Title: Real-time road transportation safety risk evaluation model based on data-mining

Authors: Wenhui Luo; Xingkai Meng; Fengtian Cai; Chuna Wu

Addresses: Research Institute of Highway Ministry of Transport, Beijing 100088, China ' Research Institute of Highway Ministry of Transport, Beijing 100088, China ' Research Institute of Highway Ministry of Transport, Beijing 100088, China ' Research Institute of Highway Ministry of Transport, Beijing 100088, China

Abstract: Aiming at the shortcoming of the massive amount of manual work required and the result relay on the cognitive level of experts the process cannot be implemented dynamically. A real-time road transportation safety risk evaluation model based on data-mining is proposed in this paper. Firstly, the pre-processing of unstructured text contains process of adding custom item dictionary, deletion of stop words, word segmentation of text at the beginning process, then dynamic risk factors identification using TF-IDF on processed text. Secondly, accident chains extraction by cue words and causal sentence structure construction. Thirdly, the relevance mining among risk factors or accident states through Apriori-algorithm. Finally, real-time risk assessment is realised by classification of the product of obtained probability and severity degree result using K-means. Experiments are conducted on text data set, and the result shows that the accuracy of proposed model is 88%, which is an effective safety risk evaluation model.

Keywords: road engineering; risk real-time evaluation model; data-mining; safety risk; Apriori; K-means.

DOI: 10.1504/IJWMC.2021.114140

International Journal of Wireless and Mobile Computing, 2021 Vol.20 No.2, pp.168 - 178

Received: 28 Sep 2020
Accepted: 16 Dec 2020
Published online: 09 Apr 2021 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article