{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:42:33Z","timestamp":1754156553964,"version":"3.41.2"},"reference-count":30,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2021,2,25]],"date-time":"2021-02-25T00:00:00Z","timestamp":1614211200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJICC"],"published-print":{"date-parts":[[2021,4,23]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>In response to these shortcomings, this paper proposes a dynamic obstacle detection and tracking method based on multi-feature fusion and a dynamic obstacle recognition method based on spatio-temporal feature vectors.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>The existing dynamic obstacle detection and tracking methods based on geometric features have a high false detection rate. The recognition methods based on the geometric features and motion status of dynamic obstacles are greatly affected by distance and scanning angle, and cannot meet the requirements of real traffic scene applications.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>First, based on the geometric features of dynamic obstacles, the obstacles are considered The echo pulse width feature is used to improve the accuracy of obstacle detection and tracking; second, the space-time feature vector is constructed based on the time dimension and space dimension information of the obstacle, and then the support vector machine method is used to realize the recognition of dynamic obstacles to improve the obstacle The accuracy of object recognition. Finally, the accuracy and effectiveness of the proposed method are verified by real vehicle tests.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>The paper proposes a dynamic obstacle detection and tracking method based on multi-feature fusion and a dynamic obstacle recognition method based on spatio-temporal feature vectors. The accuracy and effectiveness of the proposed method are verified by real vehicle tests.<\/jats:p><\/jats:sec>","DOI":"10.1108\/ijicc-10-2020-0143","type":"journal-article","created":{"date-parts":[[2021,2,23]],"date-time":"2021-02-23T07:22:16Z","timestamp":1614064936000},"page":"239-251","source":"Crossref","is-referenced-by-count":6,"title":["Unmanned vehicle dynamic obstacle detection, tracking and recognition method based on laser sensor"],"prefix":"10.1108","volume":"14","author":[{"given":"Hualei","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6148-1555","authenticated-orcid":false,"given":"Mohammad Asif","family":"Ikbal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2021,2,25]]},"reference":[{"volume-title":"Association of State Highway and Transportation Officials; Highway Safety Manual","year":"2010","author":"AASHTO American","key":"key2022121313515604300_ref001"},{"key":"key2022121313515604300_ref002","first-page":"1","article-title":"Reliability and test effort analysis of multi-sensor driver assistance systems","volume":"85","year":"2018","journal-title":"Journal of Systems Architecture"},{"first-page":"1","article-title":"A large-scale mapping method based on deep neural networks applied to self-driving car localization","year":"2020","key":"key2022121313515604300_ref003"},{"issue":"14","key":"key2022121313515604300_ref004","doi-asserted-by":"crossref","first-page":"3948","DOI":"10.3390\/s20143948","article-title":"A method of multiple dynamic objects identification and localization based on laser and RFID","volume":"20","year":"2020","journal-title":"Sensors"},{"issue":"1","key":"key2022121313515604300_ref005","first-page":"5","article-title":"Ruggedized and improved mems-based sensors for rolling stock","volume":"22","year":"2019","journal-title":"International Journal of Comadem"},{"article-title":"Obstacle detection and track detection in autonomous cars","volume-title":"Autonomous Vehicle and Smart Traffic","year":"2020","key":"key2022121313515604300_ref006"},{"issue":"12","key":"key2022121313515604300_ref007","doi-asserted-by":"crossref","first-page":"11420","DOI":"10.1109\/TVT.2018.2870995","article-title":"Design of collision detection system for smart car using li-fi and ultrasonic sensor","volume":"67","year":"2018","journal-title":"IEEE Transactions on Vehicular Technology"},{"issue":"11","key":"key2022121313515604300_ref008","article-title":"Obstacle information detection method based on multiframe three-dimensional lidar point cloud fusion","volume":"58","year":"2019","journal-title":"Optical Engineering"},{"key":"key2022121313515604300_ref009","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3023189","article-title":"Airborne LiDAR assisted obstacle recognition and intrusion detection towards unmanned aerial vehicle: architecture, modeling and evaluation","year":"2020","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"issue":"2","key":"key2022121313515604300_ref010","doi-asserted-by":"crossref","first-page":"456","DOI":"10.3390\/s18020456","article-title":"Deep learning-based gaze detection system for automobile drivers using a nir camera sensor","volume":"18","year":"2018","journal-title":"Sensors"},{"journal-title":"Advances in Civil Engineering","article-title":"The feasibility assessment study of bridge crack width recognition in images based on special inspection UAV","year":"2020","key":"key2022121313515604300_ref011"},{"first-page":"172","article-title":"Design of intrusion detection and prevention system (IDPS) using DGSOTFC in collaborative protection networks","year":"2013","key":"key2022121313515604300_ref012"},{"issue":"2","key":"key2022121313515604300_ref013","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/IJISP.2014040101","article-title":"A firegroup mechanism to provide intrusion detection and prevention system against DDoS attack in collaborative clustered networks","volume":"8","year":"2014","journal-title":"International Journal of Information Security and Privacy"},{"issue":"6","key":"key2022121313515604300_ref014","first-page":"574","article-title":"The COLLID based intrusion detection system for detection against DDOS attacks using trust evaluation","volume":"9","year":"2015","journal-title":"Advances in Natural and Applied Sciences"},{"issue":"4","key":"key2022121313515604300_ref015","doi-asserted-by":"crossref","first-page":"1549","DOI":"10.1007\/s10586-015-0496-y","article-title":"Stochastic model: reCAPTCHA controller based co-variance matrix analysis on frequency distribution using trust evaluation and re-eval by Aumann agreement theorem against DDoS attack in MANET","volume":"18","year":"2015","journal-title":"Cluster Computing"},{"key":"key2022121313515604300_ref016","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.procs.2015.04.053","article-title":"Detection and Prevention system towards the truth of convergence on decision using Aumann agreement theorem","volume":"50","year":"2015","journal-title":"Procedia Computer Science"},{"issue":"12","key":"key2022121313515604300_ref017","doi-asserted-by":"crossref","first-page":"3583","DOI":"10.1007\/s13369-015-1822-7","article-title":"A novel intrusion detection system based on trust evaluation to defend against DDoS attack in MANET","volume":"40","year":"2015","journal-title":"Arabian Journal for Science and Engineering"},{"issue":"4","key":"key2022121313515604300_ref018","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1504\/IJENM.2015.073869","article-title":"The effective intrusion detection system using optimal feature selection algorithm","volume":"6","year":"2015","journal-title":"International Journal of Enterprise Network Management"},{"issue":"22","key":"key2022121313515604300_ref019","first-page":"233","article-title":"The probabilistic approach of energy utility and reusability model with enhanced security from the compromised nodes through wireless energy transfer in WSN","volume":"116","year":"2017","journal-title":"International Journal of Pure and Applied Mathematics"},{"issue":"2","key":"key2022121313515604300_ref020","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TITS.2018.2826571","article-title":"Vehicle energy\/emissions estimation based on vehicle trajectory reconstruction using sparse mobile sensor data","volume":"20","year":"2019","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"year":"2017","key":"key2022121313515604300_ref021","article-title":"An optimal routing scheme for critical healthcare HTH services\u2014an IOT perspective"},{"issue":"6","key":"key2022121313515604300_ref022","first-page":"73","article-title":"A framework for pre-computated multi-constrained quickest qos path algorithm","volume":"93","year":"2017","journal-title":"Journal of Telecommunication, Electronic and Computer Engineering"},{"issue":"4","key":"key2022121313515604300_ref023","doi-asserted-by":"crossref","first-page":"3831","DOI":"10.1007\/s13369-018-3687-z","article-title":"Service-level agreement\u2014energy cooperative quickest ambulance routing for critical healthcare services","volume":"44","year":"2019","journal-title":"Arabian Journal for Science and Engineering"},{"issue":"1","key":"key2022121313515604300_ref025","article-title":"Front obstacle detection system based on YOLOv3","volume":"1732","year":"2021","journal-title":"Journal of Physics: Conference Series"},{"journal-title":"Journal of Advanced Transportation 2020","article-title":"A front water recognition method based on image data for off-road intelligent vehicle","year":"2020","key":"key2022121313515604300_ref024"},{"journal-title":"Computer Communications","article-title":"Multi-sensor detection and control network technology based on parallel computing model in robot target detection and recognition","year":"2020","key":"key2022121313515604300_ref026"},{"issue":"March","key":"key2022121313515604300_ref027","doi-asserted-by":"publisher","DOI":"10.1177\/1729881419831587","article-title":"Obstacle detection and tracking method for autonomous vehicle based on three-dimensional LiDAR","year":"2019","journal-title":"International Journal of Advanced Robotic Systems"},{"volume-title":"U.S. Patent No. 10,670,701","year":"2020","key":"key2022121313515604300_ref028"},{"issue":"1-2","key":"key2022121313515604300_ref029","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/s10710-017-9313-0","article-title":"Hod lipson and melba kurman: driverless: intelligent cars and the road ahead","volume":"19","year":"2018","journal-title":"Genetic Programming and Evolvable Machines"},{"issue":"5","key":"key2022121313515604300_ref030","doi-asserted-by":"crossref","first-page":"602","DOI":"10.20965\/jaciii.2018.p0602","article-title":"Dynamic obstacle detection and tracking based on 3D lidar","volume":"22","year":"2018","journal-title":"Journal of Advanced Computational Intelligence and Intelligent Informatics"}],"container-title":["International Journal of Intelligent Computing and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJICC-10-2020-0143\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJICC-10-2020-0143\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T22:54:59Z","timestamp":1753397699000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/ijicc\/article\/14\/2\/239-251\/125672"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,25]]},"references-count":30,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,2,25]]},"published-print":{"date-parts":[[2021,4,23]]}},"alternative-id":["10.1108\/IJICC-10-2020-0143"],"URL":"https:\/\/doi.org\/10.1108\/ijicc-10-2020-0143","relation":{},"ISSN":["1756-378X"],"issn-type":[{"type":"print","value":"1756-378X"}],"subject":[],"published":{"date-parts":[[2021,2,25]]}}}