Design of a Highway Traffic Safety Assessment System Based on Crash Data Mining and Modeling

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Design of a Highway Traffic Safety Assessment System Based on Crash Data Mining and Modeling

Li, Luo / Qin, Shuolei / Qi, Weiwei

With the advent of the era of traffic information technology, traffic data appears to be extremely large, and the traditional way of managing highway crashes has become difficult to adapt to the many implications of the complicated data. In this paper, we design a highway traffic safety assessment system based on crash data mining and modeling. By constructing a visualized highway traffic crash data analysis and mining platform, which is used as a basis to gather traffic crash analysis solutions and build a think tank, a safety assessment system is formed that integrates traffic crash information visualization, crash data analysis and mining technology and comprehensive solutions for crash risk prediction. The system provides crash data pre-processing solutions, crash pattern mining solutions, factor analysis solutions and crash risk prediction solutions. Based on the above solution, the basic framework and seven main functional modules of the highway traffic safety assessment system are designed and implemented. The system achieves systematic and automated data processing, pattern mining, factor analysis and risk prediction, and aims to make highway traffic safety management more efficient.

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Document information

Title :

Design of a Highway Traffic Safety Assessment System Based on Crash Data Mining and Modeling

Additional title:

Smart Innovation, Systems and Technologies

Contributors:

Bie, Yiming (editor) / Gao, Kun (editor) / Howlett, Robert J. (editor) / Jain, Lakhmi C. (editor) / Li, Luo (author) / Qin, Shuolei (author) / Qi, Weiwei (author)

Conference:

Proceedings of KES-STS International Symposium ; 2023 ; Rome, Italy June 14, 2023 - June 16, 2023

Published in:

Smart Transportation Systems 2023 ; Chapter : 17 ; 187-198

Smart Innovation, Systems and Technologies ; 356

Publication date :

2023-06-15

Size :

12 pages

ISBN :

978-981-99-3284-9 , 978-981-99-3283-2

ISSN :