POMDP-Based Decision Making for Fast Event Handling in VANETs

• Main Authors: Chen, Shuo, Irissappane, Athirai, Zhang, Jie
• Format: Conference Proceeding
• Language: English
• ISSN: 2159-5399; 2374-3468
• DOI: 10.1609/aaai.v32i1.11577

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.