Abstract
Popular navigation services are used by drivers both to plan out routes and to optimally navigate real time road congestion in internet of vehicles (IoV). However, the navigation system (such as GPS navigation system) and apps (such as Waze) may not be possible for each individual user to avoid traffic without creating congestion on the clearer roads, and it might even be that such a recommendation leads to longer aggregate routes. To solve this dispersion, in this paper, we first apply a concept of virtual vehicle in IoV, which is an image of driver and vehicle. Then, we study a setting of non-atomic routing in a network of m parallel links with symmetry of information. While a virtual vehicle knows the cost function associated with links, they are known to the individual virtual vehicles choosing the link. The virtual vehicles adapt the cooperation approach via strategic concession game, trying to minimize the individual and total travel time. How much benefit of travel time by the virtual vehicles cooperating when vehicles follow the cooperation decisions? We study the concession ratio: the ratio between the concession equilibrium obtained from an individual optimum and the social optimum. We find that cooperation approach can reduce the efficiency loss compared to the non-cooperative Nash equilibrium. In particular, in the case of two links with affine cost functions, the concession ratio is at most 3/2. For general non-decrease cost functions, the concession ratio is at most 2. For the strategic concession game, the concession ratio can approach to 1 which is a significant improvement over the unbounded price of anarchy.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Sha, W., Kwak, D., Nath, B., Iftode, L.: Social vehicle navigation: integrating shared driving experience into vehicle navigation. In: Proceedings of the 14th Workshop on Mobile Computing Systems and Applications, Jekyll Island, Georgia (2013)
Large, D.R., Burnett, G., Benford, S., Oliver, K.: Crowdsourcing good landmarks for in-vehicle navigation systems. Behav. Inf. Technol. 35(10), 1–10 (2016)
Vasserman, S., Feldman, M., Hassidim, A.: Implementing the wisdom of waze. In: Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), pp. 660–666 (2015)
Qin, Y., Huang, D., Zhang, X.: VehiCloud: cloud computing facilitating routing in vehicular networks. In: Proceedings of 11th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, pp. 1438–1445 (2012)
Roth, A.E.: Game-Theoretic Models of Bargaining. Cambridge University Press, Cambridge (1985)
An, B., Lesser, V., Sim, K.M.: Strategic agents for multi-resource negotiation. Auton. Agent. Multi Agent Syst. 23, 114–153 (2011)
Roughgarden, T., Tardos, É.: Bounding the inefficiency of equilibria in nonatomic congestion games. Games Econ. Behav. 47, 389–403 (2004)
Semwal, T., Nikhil, S., Jha, S.S., Nair, S.B.: TARTARUS: a multi-agent platform for bridging the gap between cyber and physical systems. In: Proceedings of the International Conference on Autonomous Agents & Multiagent Systems, pp. 1493–1495 (2016)
Jørgensen, S., Yeung, D.W.: A strategic concession game. Int. Game Theory Rev. 1, 103–129 (1999)
Acknowledgments
This work is supported by the Natural Science Foundation of Beijing under Grant No. 4132048, National Natural Science Foundation of China under Grant No. 61202435 and 61272521
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Lei, T., Wang, S., Li, J., Yang, F. (2016). A Cooperative Route Choice Approach via Virtual Vehicle in Internet of Vehicles. In: Hsu, CH., Wang, S., Zhou, A., Shawkat, A. (eds) Internet of Vehicles – Technologies and Services. IOV 2016. Lecture Notes in Computer Science(), vol 10036. Springer, Cham. https://doi.org/10.1007/978-3-319-51969-2_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-51969-2_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-51968-5
Online ISBN: 978-3-319-51969-2
eBook Packages: Computer ScienceComputer Science (R0)