Abstract
Vehicular ad hoc networks serves as an important enabling technology for assistant driving and intelligent transportation, it has aroused wide concern since it was proposed. However, due to the dynamic topology and poor link quality of wireless channel in VANETs caused by vehicle movement and obstacles, establishing a reliable multi-hop communication in VANETs is rather challenging. In this paper, we proposed a position-based reinforcement learning routing protocol. The protocol uses Q-learning to evaluate the quality of the neighbor nodes, and thus selects the next-hop node according to the quality of the neighbor nodes and the position of the destination node to maintain the stability and reliability of the links and routing. Through extensive simulation, the effectiveness of the proposed protocol is shown.
The work presented in this paper was supported by National Natural Science Foundation of China (Grant number 61371081, 91638204).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Toor, Y., Muhlethaler, P., Laouiti, A.: Vehicle ad hoc networks: applications and related technical issues. IEEE commun. Surv. Tutorials 10(3), 74–88 (2008)
Altayeb, M., Mahgoub, I.: A survey of vehicular ad hoc networks routing protocols. Int. J. Innov. Appl. Stud. 3(3), 829–846 (2013)
Perkins, C., Belding-Royer, E., Das, S.: Ad hoc on-demand distance vector (AODV) routing, No. RFC 3561 (2003)
Liu, J., Wan, J., Wang, Q., Deng, P., Zhou, K., Qiao, Y.: A survey on position-based routing for vehicular ad hoc networks. Telecommun. Syst. 62(1), 15–30 (2016)
Karp, B., Kung, H.T.: GPSR: greedy perimeter stateless routing for wireless networks. In: Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, pp. 243–254. ACM (2000)
Watkins, C.J., Dayan, P.: Q-learning. Mach. Learn. 8(3–4), 279–292 (1992)
Parekh, A.K.: Selecting routers in ad-hoc wireless networks. In: Proceedings of the SBT/IEEE International Telecommunications Symposium, vol. 204 (1994)
Kuklinski, S., Wolny, G.: Density based clustering algorithm for vehicular ad-hoc networks. Int. J. Internet Protoc. Technol. 4(3), 149–157 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sun, Y., Lin, Y., Tang, Y. (2019). A Reinforcement Learning-Based Routing Protocol in VANETs. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_303
Download citation
DOI: https://doi.org/10.1007/978-981-10-6571-2_303
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-6570-5
Online ISBN: 978-981-10-6571-2
eBook Packages: EngineeringEngineering (R0)