AAAI Publications, Thirty-Second AAAI Conference on Artificial Intelligence

Font Size: 
POMDP-Based Decision Making for Fast Event Handling in VANETs
Shuo Chen, Athirai A. Irissappane, Jie Zhang

Last modified: 2018-04-26

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.

Keywords


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

Full Text: PDF