Dear editor,In recent years, data-driven car-following models have been developed based on their ability to drill down to information in driving data and their flexibility. According to a study by Fleming et al. [1], ...
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Dear editor,In recent years, data-driven car-following models have been developed based on their ability to drill down to information in driving data and their flexibility. According to a study by Fleming et al. [1], the main limitation of existing methods is an insufficient amount of natural driving data. In addition,there are many situations during actual driving processes,such as those under extreme conditions [2] and in the early stages of car-following behavior modeling. In these cases,sparse data learning algorithms are indispensable.
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