| CPC G08G 1/0125 (2013.01) [G08G 1/052 (2013.01)] | 17 Claims |
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17. A method for predicting traffic flow on a new road, the method comprising:
obtaining first training data comprising first traffic data and first traffic context data;
obtaining second training data comprising second traffic data and second traffic context data,
wherein the first training data and the second training data correspond to an existing road;
performing initial training of a prediction model using the first training data and the second training data to obtain a traffic change pattern;
generating, based at least in part on the first traffic data, the second traffic context data, and the traffic change pattern, fake traffic flow data;
analyzing, by a discriminator of the prediction model, the fake traffic flow data to obtain a unique context characteristic of a second traffic context corresponding to the second context traffic data;
setting an auxiliary loss function for the prediction model based at least in part on the fake traffic flow data;
setting a reconstruction loss function for the prediction model based at least in part on the second traffic context data and a unique existing road characteristic corresponding to the existing road;
receiving input data corresponding to the new road and comprising new road traffic data and new road default context data,
wherein the new road default context data corresponds to a particular context of the new road; and
providing the input data to the prediction model to obtain a set of outputs comprising new road traffic flow data for a set of new road traffic contexts other than the particular context,
wherein the new road traffic flow data is obtained based at least in part on the auxiliary loss function and the reconstruction loss function.
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