Discrimination and localization method of vehicles in the foggy environment based on fuzzy k-means algorithm

ShangYi Zhang; YaWen Sun; ZhenFeng Long; ZeHao Yin; WenPeng Hao; XingXing Liang; Yi Jiang; BoJiang Li

doi:10.1117/12.2674880

2 May 2023 Discrimination and localization method of vehicles in the foggy environment based on fuzzy k-means algorithm

ShangYi Zhang, YaWen Sun, ZhenFeng Long, ZeHao Yin, WenPeng Hao, XingXing Liang, Yi Jiang, BoJiang Li

Proceedings Volume 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023); 1264221 (2023) https://doi.org/10.1117/12.2674880
Event: Second International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT 2023), 2023, Xishuangbanna, China

Abstract

This method proposes to first detect the features of moving objects driving on foggy roads, then compare and screen the detected feature data with the sample feature set through the Kalman filter algorithm, and then use the fuzzy k-means algorithm to classify and mark the cleaned vehicles, and at the same time obtain a more accurate feature vector interval, update the feature sample set in time, and finally send the analysis results to the control end and start the warning light for warning: in this method, the laser distance sensor detects the occlusion duration of the vehicle's tires, the occlusion interval time of adjacent tire groups, the vehicle running speed and the distance between the vehicle and the detector to judge the vehicle. This method can timely inform the driver of the information of the vehicle in front of the foggy road in advance and reduce the incidence of traffic accidents.

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ShangYi Zhang, YaWen Sun, ZhenFeng Long, ZeHao Yin, WenPeng Hao, XingXing Liang, Yi Jiang, and BoJiang Li "Discrimination and localization method of vehicles in the foggy environment based on fuzzy k-means algorithm", Proc. SPIE 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023), 1264221 (2 May 2023); https://doi.org/10.1117/12.2674880

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KEYWORDS

Fuzzy logic

Detection and tracking algorithms

Environmental sensing

Signal filtering

Matrices

Motion detection

Engineering

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