Abstract
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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Acknowledgements
This work was supported by the National Natural Science Foundation of China (No. 52072131), the Key Research Projects of Universities in Guangdong Province (No. 2019KZDXM009), the Natural Science Foundation of Guangdong Province (No. 2023A1515010039).
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Li, L., Qin, S., Qi, W. (2023). Design of a Highway Traffic Safety Assessment System Based on Crash Data Mining and Modeling. In: Bie, Y., Gao, K., Howlett, R.J., Jain, L.C. (eds) Smart Transportation Systems 2023. KES-STS 2023. Smart Innovation, Systems and Technologies, vol 356. Springer, Singapore. https://doi.org/10.1007/978-981-99-3284-9_17
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DOI: https://doi.org/10.1007/978-981-99-3284-9_17
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