Navigation is one of the most important daily activities of individuals in an urban environment. The spatial information systems of the user guidance are the most common services which guide people to navigate the various routes with different goals.The main challenge of such systems is providing context-aware navigation information. The location, time,and the identifier of the individual person are among the primary contexts and the other related contexts are modeled based on these contexts. The present paper attempts to model the spatial-temporal communication of the moving user based on the identifier of the individuals. So that it covers all spatial communications (topologic, metric and directional) in time dimension andtakes the characteristics of the user and the related contexts into consideration. In this regard, the proposed model utilizedthe advantages of Allen’s Multi-Interval Algebra (MIA) and dynamic Voronoi-based Continuous Range Query (VCRQ), and introduceda new method by following the large calculus principles and the existing customization methods. The designed model (MIA₂₅) was implemented in a software applicable in mobile systems. The evaluation of the implemented model in the tourist’s navigation scenariointhe regions 3, 6, and 11 of Tehran municipality was carried out based on 3 parameters of accuracy, runtimeand users’ satisfaction. These three regions were selected as the case study area. In order to test the accuracy of the model, the designed software was iterated 100 times in three different routes in the study area by three different tourists at three time intervals with two different average speed. Then, the recognition of each one of the textures existing on the way, was examined by the one-way binomial approximationwith 95% of confidence level over 100 iterations. Also, two indices of correctness and recall were used to evaluate the recognition of the textures through the entire route. The results of implementation and evaluation of the model based on three parameters of accuracy, runtime and users’ satisfaction demonstrate the efficiency of the proposed model in an urban context-aware navigation system.