{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T12:18:44Z","timestamp":1766578724251,"version":"3.37.3"},"reference-count":31,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T00:00:00Z","timestamp":1638403200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51905320","2018M632696","2018M642684","2019GGX104066","2017ZBXC133"],"award-info":[{"award-number":["51905320","2018M632696","2018M642684","2019GGX104066","2017ZBXC133"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["51905320","2018M632696","2018M642684","2019GGX104066","2017ZBXC133"],"award-info":[{"award-number":["51905320","2018M632696","2018M642684","2019GGX104066","2017ZBXC133"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shandong Key R&D Plan Project","award":["51905320","2018M632696","2018M642684","2019GGX104066","2017ZBXC133"],"award-info":[{"award-number":["51905320","2018M632696","2018M642684","2019GGX104066","2017ZBXC133"]}]},{"DOI":"10.13039\/501100017606","name":"Shandong University of Technology","doi-asserted-by":"publisher","award":["51905320","2018M632696","2018M642684","2019GGX104066","2017ZBXC133"],"award-info":[{"award-number":["51905320","2018M632696","2018M642684","2019GGX104066","2017ZBXC133"]}],"id":[{"id":"10.13039\/501100017606","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Robotics"],"published-print":{"date-parts":[[2021,12,2]]},"abstract":"<jats:p>The existing automatic parking algorithms often neglect the unknown obstacles in the parking environment, which causes a hidden danger to the safety of the automatic parking system. Therefore, this paper proposes parking space detection and path planning based on the VIDAR method (vision-IMU-based detection and range method) to solve the problem. In the parking space detection stage, the generalized obstacles are detected based on VIDAR to determine the obstacle areas, and then parking lines are detected by the Hough transform to determine the empty parking space. Compared with the parking detection method based on YOLO v5, the experimental results demonstrate that the proposed method has higher accuracy in complex parking environments with unknown obstacles. In the path planning stage, the path optimization algorithm of the <jats:inline-formula>\n                     <a:math xmlns:a=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\">\n                        <a:msup>\n                           <a:mrow>\n                              <a:mi>A<\/a:mi>\n                           <\/a:mrow>\n                           <a:mi>\u2217<\/a:mi>\n                        <\/a:msup>\n                     <\/a:math>\n                  <\/jats:inline-formula> algorithm combined with the Bezier curve is used to generate smooth curves, and the environmental information is updated in real time based on VIDAR. The simulation results show that the method can make the vehicle efficiently avoid the obstacles and generate a smooth path in a dynamic parking environment, which can well meet the safety and stationarity of the parking requirements.<\/jats:p>","DOI":"10.1155\/2021\/4943316","type":"journal-article","created":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T20:35:14Z","timestamp":1638477314000},"page":"1-15","source":"Crossref","is-referenced-by-count":1,"title":["Parking Space Detection and Path Planning Based on VIDAR"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4215-1993","authenticated-orcid":true,"given":"Yi","family":"Xu","sequence":"first","affiliation":[{"name":"School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China"},{"name":"Collaborative Innovation Center of New Energy Automotive, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2039-5666","authenticated-orcid":true,"given":"Shanshang","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6581-8848","authenticated-orcid":true,"given":"Guoxin","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8611-4265","authenticated-orcid":true,"given":"Xiaotong","family":"Gong","sequence":"additional","affiliation":[{"name":"School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1275-8030","authenticated-orcid":true,"given":"Hongxue","family":"Li","sequence":"additional","affiliation":[{"name":"School of Vehicle and Energy, Yanshan University, Qinhuangdao 066000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4168-3760","authenticated-orcid":true,"given":"Xiaoqing","family":"Sang","sequence":"additional","affiliation":[{"name":"School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9415-7778","authenticated-orcid":true,"given":"Liming","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2821-0312","authenticated-orcid":true,"given":"Ruoyu","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8624-7298","authenticated-orcid":true,"given":"Yuqiong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/847406"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1117\/1.oe.52.3.037203"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/smc.2017.8123081"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1109\/icme.2017.8019419"},{"issue":"4","key":"5","first-page":"935","article-title":"Detection method for parking spaces based on mini-convolution neural network","volume":"38","author":"X. 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