{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T00:42:47Z","timestamp":1760229767379,"version":"build-2065373602"},"reference-count":49,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T00:00:00Z","timestamp":1656374400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2020MF082","IGSD-2020-012","19-3-2-11-zhc","2018YFB1601500"],"award-info":[{"award-number":["ZR2020MF082","IGSD-2020-012","19-3-2-11-zhc","2018YFB1601500"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Collaborative Innovation Center for Intelligent Green Manufacturing Technology and Equipment of Shandong Province","award":["ZR2020MF082","IGSD-2020-012","19-3-2-11-zhc","2018YFB1601500"],"award-info":[{"award-number":["ZR2020MF082","IGSD-2020-012","19-3-2-11-zhc","2018YFB1601500"]}]},{"name":"Qingdao Top Talent Program of Entrepreneurship and Innovation","award":["ZR2020MF082","IGSD-2020-012","19-3-2-11-zhc","2018YFB1601500"],"award-info":[{"award-number":["ZR2020MF082","IGSD-2020-012","19-3-2-11-zhc","2018YFB1601500"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"publisher","award":["ZR2020MF082","IGSD-2020-012","19-3-2-11-zhc","2018YFB1601500"],"award-info":[{"award-number":["ZR2020MF082","IGSD-2020-012","19-3-2-11-zhc","2018YFB1601500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Driving propensity is the driver\u2019s attitude towards the actual traffic situation and the corresponding decision-making or behavior during the driving process. It is of great significance to improve the accuracy of safety early warning and reduce traffic accidents. In this paper, a real-time identification system of driving propensity based on AutoNavi navigation data is proposed. The main work includes: (1) A dynamic data acquisition method of AutoNavi navigation is proposed to obtain the time, speed and acceleration of the driver during the navigation process. (2) The dynamic data collection method of AutoNavi navigation is analyzed and verified through the dynamic data obtained in the real vehicle experiment. The principal component analysis method is used to process the experimental data to extract the driving propensity characteristics variables. (3) The fruit fly optimization algorithm combined with GRNN (generalized neural network) and the feature variable set are used to build a FOA-GRNN-based model. The results show that the overall accuracy of the model can reach 94.17%. (4) A driving propensity identification system is constructed. The system has been verified through real vehicle test experiments. This paper provides a novel and convenient method for building personalized intelligent driver assistance systems in practical applications.<\/jats:p>","DOI":"10.3390\/s22134883","type":"journal-article","created":{"date-parts":[[2022,6,29]],"date-time":"2022-06-29T01:48:38Z","timestamp":1656467318000},"page":"4883","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Real-Time Recognition System of Driving Propensity Based on AutoNavi Navigation Data"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2418-7394","authenticated-orcid":false,"given":"Xiaoyuan","family":"Wang","sequence":"first","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China"},{"name":"Collaborative Innovation Center for Intelligent Green Manufacturing Technology and Equipment of Shandong, Qingdao 266000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0065-1001","authenticated-orcid":false,"given":"Longfei","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huili","family":"Shi","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junyan","family":"Han","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quanzheng","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fusheng","family":"Zhong","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Li","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4444","DOI":"10.1109\/TITS.2019.2940481","article-title":"A comprehensive review of driver behavior analysis utilizing smartphones","volume":"21","author":"Chan","year":"2019","journal-title":"IEEE Trans. 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