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With the increasing popularity of Digital Twin, there is an opportunity to employ deep learning models in symbiotic simulation system. Symbiotic simulation can replicate multiple what-if simulation instances from its real-time reference simulation (base simulation) for short-term forecasting. Hence, it is a useful tool for just-in-time decision making process. Recent trends on symbiotic simulation studies emphasize on its combination with machine learning. Despite its success and usefulness, very few works focus on application of such a hybrid system in microscopic traffic simulation. Existing application of machine (deep) learning models in microscopic traffic simulation is confined to either predictive analysis or offline simulation-based prescriptive analysis. Thus, there is also lack of work on updating parameters of a deep learning model dynamically for real-time traffic simulation. This is necessary if the learning-based …