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Traffic systems exhibit supply-side uncertainty which is alleviated through real-time information. This article explores subscription models for a private agency sharing data at a fixed rate. A multiclass strategy-based equilibrium model is developed for two classes of subscribed and unsubscribed travelers, whose optimal strategy given the link-state costs is modeled as a Markov decision process (MDP) and a partially-observable MDP, respectively. A utility-based subscription choice model is formulated to study the impacts of subscription rates on the percentage of travelers choosing to subscribe. Solutions to the fixed-point formulation are determined using iterative algorithms. The proposed subscription model can be used for designing optimal subscription rates in various settings where real-time information can be a valuable routing tool such as express lanes, parking systems, roadside delivery, and routing of vulnerable road users.