Risk assessment of non-stationary time series driving data based on FMK method for autonomous vehicles

Juan Du; Mian Dai; Wenbin Wang; Guoyu Zhang; Xianglei Zhu

doi:10.1117/12.2686341

10 August 2023 Risk assessment of non-stationary time series driving data based on FMK method for autonomous vehicles

Juan Du, Mian Dai, Wenbin Wang, Guoyu Zhang, Xianglei Zhu

Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 127591T (2023) https://doi.org/10.1117/12.2686341
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China

Abstract

For analyzing risk behavior based on multi-source time series data, a fuzzy Mann-Kendall method for autonomous or ADAS system equipped vehicles is proposed. With the combination of Mann-Kendall and fuzzy rules, more accurate detection of the data breakpoints, outliers, and other features are achievable, and the whole statistical patterns are fully considerable. It can eliminate ambiguity and uncertainty in driving data with assessment efficacy, can provide interoperability and compatibility, can support several data distribution with trend modes, and can modify inference rules to adapt to different data sets and application scenarios. For validating the suggested approach purpose, 200 sets of cut-in data are abstracted. By comparing the result with the actual triggering sign, the result shows the method's viability.

Citation Download Citation

Juan Du, Mian Dai, Wenbin Wang, Guoyu Zhang, and Xianglei Zhu "Risk assessment of non-stationary time series driving data based on FMK method for autonomous vehicles", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 127591T (10 August 2023); https://doi.org/10.1117/12.2686341

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