POMDP-Based Decision Making for Fast Event Handling in VANETs


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


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


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.




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



AAAI Technical Track: Multiagent Systems