{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T19:20:15Z","timestamp":1754162415566,"version":"3.41.2"},"reference-count":29,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Internet of Things (IoT) is a physical network of physical devices, such as widgets, structures, and other objects, which can store program, sensors, actuators, and screen configurations to allow the objects to assemble, control, display, and exchange data. The aim of this research was to develop an autonomous system with automated navigation. Using this approach, we are able to make use of deep neural networks for automatic navigation as well as the identification of pot holes and road conditions. Additionally, it displays potholes in traffic and the correct lane on the screen. The system stresses how important it is to select the path from one node to the next.<\/jats:p>","DOI":"10.1515\/pjbr-2022-0117","type":"journal-article","created":{"date-parts":[[2023,8,15]],"date-time":"2023-08-15T06:50:43Z","timestamp":1692082243000},"source":"Crossref","is-referenced-by-count":1,"title":["Path reader and intelligent lane navigator by autonomous vehicle"],"prefix":"10.1515","volume":"14","author":[{"given":"Amar","family":"Shukla","sequence":"first","affiliation":[{"name":"School of Computer Science, University of Petroleum and Energy Studies (UPES) , Dehradun , 248007, Uttarakhand , India"}]},{"given":"Ankit","family":"Verma","sequence":"additional","affiliation":[{"name":"Wartin Labs Technologies LLP , H-187 WorkWings , Noida , Uttar Pradesh 201301 , India"}]},{"given":"Hussain Falih","family":"Mahdi","sequence":"additional","affiliation":[{"name":"Computer and Software, College of Engineering, University of Diyala , Baqubah , Iraq"}]},{"given":"Tanupriya","family":"Choudhury","sequence":"additional","affiliation":[{"name":"CSE Department, Symbiosis Institute of Technology, Symbiosis International University , Pune , Maharashtra, 412115 , India"},{"name":"School of Computer Science, University of Petroleum and Energy Studies (UPES) , Dehradun , 248007, Uttarakhand , India"},{"name":"CSE Department, Daffodil International University , Daffodil Smart City , Birulia 1216 , Bangladesh"},{"name":"CSE Department, Graphic Era Hill University , Dehradun , 248002, Uttarakhand , India"}]},{"given":"Thipendra Pal","family":"Singh","sequence":"additional","affiliation":[{"name":"School of Computer Science Engineering and Technology, Bennett University , Greater Noida , Uttar Pradesh 201310 , India"},{"name":"School of Computer Science, University of Petroleum and Energy Studies (UPES) , Dehradun , 248007, Uttarakhand , India"}]}],"member":"374","published-online":{"date-parts":[[2023,8,15]]},"reference":[{"key":"2025073006061539494_j_pjbr-2022-0117_ref_001","doi-asserted-by":"crossref","unstructured":"J. Borenstein and Y. Koren, \u201cObstacle avoidance with ultrasonic sensors,\u201d IEEE J. Robot. Autom., vol. 4, no. 2, pp. 213\u2013218, 1988.","DOI":"10.1109\/56.2085"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_002","doi-asserted-by":"crossref","unstructured":"Y. Wang, E. K. Teoh, and D. Shen, \u201cLane detection and tracking using B-Snake,\u201d Image Vis. Comput., vol. 22, no. 4, pp. 269\u2013280, 2004.","DOI":"10.1016\/j.imavis.2003.10.003"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_003","doi-asserted-by":"crossref","unstructured":"N. P. Pawar and M. M. Patil, \u201cDriver assistance system based on Raspberry Pi,\u201d Int. J. Comput. Appl., vol. 95, no. 16, p. 16, 2014.","DOI":"10.5120\/16682-6794"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_004","doi-asserted-by":"crossref","unstructured":"T. D. Do, M. T. Duong, Q. V. Dang, and M. H. 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Rus, \u201cAutonomous vehicle navigation in rural environments without detailed prior maps,\u201d In 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, pp. 2040\u20132047.","DOI":"10.1109\/ICRA.2018.8460519"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_014","doi-asserted-by":"crossref","unstructured":"N. Adnan, S. M. Nordin, M. A. bin Bahruddin, and M. Ali, \u201cHow trust can drive forward the user acceptance to the technology? In-vehicle technology for autonomous vehicle,\u201d Transportation Res. Part. A: Policy Pract., vol. 118, pp. 819\u2013836, 2018.","DOI":"10.1016\/j.tra.2018.10.019"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_015","doi-asserted-by":"crossref","unstructured":"J. Jiang and A. Astolfi, \u201cLateral control of an autonomous vehicle,\u201d IEEE Trans. Intell. Veh., vol. 3, no. 2, pp. 228\u2013237, 2018.","DOI":"10.1109\/TIV.2018.2804173"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_016","doi-asserted-by":"crossref","unstructured":"J. Fayyad, M. A. Jaradat, D. Gruyer, and H. Najjaran, \u201cDeep learning sensor fusion for autonomous vehicle perception and localization: A review,\u201d Sensors, vol. 20, no. 15, pp. 4220\u20134220, 2020.","DOI":"10.3390\/s20154220"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_017","doi-asserted-by":"crossref","unstructured":"H. Gao, B. Cheng, J. Wang, K. Li, J. Zhao, and D. Li, \u201cObject classification using CNN-based fusion of vision and LIDAR in autonomous vehicle environment,\u201d IEEE Trans. Ind. Inform., vol. 14, no. 9, pp. 4224\u20134231, 2018.","DOI":"10.1109\/TII.2018.2822828"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_018","doi-asserted-by":"crossref","unstructured":"M. Khayyat, A. Alshahrani, S. Alharbi, I. Elgendy, A. Paramonov, and A. Koucheryavy, \u201cMultilevel service-provisioning-based autonomous vehicle applications,\u201d Sustainability, vol. 12, no. 6. p. 2497, 2020.","DOI":"10.3390\/su12062497"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_019","doi-asserted-by":"crossref","unstructured":"R. McCall, F. McGee, A. Mirnig, A. Meschtscherjakov, N. Louveton, T. Engel, et al., \u201c A taxonomy of autonomous vehicle handover situations,\u201d Transportation Res. Part. A: Policy Pract., vol. 124, pp. 507\u2013522, 2019.","DOI":"10.1016\/j.tra.2018.05.005"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_020","doi-asserted-by":"crossref","unstructured":"S. A. Fayazi and A. Vahidi, \u201cMixed-integer linear programming for optimal scheduling of autonomous vehicle intersection crossing,\u201d IEEE Trans. Intell. Veh., vol. 3, no. 3, pp. 287\u2013299, 2018.","DOI":"10.1109\/TIV.2018.2843163"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_021","unstructured":"D. Stanek, R. T. Milam, E. Huang, and Y. A. Wang, Measuring autonomous vehicle impacts on congested networks using simulation. Transportation Research Board 97th Annual Meeting; 2018."},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_022","doi-asserted-by":"crossref","unstructured":"A. Best, S. Narang, L. Pasqualin, D. Barber, and D. Manocha, \u201cAutonovi-sim: Autonomous vehicle simulation platform with weather, sensing, and traffic control,\u201d In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018, pp. 1048\u20131056.","DOI":"10.1109\/CVPRW.2018.00152"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_023","doi-asserted-by":"crossref","unstructured":"X. He, Y. Liu, C. Lv, X. Ji, and Y. Liu, \u201cEmergency steering control of autonomous vehicle for collision avoidance and stabilisation,\u201d Veh. Syst. Dyn., vol. 57, no. 8, pp. 1163\u20131187, 2019.","DOI":"10.1080\/00423114.2018.1537494"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_024","doi-asserted-by":"crossref","unstructured":"C. Sun, X. Zhang, Q. Zhou, and Y. Tian, \u201cA model predictive controller with switched tracking error for autonomous vehicle path tracking,\u201d IEEE Access, vol. 7, pp. 53103\u201353114, 2019.","DOI":"10.1109\/ACCESS.2019.2912094"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_025","doi-asserted-by":"crossref","unstructured":"Y. Jeong, S. Son, E. Jeong, and B. Lee, \u201cAn integrated selfdiagnosis system for an autonomous vehicle based on an IoT gateway and deep learning,\u201d Appl. Sci., vol. 8, no. 7, p. 1164, 2018.","DOI":"10.3390\/app8071164"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_026","doi-asserted-by":"crossref","unstructured":"K. Lee, S. Jeon, H. Kim, and D. Kum, \u201cOptimal path tracking control of autonomous vehicle: Adaptive full-state linear quadratic Gaussian (LQG) control,\u201d IEEE Access, vol. 7, pp. 109120\u2013109133, 2019.","DOI":"10.1109\/ACCESS.2019.2933895"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_027","doi-asserted-by":"crossref","unstructured":"H. Fazlollahtabar and S. Hassanli, \u201cHybrid cost and time path planning for multiple autonomous guided vehicles,\u201d Appl. Intell., vol. 48, no. 2, pp. 482\u2013498, 2018.","DOI":"10.1007\/s10489-017-0997-x"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_028","doi-asserted-by":"crossref","unstructured":"B. Sebastian and P. Ben-Tzvi, \u201cPhysics based path planning for autonomous tracked vehicle in challenging terrain,\u201d J. Intell. Robotic Syst., vol. 95, no. 2, pp. 511\u2013526, 2019.","DOI":"10.1007\/s10846-018-0851-3"},{"key":"2025073006061539494_j_pjbr-2022-0117_ref_029","doi-asserted-by":"crossref","unstructured":"Q. Wang, B. Ayalew, and T. 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