Ankit Chaudhari

Working on Deep Reinforcement Learning for Enhancement of Traffic Flow Understanding and Modelling by Two-Dimensional Microscopic Models at the Chair of Econometrics and Statistics esp. in the Transport Sector, Institute of Transport and Economics, "Friedrich List" faculty of Transport and Traffic Sciences.

Product Specialist in Digital Lending

DAAD KOSPIE Scholarship for Masters thesis at TU Dresden. Worked on Project "Machine learning techniques for mixed traffic flow analysis using vehicular trajectory data"

In thesis worked on methods to estimate and calibrated driving behaviour parameters of Wiedemann-99 model for Indian traffic conditions. For identification of following regimes and leader-follower pairs different ML techniques such as Random Forest, XGBoost, Knn and Ensemble method for classification are used and Optimization is done by using genetic algorithm.