In smart transportation era, user journey is considered one of major aspect where researchers introduced different frameworks and systems to deliver level of optimization that satisfy drivers at outdoor environment. Context-aware recommendation is one of the techniques used to accomplish such an optimization for a trip by utilizing driver’s and location’s information. Many scenarios were covered in the previous studies, in particular, gas station scenario. In this paper, we highlight recent academia that focus on context-aware recommendation systems for the purpose of introducing an optimized high-level and conceptual context-aware recommender based on real-time feed specification, user feedback, dynamic profile insertion, dynamic radius search and deep neural network modules
