POMDP-Based Decision Making for Fast Event Handling in VANETs

Authors

  • Shuo Chen Nanyang Technological University
  • Athirai Irissappane University of Washington
  • Jie Zhang Nanyang Technological University

Keywords:

POMDP, Trust, Information sharing, Decision-making, VANETs

Abstract

Malicious vehicle agents broadcast fake information about traffic events and thereby undermine the benefits of vehicle-to-vehicle communication in vehicular ad-hoc networks (VANETs). Trust management schemes addressing this issue do not focus on effective/fast decision making in reacting to traffic events. We propose a Partially Observable Markov Decision Process (POMDP) based approach to balance the trade-off between information gathering and exploiting actions resulting in faster responses. Our model copes with malicious behavior by maintaining it as part of a small state space, thus is scalable for large VANETs. We also propose an algorithm to learn model parameters in a dynamic behavior setting. Experimental results demonstrate that our model can effectively balance the decision quality and response time while still being robust to sophisticated malicious attacks.

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Published

2018-04-26

How to Cite

Chen, S., Irissappane, A., & Zhang, J. (2018). POMDP-Based Decision Making for Fast Event Handling in VANETs. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/11577

Issue

Section

AAAI Technical Track: Multiagent Systems