{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T06:26:34Z","timestamp":1773037594459,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,6]],"date-time":"2023-01-06T00:00:00Z","timestamp":1672963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Connected and autonomous vehicles (CAVs) have witnessed significant attention from industries, and academia for research and developments towards the on-road realisation of the technology. State-of-the-art CAVs utilise existing navigation systems for mobility and travel path planning. However, reliable connectivity to navigation systems is not guaranteed, particularly in urban road traffic environments with high-rise buildings, nearby roads and multi-level flyovers. In this connection, this paper presents TAKEN-Traffic Knowledge-based Navigation for enabling CAVs in urban road traffic environments. A traffic analysis model is proposed for mining the sensor-oriented traffic data to generate a precise navigation path for the vehicle. A knowledge-sharing method is developed for collecting and generating new traffic knowledge from on-road vehicles. CAVs navigation is executed using the information enabled by traffic knowledge and analysis. The experimental performance evaluation results attest to the benefits of TAKEN in the precise navigation of CAVs in urban traffic environments.<\/jats:p>","DOI":"10.3390\/s23020653","type":"journal-article","created":{"date-parts":[[2023,1,6]],"date-time":"2023-01-06T03:54:49Z","timestamp":1672977289000},"page":"653","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["TAKEN: A Traffic Knowledge-Based Navigation System for Connected and Autonomous Vehicles"],"prefix":"10.3390","volume":"23","author":[{"given":"Nikhil","family":"Kamath B","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, NMAM Institute of Technology, NITTE (Deemed to be University), Nitte 574110, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7625-3296","authenticated-orcid":false,"given":"Roshan","family":"Fernandes","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, NMAM Institute of Technology, NITTE (Deemed to be University), Nitte 574110, India"}]},{"given":"Anisha P.","family":"Rodrigues","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, NMAM Institute of Technology, NITTE (Deemed to be University), Nitte 574110, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2037-8348","authenticated-orcid":false,"given":"Mufti","family":"Mahmud","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Computing and Informatics Research Centre, and Medical Technologies Innovation Facility, Nottingham Trent University, Clifton Lane, Nottingham NG11 8NS, UK"}]},{"given":"P.","family":"Vijaya","sequence":"additional","affiliation":[{"name":"Department of Mathematics and CS, Modern College of Business and Science Bowshar, Muscat 133, Oman"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0097-801X","authenticated-orcid":false,"given":"Thippa Reddy","family":"Gadekallu","sequence":"additional","affiliation":[{"name":"Department of Information Technology Vellore Institute of Technology, Vellore 632014, India"},{"name":"Department of Electrical and Computer Engineering, Lebanese American University, Byblos 13-5053, Lebanon"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4604-5461","authenticated-orcid":false,"given":"M. Shamim","family":"Kaiser","sequence":"additional","affiliation":[{"name":"Institute of Information Technology, Jahangirnagar University, Dhaka 1342, Bangladesh"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,6]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Human-machine interaction in intelligent and connected vehicles: A review of status quo, issues and opportunities","volume":"23","author":"Tan","year":"2021","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Dhawankar, P., Agrawal, P., Abderezzak, B., Kaiwartya, O., Busawon, K., and Raboaca, M.S. (2021). Design and numerical implementation of v2x control architecture for autonomous driving vehicles. Mathematics, 9.","DOI":"10.3390\/math9141696"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"5356","DOI":"10.1109\/ACCESS.2016.2603219","article-title":"Internet of vehicles: Motivation, layered architecture, network model, challenges, and future aspects","volume":"4","author":"Kaiwartya","year":"2016","journal-title":"IEEE Access"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Gao, Y., Jing, H., Dianati, M., Hancock, C.M., and Meng, X. (2022). Performance analysis of robust cooperative positioning based on gps\/uwb integration for connected autonomous vehicles. IEEE Trans. Intell. Veh., 1.","DOI":"10.1109\/TIV.2022.3144341"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3800","DOI":"10.1109\/TVT.2018.2796242","article-title":"Geometry-based localization for gps outage in vehicular cyber physical systems","volume":"67","author":"Kaiwartya","year":"2018","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3644","DOI":"10.1109\/TITS.2020.3028695","article-title":"Green computing in software defined social internet of vehicles","volume":"22","author":"Kumar","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"51005","DOI":"10.1109\/ACCESS.2021.3063463","article-title":"Traffic flow management of autonomous vehicles using deep reinforcement learning and smart rerouting","volume":"9","author":"Mushtaq","year":"2021","journal-title":"IEEE Access"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1109\/TIV.2018.2886684","article-title":"Minimizing traffic congestion through continuous-time route reservations with travel time predictions","volume":"4","author":"Menelaou","year":"2018","journal-title":"IEEE Trans. Intell. Veh."},{"key":"ref_9","unstructured":"GOV.UK (2022, May 20). Connected and Automated Vehicles: Market Forecast 2020, Available online: https:\/\/www.gov.uk\/government\/publications\/connected-and-automated-vehicles-market-forecast-2020."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1109\/JIOT.2020.3006527","article-title":"Toward physical-layer security for internet of vehicles: Interference-aware modeling","volume":"8","author":"Makarfi","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3092","DOI":"10.1109\/TITS.2017.2771746","article-title":"Advances in crowd analysis for urban applications through urban event detection","volume":"19","author":"Kaiser","year":"2017","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1109\/6979.994793","article-title":"Quintic g\/sup 2\/-splines for the iterative steering of vision-based autonomous vehicles","volume":"3","author":"Piazzi","year":"2002","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1109\/TITS.2010.2046037","article-title":"Maneuver-based trajectory planning for highly autonomous vehicles on real road with traffic and driver interaction","volume":"11","author":"Glaser","year":"2010","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1109\/TVT.2012.2186991","article-title":"Path following of autonomous vehicles in the presence of sliding effects","volume":"61","author":"Arogeti","year":"2012","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2063","DOI":"10.1109\/TNNLS.2018.2790388","article-title":"Applications of deep learning and reinforcement learning to biological data","volume":"29","author":"Mahmud","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12559-020-09773-x","article-title":"Deep learning in mining biological data","volume":"13","author":"Mahmud","year":"2021","journal-title":"Cogn. Comput."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"27779","DOI":"10.1109\/JSEN.2021.3124788","article-title":"This is the way: Sensors auto-calibration approach based on deep learning for self-driving cars","volume":"21","author":"Wu","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1109\/OJITS.2021.3083201","article-title":"A reinforcement learning framework for video frame-based autonomous car-following","volume":"2","author":"Masmoudi","year":"2021","journal-title":"IEEE Open J. Intell. Transp. Syst."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2862","DOI":"10.1109\/TITS.2020.2976572","article-title":"Deep learning based caching for self-driving cars in multi-access edge computing","volume":"22","author":"Ndikumana","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"4316","DOI":"10.1109\/TITS.2020.3032227","article-title":"Deep learning for safe autonomous driving: Current challenges and future directions","volume":"22","author":"Muhammad","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"10363","DOI":"10.1109\/ACCESS.2020.2964530","article-title":"Self-assessment based clustering data dissemination for sparse and dense traffic conditions for internet of vehicles","volume":"8","author":"Qureshi","year":"2020","journal-title":"IEEE Access"},{"key":"ref_22","unstructured":"Liu, W., Liu, Y., and Bucknall, R. (2022). Filtering based multi-sensor data fusion algorithm for a reliable unmanned surface vehicle navigation. J. Mar. Eng. Technol., 1\u201317."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Lakhekar, G.V., and Waghmare, L.M. (2022). Robust self-organising fuzzy sliding mode-based path-following control for autonomous underwater vehicles. J. Mar. Eng. Technol., 1\u201322.","DOI":"10.1080\/20464177.2022.2120448"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.future.2018.05.054","article-title":"Software defined network-based control system for an efficient traffic management for emergency situations in smart cities","volume":"88","author":"Rego","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"100418","DOI":"10.1016\/j.cosrev.2021.100418","article-title":"A review on specification evaluation of broadcasting routing protocols in vanet","volume":"41","author":"Shah","year":"2021","journal-title":"Comput. Sci. Rev."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Hakak, S., Gadekallu, T.R., Maddikunta, P.K.R., Ramu, S.P., Parimala, M., De Alwis, C., and Liyanage, M. (2022). Autonomous Vehicles in 5G and beyond: A Survey. Veh. Commun., 100551.","DOI":"10.1016\/j.vehcom.2022.100551"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Arikumar, K.S., Deepak Kumar, A., Gadekallu, T.R., Prathiba, S.B., and Tamilarasi, K. (2022). Real-Time 3D Object Detection and Classification in Autonomous Driving Environment Using 3D LiDAR and Camera Sensors. Electronics, 11.","DOI":"10.3390\/electronics11244203"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Han, Z., Yang, Y., Wang, W., Zhou, L., Gadekallu, T.R., Alazab, M., and Su, C. (2022). RSSI Map-Based Trajectory Design for UGV Against Malicious Radio Source: A Reinforcement Learning Approach. IEEE Trans. Intell. Transp. Syst.","DOI":"10.1109\/TITS.2022.3208245"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1260","DOI":"10.1109\/TGCN.2022.3195309","article-title":"Guest Editorial Special Issue on Green Communication and Networking for Connected and Autonomous Vehicles","volume":"6","author":"Dev","year":"2022","journal-title":"IEEE Trans. Green Commun. Netw."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Victor, N., Alazab, M., Bhattacharya, S., Magnusson, S., Maddikunta, P.K.R., Ramana, K., and Gadekallu, T.R. (2022). Federated Learning for IoUT: Concepts, Applications, Challenges and Opportunities. arXiv.","DOI":"10.1109\/IOTM.001.2200067"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Hoffmann, G.M., Tomlin, C.J., Montemerlo, M., and Thrun, S. (2007, January 9\u201313). Autonomous automobile trajectory tracking for off-road driving: Controller design, experimental validation and racing. Proceedings of the 2007 American Control Conference, New York, NY, USA.","DOI":"10.1109\/ACC.2007.4282788"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Simon, D. (2006). Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches, John Wiley & Sons.","DOI":"10.1002\/0470045345"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Preiss, J.A., Honig, W., Sukhatme, G.S., and Ayanian, N. (June, January 29). Crazyswarm: A large nano-quadcopter swarm. Proceedings of the 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore.","DOI":"10.1109\/ICRA.2017.7989376"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/2\/653\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:01:11Z","timestamp":1760119271000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/2\/653"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,6]]},"references-count":33,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["s23020653"],"URL":"https:\/\/doi.org\/10.3390\/s23020653","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,6]]}}}