A computer implemented method for determining routing information for a navigation application comprising: receiving an observed time series of tokens, wherein each of the tokens represents an observed vehicle traffic pattern associated with a respective time period for a given road segment of a road network, the observed vehicle traffic pattern being predictable based on a variable number of past observations generated by one or more sensors, and wherein a minimum density for said each of the tokens is enforced; adding a most recent token from the observed time series of tokens into a variable token set; processing a historical token set to determine a historical token sequence comprising the variable token set followed by a next token; recursively adding a next most recent token from the observed time series of tokens into the variable token set for processing until the next token following the variable token set in the determined historical token sequence meets a target number of possible predictions, wherein determining that the next token meets the target number of possible predictions comprises: determining a count of the historical token sequence and at least one other historical token sequence that includes the variable token set followed by the next token or another next token; and determining that the count meets the target number of possible predictions; and identifying the next token as a predicted next token of the observed time series of tokens, the predicted next token representing a predicted vehicle traffic pattern for the given road segment; and determining routing information based on the predicted next token. receiving an observed time series of tokens, wherein each of the tokens represents an observed vehicle traffic pattern associated with a respective time period for a given road segment of a road network, the observed vehicle traffic pattern being predictable based on a variable number of past observations generated by one or more sensors, and wherein a minimum density for said each of the tokens is enforced; adding a most recent token from the observed time series of tokens into a variable token set; processing a historical token set to determine a historical token sequence comprising the variable token set followed by a next token; recursively adding a next most recent token from the observed time series of tokens into the variable token set for processing until the next token following the variable token set in the determined historical token sequence meets a target number of possible predictions, wherein determining that the next token meets the target number of possible predictions comprises: determining a count of the historical token sequence and at least one other historical token sequence that includes the variable token set followed by the next token or another next token; and determining that the count meets the target number of possible predictions; and determining a count of the historical token sequence and at least one other historical token sequence that includes the variable token set followed by the next token or another next token; and determining that the count meets the target number of possible predictions; and identifying the next token as a predicted next token of the observed time series of tokens, the predicted next token representing a predicted vehicle traffic pattern for the given road segment; and determining routing information based on the predicted next token. <EOS>