Design of Intelligent Transportation Systems using Machine Learning Techniques an Empirical Evaluation

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Dr. G. Ravindranath, Mr. K. Vali Babu


Machine learning (ML) plays an important role in the intellectualization of transport systems. Ongoing research has seen the arrival and predominance of deep learning that had prompted the shock in ITS (Intelligent Transportation Systems) that can manage the real-time information gathered from heterogeneous sources in a split second and examine them for better decision-making skills. The new learning approaches have thus been replaced by conventional ML models in various applications and the ITS scene is being reshaped. In such point of view, we offer the detailed study that highlights on the usage of deep learning models to improve such knowledge level of transportation systems. By sorting out various important research works that were initially scattered to a large extent, this study gives a better image of the implementation of different deep learning models for varying transport applications.

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