  Artificial Intelligence-Generated Content (AIGC) refers to the paradigm of
automated content generation utilizing AI models. Mobile AIGC services in the
Internet of Vehicles (IoV) network have numerous advantages over traditional
cloud-based AIGC services, including enhanced network efficiency, better
reconfigurability, and stronger data security and privacy. Nonetheless, AIGC
service provisioning frequently demands significant resources. Consequently,
resource-constrained roadside units (RSUs) face challenges in maintaining a
heterogeneous pool of AIGC services and addressing all user service requests
without degrading overall performance. Therefore, in this paper, we propose a
decentralized incentive mechanism for mobile AIGC service allocation, employing
multi-agent deep reinforcement learning to find the balance between the supply
of AIGC services on RSUs and user demand for services within the IoV context,
optimizing user experience and minimizing transmission latency. Experimental
results demonstrate that our approach achieves superior performance compared to
other baseline models.
