Research Article
Road Traffic Safety Risk Estimation Method Based on Vehicle Onboard Diagnostic Data
Algorithm 1
Level threshold optimization algorithm (“⟵” represents value assignment).
| (1) | int r ⟵ k-means number of clusters | | (2) | For int t = 1 to r − 1 | | (3) | int at ⟵ Safety entropy value of the center of the tth cluster | | (4) | int bt ⟵ Safety entropy value of the center of the (t + 1)th cluster | | (5) | int st ⟵ Sum of the data in the tth and (t + 1)th clusters | | (6) | int f = 1 | | (7) | For float etf = at to bt | | (8) | int ctf ⟵ Volume of data in the tth cluster that is misclassified | | (9) | int dtf ⟵ Volume of data in the (t + 1)th cluster that is misclassified | | (10) | = 1 − ((ctf + dtf)/st)//Calculation of accuracy | | (11) | etf = etf + 0.01 | | (12) | Bt (f, 1: 2) = [etf, ]//The threshold and accuracy are stored in the matrix Bt | | (13) | f = f + 1 | | (14) | End for | | (15) | Ct ⟵ Generation of the threshold corresponding to the highest accuracy | | (16) | End for | | (17) | C = [C1, C2, …, Cr − 1]//A number of thresholds (r − 1) is successively stored in the vector C |
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