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The greater the difference between vehicle speed and average vehicle speed, or the more discrete the vehicle speed distribution, the higher the accident rate. This paper proposes a vehicle speed prediction method based on adaptive KF (Kalman filtering) in the ARMA (Autoregressive Moving Average) environment to address the problem of high-speed moving vehicle speed prediction. The ARMA theory is used to model the prediction of speed time series. The contribution rate of each coefficient representing the original time series is different after fitting the original time series with the ARMA model, so each coefficient must be given a certain weight. Multisource traffic data fusion and interval speed prediction are carried out on the basis of few-shot data preprocessing and traffic state division, according to different traffic states. The speed prediction accuracy is very high, according to the algorithm verification results.<\/jats:p>","DOI":"10.1155\/2022\/2526821","type":"journal-article","created":{"date-parts":[[2022,1,20]],"date-time":"2022-01-20T01:50:05Z","timestamp":1642643405000},"page":"1-9","source":"Crossref","is-referenced-by-count":11,"title":["ARIMA Model and Few-Shot Learning for Vehicle Speed Time Series Analysis and Prediction"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8659-3382","authenticated-orcid":true,"given":"Yingzi","family":"Wang","sequence":"first","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin 300300, China"},{"name":"Automotive Data of China (Tianjin) Co., Ltd., Tianjin 300300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ce","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin 300300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jue","family":"Hou","sequence":"additional","affiliation":[{"name":"Automotive Data of China (Tianjin) Co., Ltd., Tianjin 300300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sisi","family":"Chu","sequence":"additional","affiliation":[{"name":"Automotive Data of China (Tianjin) Co., Ltd., Tianjin 300300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongjia","family":"Zhang","sequence":"additional","affiliation":[{"name":"Automotive Data of China (Tianjin) Co., Ltd., Tianjin 300300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Zhu","sequence":"additional","affiliation":[{"name":"Automotive Data of China (Tianjin) Co., Ltd., Tianjin 300300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btw131"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1109\/tsmc.2021.3131349"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcis.2020.08.052"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.12989\/sss.2018.21.5.705"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1142\/s2335680417500107"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1063\/1.5022737"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jweia.2018.01.009"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1007\/s00034-020-01610-8"},{"issue":"17","key":"9","first-page":"2751","article-title":"Time sequence analysis and application research of highway tunnel on-site monitoring","volume":"000","author":"B. 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