarm algorithm for solving road network equilibrium traffic assignment problem. Comput. Simul. 28(6), 326–329 (2011). ISSN 1006-9348
Lei, L., Shiru, Q.: An effective swarm vehicle coordinative traffic control design based on fish swarm grouping behavior. J. Northwestern Polytechn. Univ. 30 (2012)
Ban, X., Ning, S.: Research on advanced self-organization behavior for artificial fish school. Acta Automatica Sin. 34(10), 1328–1331 (2008)
Tang, A., Yip, A.: Collision avoidance timing analysis of DSRC-based vehicles. Accid. Anal. Prev. 42(1), 182–195 (2010)
Chu, T.G., Wang, L., Mu, S.M.: Collective behavior analysis of an anisotropic swarm model. In: Proceedings of the 16th International Symposium on Mathematical Theory of Network and Systems. Mathematical Theory of Network and Systems (2004)
He, S., Xia, L.: Friction coefficient mesurement and evaluation for lane surface of expressway. J. Highway Transp. Res. Devel. 19 (2002)
Johansson, G., Rumar, K.: ‘Driver’s brake reaction times’, human factors. J. Hum. Factors Ergon. Soc. 13, 23–27 (1971)
Taoka, G.: Break reaction times of unalerted drivers. ITE J. 59, 19–21 (1989)
Tian, D., Zhu, K.: Swarm model for cooperative multi-vehicle mobility with inter-vehicle communications. IET Intell. Transp. Syst. 9, 887–896 (2015)
Yang, D., Pu, Y., Yang, F.: Car-following model based on optimal distance and its characteristics analysis. J. Northwest Transp. Univ. 47 (2012)
Acknowledgments
This research was supported in part by no. Beijing Science and Technology Program no. D171100000317003 and the National Natural Science Foundation of China under Grant nos. 61672082, U1564212.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Tian, D. et al. (2018). Modeling and Simulation on Cooperative Movement of Vehicle Group Based on the Behavior of Fish. In: Long, K., Leung, V., Zhang, H., Feng, Z., Li, Y., Zhang, Z. (eds) 5G for Future Wireless Networks. 5GWN 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 211. Springer, Cham. https://doi.org/10.1007/978-3-319-72823-0_58
Download citation
DOI: https://doi.org/10.1007/978-3-319-72823-0_58
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-72822-3
Online ISBN: 978-3-319-72823-0
eBook Packages: Computer ScienceComputer Science (R0)