Citation

Yang L, Chu YX. Adv. Transp. Stud. 2023; (SI 2): 159-170.

Copyright

(Copyright © 2023, Arcane Publishers)

DOI

unavailable

PMID

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Abstract

Fast identification of road traffic safety is crucial for improving traffic safety levels. In order to improve the accuracy of road traffic safety identification and reduce the identification time, a fast identification method of road traffic safety based on WOMDI-Apriori algorithm is proposed. Based on the WOMDI-Apriori algorithm, the method searches for frequent itemsets, derives and optimizes association rules to obtain road traffic data mining results. The combination rules between road traffic data are determined, and the road traffic safety risks are classified into levels using the triangular distribution method. Based on the risk level classification results, a road traffic safety fast identification model is built. The road traffic data is inputted into the identification model to obtain relevant identification results. The experimental results show that the accuracy of road traffic safety identification using this method can reach up to 99.8%, with a maximum identification time of 6.2min, the identification recall rate varies from 96% to 100%.

Language: en

Keywords

Analysis; Models; Road Safety