In order to predict a change in land use in a city by an autonomous vehicle, the present invention selects any one of a plurality of scenarios after selecting a city to predict the change in land use, and the same according to the size of the city selected to apply the cellular automata. Divide into a plurality of cells having a size, divide the land use of the plurality of cells, extract the accessibility, land price and green area accessibility values according to the land use for each cell, and extract the neighboring effect value according to the land use for each cell In addition, different accessibility weights, land price weights, and green area accessibility weight values are set according to the land use, and the accessibility weight, land price weight, and green area in the conversion rule indicating the conversion possibility that land can be used for different purposes for each cell. The convertibility value is extracted for each land use by applying the accessibility weight value and the neighboring effect value, and the maximum value among the extracted convertibility values and the convertibility value of the current cell land use are compared to simulate the prediction of the change in land use of the cell. It relates to a method for predicting changes in urban land use by autonomous vehicles. According to the present invention, it is possible to predict changes in land use in a city when the autonomous vehicle becomes a major means of transportation by simulation based on scenarios divided according to the degree of automation of the autonomous vehicle. Accordingly, effective urban design and policy establishment are possible. It is possible.
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