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Autonomous vehicles need to have the ability to predict the motion of surrounding vehicles, which will help to avoid potential accidents and make the best decision to ensure safety and comfort. The interactions among vehicles and those between them and the uncertainty of driving intention make trajectory prediction a challenging task. This study presents a long short-term memory (LSTM) model for the task of trajectory prediction to account for both the mutual information and the multimodaldoi:10.1049/iet-its.2019.0299 fatcat:zmbgcoloqbb7lapftkkyfzs6ky