{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T00:10:05Z","timestamp":1780704605889,"version":"3.54.1"},"reference-count":293,"publisher":"Tech Science Press","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.061749","type":"journal-article","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T03:04:46Z","timestamp":1740020686000},"page":"3643-3692","source":"Crossref","is-referenced-by-count":8,"title":["Artificial Intelligence Revolutionising the Automotive Sector: A Comprehensive Review of Current Insights, Challenges, and Future Scope"],"prefix":"10.32604","volume":"82","author":[{"given":"Md Naeem","family":"Hossain","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md. Abdur","family":"Rahim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md Mustafizur","family":"Rahman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Devarajan","family":"Ramasamy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"10557","DOI":"10.1007\/s10462-023-10410-w","article-title":"Artificial intelligence applications for microgrids integration and management of hybrid renewable energy sources","volume":"56","author":"Talaat","year":"2023","journal-title":"Artif Intell Rev"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"105697","DOI":"10.1016\/j.engappai.2022.105697","article-title":"Review of artificial intelligence applications in engineering design perspective","volume":"118","author":"Y\u00fcksel","year":"2023","journal-title":"Eng Appl Artif Intell"},{"key":"ref3","doi-asserted-by":"crossref","unstructured":"Soni N, Sharma EK, Singh N, Kapoor A. Impact of artificial intelligence on businesses: from research, innovation, market deployment to future shifts in business models. arXiv:1905.02092. 2019.","DOI":"10.1016\/j.procs.2020.03.272"},{"key":"ref4","first-page":"4207","article-title":"Artificial intelligence and advanced materials in automotive industry: potential applications and perspectives","volume":"62","author":"Kamran","year":"2022","journal-title":"Mater Today: Proc"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"951","DOI":"10.3390\/jpm13060951","article-title":"A review of the role of artificial intelligence in healthcare","volume":"13","author":"Al Kuwaiti","year":"2023","journal-title":"J Pers Med"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.3390\/en16031077","article-title":"A comprehensive review of artificial intelligence (AI) companies in the power sector","volume":"16","author":"Franki","year":"2023","journal-title":"Energies"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"2899","DOI":"10.3390\/su12072899","article-title":"Developing a forecasting model for real estate auction prices using artificial intelligence","volume":"12","author":"Kang","year":"2020","journal-title":"Sustainability"},{"key":"ref8","first-page":"295","author":"Han","year":"2021","journal-title":"The social science handbook of AI"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1016\/j.ifacol.2019.11.203","article-title":"Machine learning in predicting demand for fast-moving consumer goods: an exploratory research","volume":"52","author":"Tarallo","year":"2019","journal-title":"IFAC-PapersOnLine"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"457","DOI":"10.5267\/j.ijdns.2022.8.013","article-title":"The adoption of artificial intelligence applications in education","volume":"7","author":"Alhumaid","year":"2023","journal-title":"Int J Data Netw Sci"},{"key":"ref11","first-page":"264","article-title":"State-of-the-art and adoption of artificial intelligence in retailing","volume":"21","author":"Weber","year":"2019","journal-title":"Digit Policy Regul Gov"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1109\/ACCESS.2022.3232485","article-title":"Artificial intelligence technology in the agricultural sector: a systematic literature review","volume":"11","author":"Elbasi","year":"2022 Dec","journal-title":"IEEE Access"},{"key":"ref13","article-title":"Effectiveness of artificial intelligence techniques against cyber security risks apply of IT industry","author":"Alhayani","year":"2021","journal-title":"Mater Today: Proc"},{"key":"ref14","first-page":"309","article-title":"Artificial intelligence: opportunities, issues and applications in banking, accounting, and auditing in Nigeria","volume":"8","author":"Ukpong","year":"2019","journal-title":"Asian J Econ, Bus Account"},{"key":"ref15","first-page":"30","author":"Kortelainen","year":"2020","journal-title":"Artificial intelligence for the support of regulator decision making"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"6248","DOI":"10.1109\/TIE.2020.2994868","article-title":"Fault diagnosis of an autonomous vehicle with an improved SVM algorithm subject to unbalanced datasets","volume":"68","author":"Shi","year":"2021","journal-title":"IEEE Trans Ind Electron"},{"key":"ref17","series-title":"2018 IEEE International Conference on Big Data (Big Data)","first-page":"3144","article-title":"Artificial intelligence and deep learning applications for automotive manufacturing","author":"Luckow","year":"2018"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"110969","DOI":"10.1016\/j.rser.2021.110969","article-title":"Intelligent building control systems for thermal comfort and energy-efficiency: a systematic review of artificial intelligence-assisted techniques","volume":"144","author":"Merabet","year":"2021","journal-title":"Renew Sustain Energ Rev"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"1384","DOI":"10.3390\/pr8111384","article-title":"Performance evaluation for a sustainable supply chain management system in the automotive industry using artificial intelligence","volume":"8","author":"Dumitrascu","year":"2020","journal-title":"Processes"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"113074","DOI":"10.1016\/j.eswa.2019.113074","article-title":"Intelligent traffic control for autonomous vehicle systems based on machine learning","volume":"144","author":"Lee","year":"2020","journal-title":"Expert Syst Appl"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1007\/978-981-33-4795-3_76","author":"Rizvi","year":"2021","journal-title":"Current advances in mechanical engineering: select proceedings of ICRAMERD 2020"},{"key":"ref22","unstructured":"Automotive artificial intelligence (AI) market size, share, and trends 2024 to 2034 [Internet]. 2024 [cited 2025 Jan 10]. Available from: https:\/\/www.precedenceresearch.com\/automotive-artificial-intelligence-market."},{"key":"ref23","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1007\/s42154-018-0009-9","article-title":"Survey on artificial intelligence for vehicles","volume":"1","author":"Li","year":"2018","journal-title":"Automot Innov"},{"key":"ref24","series-title":"2020 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA)","first-page":"1","article-title":"Detection and prevention of assembly defects, by machine learning algorithms, in semiconductor industry for automotive","author":"Berg\u00e8s","year":"2020"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1109\/MetroAutomotive54295.2022.9855154","author":"Fedullo","year":"2022","journal-title":"2022 IEEE International Workshop on Metrology for Automotive (MetroAutomotive)"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"109237","DOI":"10.1016\/j.compeleceng.2024.109237","article-title":"Automotive intelligence: unleashing the potential of AI beyond advance driver assisting system, a comprehensive review","volume":"117","author":"Rana","year":"2024","journal-title":"Comput Electr Eng"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1007\/978-3-030-59897-6_8","author":"Ammal","year":"2021","journal-title":"Automotive embedded systems: key technologies, innovations, and applications"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"688482","DOI":"10.3389\/ffutr.2021.688482","article-title":"Automotive intelligence embedded in electric connected autonomous and shared vehicles technology for sustainable green mobility","volume":"2","author":"Vermesan","year":"2021","journal-title":"Front Future Transp"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1177\/0008125619864925","article-title":"A brief history of artificial intelligence: on the past, present, and future of artificial intelligence","volume":"61","author":"Haenlein","year":"2019","journal-title":"Calif Manage Rev"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1108\/IR-04-2013-342","article-title":"Robotic vision boosts automotive industry quality and productivity","volume":"40","author":"Bogue","year":"2013","journal-title":"Ind Robot: Int J"},{"key":"ref31","series-title":"Proceedings of the 6th International Joint Conference on Artificial Intelligence","first-page":"893","article-title":"An automobile with artificial intelligence","volume":"2","author":"Tsugawa","year":"1979"},{"key":"ref32","author":"Gage","year":"1995","journal-title":"Naval command control and ocean surveillance center RDT and E"},{"key":"ref33","series-title":"West Coast International Meeting and Exposition","first-page":"12","article-title":"Using artificial intelligence in vehicle diagnostic systems","author":"Klausmeier","year":"1986 Aug"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/0968-090X(95)00009-8","article-title":"A review of neural networks applied to transport","volume":"3","author":"Dougherty","year":"1995","journal-title":"Transp Res Part C Emerg Technol"},{"key":"ref35","unstructured":"Luu R. A fuzzy logic-based automobile fuel injection control system [M.S. thesis]. Long Beach: Department of Electrical Engineering, California State University; 1995."},{"key":"ref36","first-page":"40","article-title":"Intelligent in-car health monitoring system for elderly drivers in connected car","volume":"823","author":"Park","year":"2019","journal-title":"Adv Intell Syst Comput"},{"key":"ref37","doi-asserted-by":"crossref","first-page":"2789","DOI":"10.3390\/su12072789","article-title":"Artificial intelligence, transport and the smart city: definitions and dimensions of a new mobility era","volume":"12","author":"Nikitas","year":"2020","journal-title":"Sustainability"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/su11010189","article-title":"Applications of artificial intelligence in transport: an overview","volume":"11","author":"Abduljabbar","year":"2019","journal-title":"Sustainability"},{"key":"ref39","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1007\/978-3-030-18963-1_2","author":"Khayyam","year":"2020","journal-title":"Nonlinear approaches in engineering applications: automotive applications of engineering problems"},{"key":"ref40","unstructured":"\u0160kavi\u0107 F. The implementation of artificial intelligence and its future potential. Croatia: Department of Informatics, University of Zagreb; 2019."},{"key":"ref41","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/B978-0-12-817024-3.00008-8","author":"Kirwan","year":"2020","journal-title":"Smart cities and artificial intelligence"},{"key":"ref42","doi-asserted-by":"crossref","first-page":"143","DOI":"10.3390\/ai1020008","article-title":"Artificial intelligence (AI) or intelligence augmentation (IA): what is the future?","volume":"1","author":"Hassani","year":"2020","journal-title":"AI"},{"key":"ref43","doi-asserted-by":"crossref","first-page":"e0189008","DOI":"10.1371\/journal.pone.0189008","article-title":"Reactive navigation in extremely dense and highly intricate environments","volume":"12","author":"Tobaruela","year":"2017","journal-title":"PLoS One"},{"key":"ref44","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/S0020-0255(02)00227-X","article-title":"Reactive navigation and opportunistic localization for autonomous underground mining vehicles","volume":"145","author":"Roberts","year":"2002","journal-title":"Inf Sci"},{"key":"ref45","doi-asserted-by":"crossref","first-page":"100057","DOI":"10.1016\/j.array.2021.100057","article-title":"Deep learning for object detection and scene perception in self-driving cars: survey, challenges, and open issues","volume":"10","author":"Gupta","year":"2021","journal-title":"Array"},{"key":"ref46","doi-asserted-by":"crossref","unstructured":"Andreu-Perez J, Deligianni F, Ravi D, Yang GZ. Artificial intelligence and robotics. arXiv:1803.10813. 2018.","DOI":"10.31256\/WP2017.1"},{"key":"ref47","first-page":"121","article-title":"Technological opacity, predictability, and self-driving cars","volume":"38","author":"Surden","year":"2016","journal-title":"Cardozo L Rev"},{"key":"ref48","series-title":"35th International Conference on Machine Learning","first-page":"4218","article-title":"Machine theory of mind","author":"Rabinowitz","year":"2018"},{"key":"ref49","series-title":"Design, Automation & Test in Europe Conference & Exhibition (DATE)","first-page":"1050","article-title":"Self-awareness in autonomous automotive systems","author":"Schlatow","year":"2017"},{"key":"ref50","doi-asserted-by":"crossref","first-page":"4403","DOI":"10.3390\/en16114403","article-title":"Cloud-based artificial intelligence framework for battery management system","volume":"16","author":"Shi","year":"2023","journal-title":"Energies"},{"key":"ref51","doi-asserted-by":"crossref","first-page":"106516","DOI":"10.1016\/j.ssci.2024.106516","article-title":"The prevention of road accidents in non-expert drivers: exploring the influence of theory of mind and driving style","volume":"175","author":"Nori","year":"2024","journal-title":"Saf Sci"},{"key":"ref52","series-title":"2023 IEEE Intelligent Vehicles Symposium (IV)","first-page":"1","article-title":"Self-aware trajectory prediction for safe autonomous driving","author":"Shao","year":"2023"},{"key":"ref53","unstructured":"Gryth E, Rundberg D. Am AI ready? Investigating the impacts of artificial intelligence on [M.S. thesis]. Sweden: School of Business, Economics, and Law, University of Gothenburg; 2018."},{"key":"ref54","doi-asserted-by":"crossref","first-page":"6297","DOI":"10.1109\/TITS.2020.2991039","article-title":"A theoretical foundation of intelligence testing and its application for intelligent vehicles","volume":"22","author":"Li","year":"2020","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"ref55","first-page":"1","article-title":"Impact of artificial intelligence in automotive industries transformation","volume":"9","author":"Chai","year":"2021","journal-title":"Int J Inf Syst Eng"},{"key":"ref56","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1007\/978-3-030-70917-4_19","author":"Rahim","year":"2021","journal-title":"Advances in robotics, automation and data analytics: selected papers from ICITES 2020"},{"key":"ref57","first-page":"1","article-title":"Machine learning technologies for secure vehicular communication in internet of vehicles: recent advances and applications","volume":"2021","author":"Ali","year":"2021","journal-title":"Secur Commun Netw"},{"key":"ref58","doi-asserted-by":"crossref","first-page":"267","DOI":"10.3390\/vehicles2020015","article-title":"Powertrain control for hybrid-electric vehicles using supervised machine learning","volume":"2","author":"Harold","year":"2020","journal-title":"Vehicles"},{"key":"ref59","doi-asserted-by":"crossref","first-page":"105403","DOI":"10.1088\/1361-6501\/ac0b6c","article-title":"Smart data driven defect detection method for surface quality control in manufacturing","volume":"32","author":"Chouhad","year":"2021","journal-title":"Meas Sci Technol"},{"key":"ref60","series-title":"IEEE Intelligent Vehicles Symposium","first-page":"1262","article-title":"Road friction estimation for connected vehicles using supervised machine learning","author":"Panahandeh","year":"2017"},{"key":"ref61","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.3390\/s18061696","article-title":"Accurate traffic flow prediction in heterogeneous vehicular networks in an intelligent transport system using a supervised non-parametric classifier","volume":"18","author":"El-Sayed","year":"2018","journal-title":"Sensors"},{"key":"ref62","doi-asserted-by":"crossref","first-page":"2386","DOI":"10.3390\/s19102386","article-title":"Machine learning techniques for undertaking roundabouts in autonomous driving","volume":"19","author":"Cuenca","year":"2019","journal-title":"Sensors"},{"key":"ref63","series-title":"2018 World Automation Congress (WAC)","first-page":"1","article-title":"Data-driven fault detection of un-manned aerial vehicles using supervised learning over cloud networks","author":"Yousefi","year":"2018"},{"key":"ref64","series-title":"2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)","first-page":"1043","article-title":"Machine learning-based predictive analytics and big data in the automotive sector","author":"Lourens","year":"2023"},{"key":"ref65","doi-asserted-by":"crossref","first-page":"104492","DOI":"10.1016\/j.ssci.2019.09.015","article-title":"Applications of machine learning methods for engineering risk assessment\u2014a review","volume":"122","author":"Hegde","year":"2020","journal-title":"Saf Sci"},{"key":"ref66","first-page":"1","article-title":"Data mining and machine learning techniques (mahout on hadoop) for automotive industries: a survey","volume":"119","author":"Madasamy","year":"2018","journal-title":"Int J Pure Appl Math"},{"key":"ref67","doi-asserted-by":"crossref","first-page":"911","DOI":"10.12785\/ijcds\/130172","article-title":"An unsupervised machine learning algorithms: comprehensive review","volume":"13","author":"Naeem","year":"2023","journal-title":"Int J Comput Digit Syst"},{"key":"ref68","series-title":"Intelligent computing","first-page":"158","article-title":"A review of unsupervised machine learning frameworks for anomaly detection in industrial applications","author":"Usmani","year":"2022"},{"key":"ref69","series-title":"IEEE International Conference on Industrial Informatics (INDIN)","first-page":"1279","article-title":"Analysis of the applicability of fault detection and failure prediction based on unsupervised learning and monte carlo simulations for real devices in the industrial automobile production","author":"Garay","year":"2019"},{"key":"ref70","first-page":"1","article-title":"Fast unsupervised automobile insurance fraud detection based on spectral ranking of anomalies","volume":"33","author":"Shaeiri","year":"2020","journal-title":"Int J Eng"},{"key":"ref71","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1109\/MCE.2020.3023538","article-title":"Reverse engineering controller area network messages using unsupervised machine learning","volume":"11","author":"Ezeobi","year":"2020","journal-title":"IEEE Consum Electron Mag"},{"key":"ref72","series-title":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","first-page":"54","article-title":"Cluster-linkage analysis in traffic data clustering for development of advanced driver assistance systems","author":"Watanabe","year":"2020"},{"key":"ref73","doi-asserted-by":"crossref","first-page":"4337","DOI":"10.1109\/TIP.2019.2913986","article-title":"Improving dataset volumes and model accuracy with semi-supervised iterative self-learning","volume":"29","author":"Dupre","year":"2019","journal-title":"IEEE Trans Image Process"},{"key":"ref74","unstructured":"Lamm N, Jaiprakash S, Srikanth M, Drori I. Vehicle trajectory prediction by transfer learning of semi-supervised models. arXiv:2007.06781. 2020."},{"key":"ref75","series-title":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","first-page":"426","article-title":"A feature-aware semi-supervised learning approach for automotive ethernet","author":"Shibly","year":"2023"},{"key":"ref76","first-page":"100520","article-title":"Detecting in-vehicle intrusion via semi-supervised learning-based convolutional adversarial autoencoders","volume":"38","author":"Hoang","year":"2022","journal-title":"Veh Commun"},{"key":"ref77","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.neucom.2021.02.059","article-title":"Broad learning system for semi-supervised learning","volume":"444","author":"Liu","year":"2021","journal-title":"Neurocomputing"},{"key":"ref78","doi-asserted-by":"crossref","first-page":"4909","DOI":"10.1109\/TITS.2021.3054625","article-title":"Deep reinforcement learning for autonomous driving: a survey","volume":"23","author":"Kiran","year":"2021","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"ref79","first-page":"1","article-title":"Using reinforcement learning and simulation to develop autonomous vehicle control strategies","volume":"1","author":"Navarro","year":"2020","journal-title":"SAE Technical Papers"},{"key":"ref80","series-title":"32nd Conference on Neural Information Processing Systems (NeurIPS 2018)","first-page":"1","article-title":"Reinforcement learning for solving the vehicle routing problem","author":"Nazari","year":"2018"},{"key":"ref81","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.trc.2019.08.011","article-title":"Automated vehicle\u2019s behavior decision making using deep reinforcement learning and high-fidelity simulation environment","volume":"107","author":"Ye","year":"2019","journal-title":"Transp Res Part C Emerg Technol"},{"key":"ref82","doi-asserted-by":"crossref","first-page":"4205","DOI":"10.1109\/TWC.2021.3056573","article-title":"Simultaneous navigation and radio mapping for cellular-connected UAV with deep reinforcement learning","volume":"20","author":"Zeng","year":"2021","journal-title":"IEEE Trans Wirel Commun"},{"key":"ref83","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1109\/TVT.2019.2952549","article-title":"Deep reinforcement learning for UAV navigation through massive MIMO technique","volume":"69","author":"Huang","year":"2020","journal-title":"IEEE Trans Veh Technol"},{"key":"ref84","doi-asserted-by":"crossref","first-page":"1867","DOI":"10.1017\/S0263574719000316","article-title":"Autonomous vehicular landings on the deck of an unmanned surface vehicle using deep reinforcement learning","volume":"37","author":"Polvara","year":"2019","journal-title":"Robotica"},{"key":"ref85","doi-asserted-by":"crossref","first-page":"914","DOI":"10.3390\/vehicles5030050","article-title":"Cloud-based reinforcement learning in automotive control function development","volume":"5","author":"Koch","year":"2023","journal-title":"Vehicles"},{"key":"ref86","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1109\/TASE.2022.3168621","article-title":"Unified automatic control of vehicular systems with reinforcement learning","volume":"20","author":"Yan","year":"2022","journal-title":"IEEE Trans Autom Sci Eng"},{"key":"ref87","first-page":"3884","article-title":"A reinforcement learning approach to autonomous decision making of intelligent vehicles on highways","volume":"50","author":"Xu","year":"2018","journal-title":"IEEE Trans Syst Man Cybern: Syst"},{"key":"ref88","doi-asserted-by":"crossref","first-page":"1108","DOI":"10.1016\/j.procir.2023.06.190","article-title":"Deep learning based predictive testing strategy in the automotive industry","volume":"118","author":"Schoch","year":"2023","journal-title":"Procedia CIRP"},{"key":"ref89","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.procir.2019.03.077","article-title":"Automobile maintenance prediction using deep learning with gis data","volume":"81","author":"Chen","year":"2019","journal-title":"Procedia CIRP"},{"key":"ref90","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/s18020456","article-title":"Deep learning-based gaze detection system for automobile drivers using a NIR camera sensor","volume":"18","author":"Naqvi","year":"2018","journal-title":"Sensors"},{"key":"ref91","series-title":"2021 IEEE Radar Conference (RadarConf21)","first-page":"1","article-title":"Deepreflecs: deep learning for automotive object classification with radar reflections","author":"Ulrich","year":"2021"},{"key":"ref92","unstructured":"Paparusso L, Melzi S, Braghin F. A deep-learning framework to predict the dynamics of a human-driven vehicle based on the road geometry. arXiv:2103.03825v1. 2021."},{"key":"ref93","doi-asserted-by":"crossref","first-page":"13799","DOI":"10.3390\/su151813799","article-title":"Improving the performance of autonomous driving through deep reinforcement learning","volume":"15","author":"Tammewar","year":"2023","journal-title":"Sustainability"},{"key":"ref94","doi-asserted-by":"crossref","unstructured":"Talpaert V, Sobh I, Kiran BR, Mannion P, Yogamani S, El-Sallab A, et al. Exploring applications of deep reinforcement learning for real-world autonomous driving systems. arXiv:1901.01536. 2019.","DOI":"10.5220\/0007520300002108"},{"key":"ref95","series-title":"2021 4th International Conference on Artificial Intelligence and Big Data (ICAIBD)","first-page":"247","article-title":"Applying deep learning to autonomous vehicles: a survey","author":"Ren","year":"2021"},{"key":"ref96","unstructured":"Singh KB, Arat MA. Deep learning in the automotive industry: recent advances and application examples. arXiv:1906.08834. 2019."},{"key":"ref97","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.jmsy.2018.01.003","article-title":"Deep learning for smart manufacturing: methods and applications","volume":"48","author":"Wang","year":"2018","journal-title":"J Manuf Syst"},{"key":"ref98","doi-asserted-by":"crossref","first-page":"26145","DOI":"10.1007\/s11042-021-10913-0","article-title":"RNN\/LSTM with modified Adam optimizer in deep learning approach for automobile spare parts demand forecasting","volume":"80","author":"Chandriah","year":"2021","journal-title":"Multimed Tools Appl"},{"key":"ref99","first-page":"102456","article-title":"A review on deep learning in UAV remote sensing","volume":"102","author":"Osco","year":"2021","journal-title":"Int J Appl Earth Obs Geoinf"},{"key":"ref100","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/B978-0-12-812256-3.00018-X","author":"Lindfield","year":"2019","journal-title":"Numerical methods"},{"key":"ref101","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1287\/ijoc.2023.1288","article-title":"Decomposition strategies for vehicle routing heuristics","volume":"35","author":"Santini","year":"2023","journal-title":"INFORMS J Comput"},{"key":"ref102","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1007\/s10479-021-03985-6","article-title":"A robust-heuristic optimization approach to a green supply chain design with consideration of assorted vehicle types and carbon policies under uncertainty","volume":"324","author":"Homayouni","year":"2023","journal-title":"Ann Oper Res"},{"key":"ref103","first-page":"1","article-title":"A heuristic algorithm for the routing and scheduling problem with time windows: a case study of the automotive industry in Mexico","volume":"12","author":"P\u00e9rez","year":"2019","journal-title":"Algorithms"},{"key":"ref104","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2019\/7983583","volume":"2019","author":"Gunantara","year":"2019","journal-title":"J Comput Netw Commun"},{"key":"ref105","doi-asserted-by":"crossref","first-page":"13187","DOI":"10.1007\/s10462-023-10470-y","article-title":"An exhaustive review of the metaheuristic algorithms for search and optimization: Taxonomy, applications, and open challenges","volume":"56","author":"Rajwar","year":"2023","journal-title":"Artif Intell Rev"},{"key":"ref106","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1007\/s11831-020-09412-6","article-title":"A comprehensive analysis of nature-inspired meta-heuristic techniques for feature selection problem","volume":"28","author":"Sharma","year":"2021","journal-title":"Arch Comput Methods Eng"},{"key":"ref107","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1109\/JAS.2021.1004129","article-title":"A review on representative swarm intelligence algorithms for solving optimization problems: applications and trends","volume":"8","author":"Tang","year":"2021","journal-title":"IEEE\/CAA J Automatica Sinica"},{"key":"ref108","doi-asserted-by":"crossref","first-page":"905983","DOI":"10.3389\/fbioe.2022.905983","article-title":"Path planning optimization of intelligent vehicle based on improved genetic and ant colony hybrid algorithm","volume":"10","author":"Shi","year":"2022","journal-title":"Front Bioeng Biotechnol"},{"key":"ref109","doi-asserted-by":"crossref","first-page":"105397","DOI":"10.1016\/j.cor.2021.105397","article-title":"A hybrid ant colony optimization-variable neighborhood descent approach for the cumulative capacitated vehicle routing problem","volume":"134","author":"Kyriakakis","year":"2021","journal-title":"Comput Operat Res"},{"key":"ref110","author":"Hashim","year":"2019","journal-title":"Studies in computational intelligence"},{"key":"ref111","first-page":"83","article-title":"Research on vehicle routing planning based on adaptive ant colony and particle swarm optimization algorithm","volume":"19","author":"Jiang","year":"2021","journal-title":"Int J Intell Transp Syst Res"},{"key":"ref112","doi-asserted-by":"crossref","first-page":"103582","DOI":"10.1016\/j.engappai.2020.103582","article-title":"Demand coverage diversity based ant colony optimization for dynamic vehicle routing problems","volume":"91","author":"Xiang","year":"2020","journal-title":"Eng Appl Artif Intell"},{"key":"ref113","doi-asserted-by":"crossref","first-page":"5027","DOI":"10.1149\/10701.5027ecst","article-title":"A systematic review of swarm intelligence algorithms to perform routing for VANETs communication","volume":"107","author":"Kaushal","year":"2022","journal-title":"ECS Trans"},{"key":"ref114","series-title":"2023 IEEE world AI IoT congress (AIIoT)","first-page":"701","article-title":"Ant colony optimization algorithm enhancement for better performance","author":"Faisal","year":"2023"},{"key":"ref115","series-title":"26th International Technical Conference on the Enhanced Safety of Vehicles (ESV): Technology: Enabling a Safer Tomorrow","article-title":"Detecting potential vehicle concerns using natural language processing applied to automotive big data","author":"Eboli","year":"2019"},{"key":"ref116","first-page":"100670","article-title":"On the road safety benefits of advanced driver assistance systems in different driving contexts","volume":"15","author":"Masello","year":"2022","journal-title":"Transp Res Interdiscip Perspect"},{"key":"ref117","series-title":"2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE)","first-page":"701","article-title":"Hand gesture recognition system for in-car device control based on infrared array sensor","author":"Tateno","year":"2019"},{"key":"ref118","doi-asserted-by":"crossref","first-page":"127514","DOI":"10.1109\/ACCESS.2022.3226539","article-title":"A novel human-vehicle interaction assistive device for Arab drivers using speech recognition","volume":"10","author":"Jaradat","year":"2022","journal-title":"IEEE Access"},{"key":"ref119","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/B978-0-12-813677-5.00007-9","author":"Eksin","year":"2018","journal-title":"Cooperative and graph signal processing"},{"key":"ref120","doi-asserted-by":"crossref","first-page":"818","DOI":"10.1109\/LRA.2021.3134249","article-title":"Deep reinforcement learning based game-theoretic decision-making for autonomous vehicles","volume":"7","author":"Yuan","year":"2021","journal-title":"IEEE Robot Autom Lett"},{"key":"ref121","doi-asserted-by":"crossref","first-page":"3609","DOI":"10.1109\/TVT.2022.3148972","article-title":"Game-theoretic lane-changing decision making and payoff learning for autonomous vehicles","volume":"71","author":"Lopez","year":"2022","journal-title":"IEEE Trans Veh Technol"},{"key":"ref122","doi-asserted-by":"crossref","first-page":"1313","DOI":"10.1109\/TRO.2020.3047521","article-title":"Game-theoretic planning for self-driving cars in multivehicle competitive scenarios","volume":"37","author":"Wang","year":"2021","journal-title":"IEEE Trans Robot"},{"key":"ref123","doi-asserted-by":"crossref","first-page":"2676","DOI":"10.1109\/LRA.2022.3144516","article-title":"Game-theoretic multi-agent planning with human drivers at intersections, roundabouts, and merging","volume":"7","author":"Chandra","year":"2022","journal-title":"IEEE Robot Autom Lett"},{"key":"ref124","series-title":"2022 10th RSI International Conference on Robotics and Mechatronics (ICRoM)","first-page":"564","article-title":"Combining deep learning and game theory for path planning in autonomous racing cars","author":"Ardekani","year":"2022"},{"key":"ref125","doi-asserted-by":"crossref","first-page":"10077","DOI":"10.15282\/jmes.18.2.2024.9.0796","article-title":"Advancements, challenges, and implications for navigating the autonomous vehicle revolution","volume":"8","author":"Hossain","year":"2024","journal-title":"J Mech Eng Sci"},{"key":"ref126","doi-asserted-by":"crossref","first-page":"829","DOI":"10.3390\/app10030829","article-title":"Demand prediction using a soft-computing approach: a case study of automotive industry","volume":"10","author":"Salais-Fierro","year":"2020","journal-title":"Appl Sci"},{"key":"ref127","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.aci.2018.04.004","article-title":"A review on multi-criteria decision-making for energy efficiency in automotive engineering","volume":"17","author":"Castro","year":"2021","journal-title":"Appl Comput Inform"},{"key":"ref128","doi-asserted-by":"crossref","first-page":"3726","DOI":"10.3390\/app11083726","article-title":"A DMAIC integrated fuzzy FMEA model: a case study in the Automotive Industry","volume":"11","author":"Godina","year":"2021","journal-title":"Appl Sci"},{"key":"ref129","doi-asserted-by":"crossref","first-page":"106577","DOI":"10.1016\/j.compeleceng.2020.106577","article-title":"Real-time range estimation in electric vehicles using fuzzy logic classifier","volume":"83","author":"\u00c7even","year":"2020","journal-title":"Comput Electr Eng"},{"key":"ref130","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1108\/BIJ-08-2021-0505","article-title":"Benchmarking Industry 4.0 readiness evaluation using fuzzy approaches","volume":"30","author":"Wankhede","year":"2023","journal-title":"Benchmarking: Int J"},{"key":"ref131","doi-asserted-by":"crossref","first-page":"734","DOI":"10.3390\/en16020734","article-title":"Evaluating vehicle energy efficiency in urban transport systems based on fuzzy logic models","volume":"16","author":"Mateichyk","year":"2023","journal-title":"Energies"},{"key":"ref132","doi-asserted-by":"crossref","first-page":"7949","DOI":"10.1007\/s12652-020-02524-8","article-title":"A combined big data analytics and Fuzzy DEMATEL technique to improve the responsiveness of automotive supply chains","volume":"12","author":"Sathyan","year":"2021","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"ref133","doi-asserted-by":"crossref","first-page":"6011","DOI":"10.1109\/TITS.2021.3074695","article-title":"A survey on hybrid human-artificial intelligence for autonomous driving","volume":"23","author":"Ning","year":"2021","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"ref134","series-title":"AAMAS\u201923: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems","first-page":"1191","article-title":"ML-MAS: a hybrid AI framework for self-driving vehicles","author":"Al Shukairi","year":"2023"},{"key":"ref135","doi-asserted-by":"crossref","first-page":"125080","DOI":"10.1016\/j.eswa.2024.125080","article-title":"Deep learning-based vehicular engine health monitoring system utilising a hybrid convolutional neural network\/bidirectional gated recurrent unit","volume":"257","author":"Rahim","year":"2024","journal-title":"Expert Syst Appl"},{"key":"ref136","doi-asserted-by":"crossref","first-page":"9378","DOI":"10.3390\/su14159378","article-title":"Intelligent driver assistance and energy management systems of hybrid electric autonomous vehicles","volume":"14","author":"Al-Saadi","year":"2022","journal-title":"Sustainability"},{"key":"ref137","unstructured":"Nazari S, Gowans N, Abtahi M. Powertrain hybridization for autonomous vehicles. arXiv:2309.17442. 2023."},{"key":"ref138","series-title":"2024 8th International Artificial Intelligence and Data Processing Symposium (IDAP)","first-page":"1","article-title":"A robust hybrid control model implementation for autonomous vehicles","author":"Al-Jumaili","year":"2024"},{"key":"ref139","doi-asserted-by":"crossref","first-page":"165","DOI":"10.12700\/APH.20.9.2023.9.10","article-title":"A hybrid machine learning-based control strategy for autonomous driving optimization","volume":"20","author":"Reda","year":"2023","journal-title":"Acta Polytechnica Hung"},{"key":"ref140","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1109\/TIV.2020.3011954","article-title":"Interval type 2 fuzzy logic control for energy management of hybrid electric autonomous vehicles","volume":"6","author":"Phan","year":"2020","journal-title":"IEEE Trans Intell Veh"},{"key":"ref141","doi-asserted-by":"crossref","first-page":"102210","DOI":"10.1016\/j.simpat.2020.102210","article-title":"Transitioning to a driverless city: evaluating a hybrid system for autonomous and non-autonomous vehicles","volume":"107","author":"Santana","year":"2021","journal-title":"Simul Model Pract Theory"},{"key":"ref142","series-title":"2018 22nd International Conference on System Theory, Control and Computing (ICSTCC)","first-page":"559","article-title":"A multi-platform framework for artificial intelligence engines in automotive systems","author":"Marina","year":"2018"},{"key":"ref143","doi-asserted-by":"crossref","first-page":"2879","DOI":"10.3390\/app13052879","article-title":"AI-for-mobility\u2014a new research platform for AI-based control methods","volume":"13","author":"Ruggaber","year":"2023","journal-title":"Appl Sci"},{"key":"ref144","doi-asserted-by":"crossref","first-page":"74","DOI":"10.21754\/tecnia.v30i2.801","article-title":"Computer vision methods for automotive applications","volume":"30","author":"D\u00edaz","year":"2020","journal-title":"Tecnia"},{"key":"ref145","doi-asserted-by":"crossref","first-page":"3543","DOI":"10.3390\/math10193543","article-title":"Computer vision algorithms, remote sensing data fusion techniques, and mapping and navigation tools in the Industry 4.0-based Slovak automotive sector","volume":"10","author":"Nagy","year":"2022","journal-title":"Mathematics"},{"key":"ref146","series-title":"2023 Conference on Information Communications Technology and Society (ICTAS)","first-page":"1","article-title":"Computer vision-based applications in modern cars for safety purposes: a systematic literature review","author":"Nkuzo","year":"2023"},{"key":"ref147","series-title":"2021 IEEE International Conference on Imaging Systems and Techniques (IST)","first-page":"1","article-title":"The role of machine vision in industry 4.0: an automotive manufacturing perspective","author":"Konstantinidis","year":"2021"},{"key":"ref148","series-title":"2021 22nd International Carpathian Control Conference (ICCC)","first-page":"1","article-title":"Detection of a surface defect on an engine block using computer vision","author":"Abagiu","year":"2021"},{"key":"ref149","doi-asserted-by":"crossref","first-page":"11588","DOI":"10.1109\/JSEN.2020.3038186","article-title":"Application of computer vision for estimation of moving vehicle weight","volume":"21","author":"Feng","year":"2020","journal-title":"IEEE Sens J"},{"key":"ref150","series-title":"2022 Interdisciplinary Research in Technology and Management (IRTM)","first-page":"1","article-title":"Computer vision application in automobile error detection","author":"Darapaneni","year":"2022"},{"key":"ref151","doi-asserted-by":"crossref","first-page":"107293","DOI":"10.1109\/ACCESS.2022.3209825","article-title":"A review on machine learning styles in computer vision\u2014techniques and future directions","volume":"10","author":"Mahadevkar","year":"2022","journal-title":"IEEE Access"},{"key":"ref152","series-title":"Futuristic Trends in Networks and Computing Technologies (FTNCT 2019)","first-page":"245","article-title":"Comparative analysis of different machine learning techniques","author":"Srivastava","year":"2020"},{"key":"ref153","doi-asserted-by":"crossref","first-page":"7068349","DOI":"10.1155\/2018\/7068349","article-title":"Deep learning for computer vision: a brief review","volume":"2018","author":"Voulodimos","year":"2018","journal-title":"Comput Intell Neurosci"},{"key":"ref154","doi-asserted-by":"crossref","first-page":"6326","DOI":"10.1021\/acsnano.8b03569","article-title":"Deep-learning-enabled on-demand design of chiral metamaterials","volume":"12","author":"Ma","year":"2018","journal-title":"ACS Nano"},{"key":"ref155","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.1093\/jamia\/ocad152","article-title":"Two complementary AI approaches for predicting UMLS semantic group assignment: heuristic reasoning and deep learning","volume":"30","author":"Mao","year":"2023","journal-title":"J Am Med Inform Assoc"},{"key":"ref156","doi-asserted-by":"crossref","first-page":"3145956","DOI":"10.1155\/2022\/3145956","article-title":"Optimizing deep learning model for software cost estimation using hybrid meta-heuristic algorithmic approach","volume":"2022","author":"ul Hassan","year":"2022","journal-title":"Comput Intell Neurosci"},{"key":"ref157","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/j.ejor.2021.04.032","article-title":"Machine learning at the service of meta-heuristics for solving combinatorial optimization problems: a state-of-the-art","volume":"296","author":"Karimi-Mamaghan","year":"2022","journal-title":"Eur J Oper Res"},{"key":"ref158","series-title":"Advances in Computer Vision: Proceedings of the 2019 Computer Vision Conference (CVC)","first-page":"59","article-title":"Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective","volume":"11","author":"Chiroma","year":"2020"},{"key":"ref159","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1007\/s12599-019-00595-2","article-title":"Hybrid intelligence","volume":"61","author":"Dellermann","year":"2019","journal-title":"Bus Inf Syst Eng"},{"key":"ref160","doi-asserted-by":"crossref","first-page":"2660","DOI":"10.1109\/COMST.2021.3108466","article-title":"Applications of game theory in vehicular networks: a survey","volume":"23","author":"Sun","year":"2021","journal-title":"IEEE Commun Surv Tutor"},{"key":"ref161","doi-asserted-by":"crossref","first-page":"112063","DOI":"10.1016\/j.measurement.2022.112063","article-title":"Image feature extraction based on fuzzy restricted Boltzmann machine","volume":"204","author":"L\u00fc","year":"2022","journal-title":"Measurement"},{"key":"ref162","doi-asserted-by":"crossref","first-page":"10573","DOI":"10.1007\/s00521-019-04593-z","article-title":"An improved fuzzy inference system-based risk analysis approach with application to automotive production line","volume":"32","author":"Soltanali","year":"2020","journal-title":"Neural Comput Appl"},{"key":"ref163","doi-asserted-by":"crossref","first-page":"44681","DOI":"10.1109\/ACCESS.2021.3065710","article-title":"A hybrid multi-task learning approach for optimizing deep reinforcement learning agents","volume":"9","author":"Varghese","year":"2021","journal-title":"IEEE Access"},{"key":"ref164","series-title":"2023 11th International Conference on Information and Education Technology (ICIET)","first-page":"448","article-title":"A comparative study of hybrid neural network with metaheuristics for student performance classification","author":"Phatai","year":"2023"},{"key":"ref165","series-title":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","first-page":"1","article-title":"Performance analysis of vehicle detection using support vector machine comparing with K-nearest neighbor algorithm","author":"Manivarma","year":"2023"},{"key":"ref166","series-title":"2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM)","first-page":"1","article-title":"A comparative analysis of machine learning algorithms for predictive maintenance in electrical systems","author":"Singh","year":"2024"},{"key":"ref167","doi-asserted-by":"crossref","first-page":"322","DOI":"10.3390\/s20010322","article-title":"A comparative analysis of machine\/deep learning models for parking space availability prediction","volume":"20","author":"Awan","year":"2020","journal-title":"Sensors"},{"key":"ref168","doi-asserted-by":"crossref","first-page":"4381","DOI":"10.1109\/TIV.2023.3296227","article-title":"Robust adversarial attacks detection based on explainable deep reinforcement learning for UAV guidance and planning","volume":"8","author":"Hickling","year":"2023","journal-title":"IEEE Trans Intell Vehicles"},{"key":"ref169","series-title":"2018 International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)","first-page":"1","article-title":"Comparison of machine learning algorithm\u2019s performance based on decision making in autonomous car","author":"Thammachantuek","year":"2018"},{"key":"ref170","doi-asserted-by":"crossref","first-page":"49557","DOI":"10.1109\/ACCESS.2021.3069256","article-title":"A novel predictive maintenance method based on deep adversarial learning in the intelligent manufacturing system","volume":"9","author":"Liu","year":"2021","journal-title":"IEEE Access"},{"key":"ref171","doi-asserted-by":"crossref","first-page":"1673","DOI":"10.1109\/TNSM.2021.3077249","article-title":"Generative adversarial network-based transfer reinforcement learning for routing with prior knowledge","volume":"18","author":"Dong","year":"2021","journal-title":"IEEE Trans Netw Serv Manag"},{"key":"ref172","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1109\/TC.2020.3003083","article-title":"Control performance optimization for application integration on automotive architectures","volume":"70","author":"Minaeva","year":"2020","journal-title":"IEEE Trans Comput"},{"key":"ref173","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1177\/10775463211009383","article-title":"Cooperative-game-theoretic optimal robust path tracking control for autonomous vehicles","volume":"28","author":"Hu","year":"2022","journal-title":"J Vib Control"},{"key":"ref174","doi-asserted-by":"crossref","first-page":"9318475","DOI":"10.1155\/2022\/9318475","article-title":"Game algorithm of intelligent driving vehicle based on left-turn scene of crossroad traffic flow","volume":"2022","author":"Guo","year":"2022","journal-title":"Comput Intell Neurosci"},{"key":"ref175","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1002\/oca.3051","article-title":"Chimp optimization-based fuzzy controller for hybrid electric vehicle speed control using electronic throttle plate","volume":"45","author":"Tripathi","year":"2024","journal-title":"Optim Control Appl Methods"},{"key":"ref176","doi-asserted-by":"crossref","first-page":"7950","DOI":"10.3390\/app11177950","article-title":"Fuzzy simheuristics for optimizing transportation systems: dealing with stochastic and fuzzy uncertainty","volume":"11","author":"Tordecilla","year":"2021","journal-title":"Appl Sci"},{"key":"ref177","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1504\/IJCAET.2020.108112","article-title":"Artificial Intelligent Technology for safe driver assistance system","volume":"13","author":"Takialddin","year":"2020","journal-title":"Int J Comput Aided Eng Technol"},{"key":"ref178","doi-asserted-by":"crossref","first-page":"100083","DOI":"10.1016\/j.treng.2021.100083","article-title":"AI enabled applications towards intelligent transportation","volume":"5","author":"Iyer","year":"2021","journal-title":"Transp Eng"},{"key":"ref179","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/MCE.2018.2828440","article-title":"Advanced driver-assistance systems: a path toward autonomous vehicles","volume":"7","author":"Kukkala","year":"2018","journal-title":"IEEE Consum Electron Mag"},{"key":"ref180","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3377408","article-title":"Anomaly detection based on RBM-LSTM neural network for CPS in advanced driver assistance system","volume":"4","author":"Wu","year":"2020","journal-title":"ACM Tran Cyber-Phys Syst"},{"key":"ref181","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1109\/TIV.2019.2955910","article-title":"A survey of personalization for advanced driver assistance systems","volume":"5","author":"Hasenj\u00e4ger","year":"2019","journal-title":"IEEE Trans Intell Veh"},{"key":"ref182","doi-asserted-by":"crossref","first-page":"5866","DOI":"10.3390\/s21175866","article-title":"Advanced driver assistance systems (ADAS) based on machine learning techniques for the detection and transcription of variable message signs on roads","volume":"21","author":"De-Las-Heras","year":"2021","journal-title":"Sensors"},{"key":"ref183","doi-asserted-by":"crossref","first-page":"3885","DOI":"10.22214\/ijraset.2022.43260","article-title":"Advanced driver assistance system for drivers using machine learning and artificial intelligence techniques","volume":"10","author":"Salve","year":"2022","journal-title":"Int J Res Appl Sci Eng Technol"},{"key":"ref184","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/978-3-030-59897-6_9","author":"Antony","year":"2021","journal-title":"Automotive embedded systems: key technologies, innovations, and applications"},{"key":"ref185","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1109\/OJITS.2022.3166394","article-title":"Quantitative evaluation of the impacts of the time headway of adaptive cruise control systems on congested urban freeways using different car following models and early control results","volume":"3","author":"Elmorshedy","year":"2022","journal-title":"IEEE Open J Intell Transp Syst"},{"key":"ref186","doi-asserted-by":"crossref","first-page":"2094","DOI":"10.1109\/TIV.2023.3307157","article-title":"Radar-camera fusion for object detection and semantic segmentation in autonomous driving: a comprehensive review","volume":"9","author":"Yao","year":"2023","journal-title":"IEEE Trans Intell Veh"},{"key":"ref187","doi-asserted-by":"crossref","first-page":"1451","DOI":"10.14716\/ijtech.v11i7.4592","article-title":"Neural network predictive control approach design for adaptive cruise control","volume":"11","author":"Mahadika","year":"2020","journal-title":"Int J Technol"},{"key":"ref188","series-title":"2023 International Russian Automation Conference (RusAutoCon)","first-page":"634","article-title":"Research on the impact of different controllers on the adapative cruise control system","author":"Suleiman","year":"2023"},{"key":"ref189","series-title":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","first-page":"2901","article-title":"A personalized adaptive cruise control driving style characterization based on a learning approach","author":"Nava","year":"2019"},{"key":"ref190","doi-asserted-by":"crossref","first-page":"1896","DOI":"10.1177\/09544070231156956","article-title":"An innovative method for scene recognition and target tracking for adaptive cruise control in complex traffic environment","volume":"238","author":"Zhang","year":"2024","journal-title":"Proc Inst Mech Eng, Part D: J Automobile Eng"},{"key":"ref191","unstructured":"Yin W. Machine learning for adaptive cruise control target selection [dissertation]. 2019. Sweden: School of Electrical Engineering and Computer Science, KTH."},{"key":"ref192","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1007\/s42979-021-00759-6","article-title":"Collision avoidance using deep learning-based monocular vision","volume":"2","author":"Rill","year":"2021","journal-title":"SN Comput Sci"},{"key":"ref193","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.procs.2018.10.290","article-title":"Space-based collision avoidance framework for autonomous vehicles","volume":"140","author":"Yu","year":"2018","journal-title":"Procedia Comput Sci"},{"key":"ref194","series-title":"2021 Zooming Innovation in Consumer Technologies Conference (ZINC)","first-page":"198","article-title":"Camera and LiDAR sensor fusion for 3D object tracking in a collision avoidance system","author":"Kotur","year":"2021"},{"key":"ref195","doi-asserted-by":"crossref","first-page":"1564","DOI":"10.1177\/03611981221105066","article-title":"Rotated mask region-based convolutional neural network detection for parking space management system","volume":"2677","author":"Truong","year":"2023","journal-title":"Transp Res Rec"},{"key":"ref196","doi-asserted-by":"crossref","first-page":"3996","DOI":"10.3390\/s19183996","article-title":"Reinforcement learning-based end-to-end parking for automatic parking system","volume":"19","author":"Zhang","year":"2019","journal-title":"Sensors"},{"key":"ref197","series-title":"IOP Conference Series: Materials Science and Engineering","first-page":"32026","article-title":"Parking area data collection and scenario extraction for the purpose of automatic parking ADAS function","author":"Wang","year":"2020"},{"key":"ref198","doi-asserted-by":"crossref","first-page":"4391864","DOI":"10.1155\/2021\/4391864","article-title":"Automatic parking system based on improved neural network algorithm and intelligent image analysis","volume":"2021","author":"Guo","year":"2021","journal-title":"Comput Intell Neurosci"},{"key":"ref199","first-page":"100285","article-title":"Evolution of IoT-enabled connectivity and applications in automotive industry: a review","volume":"27","author":"Rahim","year":"2021","journal-title":"Veh Commun"},{"key":"ref200","doi-asserted-by":"crossref","first-page":"19727","DOI":"10.1109\/TITS.2021.3138255","article-title":"A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics","volume":"23","author":"Rahman","year":"2022","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"ref201","doi-asserted-by":"crossref","first-page":"1298","DOI":"10.1109\/TGCN.2022.3179350","article-title":"An intelligent risk management framework for monitoring vehicular engine health","volume":"6","author":"Rahim","year":"2022","journal-title":"IEEE Trans Green Commun Netw"},{"key":"ref202","series-title":"ELIV","first-page":"143","article-title":"AI-based signal integrity monitoring for integrated vehicle health management","author":"Reiter","year":"2021"},{"key":"ref203","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s10846-020-01293-y","article-title":"Health monitoring system for autonomous vehicles using dynamic Bayesian networks for diagnosis and prognosis","volume":"101","author":"Gomes","year":"2021","journal-title":"J Intell Robot Syst"},{"key":"ref204","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1109\/TII.2021.3072045","article-title":"Lightweight computational intelligence for IoT health monitoring of off-road vehicles: enhanced selection log-scaled mutation GA structured ANN","volume":"18","author":"Gupta","year":"2021","journal-title":"IEEE Trans Ind Inform"},{"key":"ref205","article-title":"Impact of AI on the automobile industry in the U.S","author":"Koricanac","year":"2021","journal-title":"SSRN Electron J"},{"key":"ref206","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/j.promfg.2020.03.068","article-title":"Collaborative robotics research: subiko project","volume":"46","author":"Tokody","year":"2020","journal-title":"Procedia Manuf"},{"key":"ref207","first-page":"423","article-title":"The role of artificial intelligence in automotive design","volume":"61","author":"Despot","year":"2023","journal-title":"KNOWLEDGE\u2014Int J"},{"key":"ref208","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1080\/00207543.2021.1988750","article-title":"Design and development of automobile assembly model using federated artificial intelligence with smart contract","volume":"60","author":"Manimuthu","year":"2021","journal-title":"Int J Prod Res"},{"key":"ref209","first-page":"102317","article-title":"How can artificial intelligence enhance car manufacturing? A Delphi study-based identification and assessment of general use cases","volume":"58","author":"Demlehner","year":"2021","journal-title":"Int J Inf Manage"},{"key":"ref210","doi-asserted-by":"crossref","first-page":"102375","DOI":"10.1016\/j.technovation.2021.102375","article-title":"Prerequisites for the adoption of AI technologies in manufacturing-Evidence from a worldwide sample of manufacturing companies","volume":"110","author":"Kinkel","year":"2022","journal-title":"Technovation"},{"key":"ref211","doi-asserted-by":"crossref","first-page":"120889","DOI":"10.1016\/j.techfore.2021.120889","article-title":"Multi-layered coding-based study on optimization algorithms for automobile production logistics scheduling","volume":"170","author":"Yue","year":"2021","journal-title":"Technol Forecast Soc Change"},{"key":"ref212","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1007\/s10696-021-09430-x","article-title":"AI for in-line vehicle sequence controlling: development and evaluation of an adaptive machine learning artifact to predict sequence deviations in a mixed-model production line","volume":"34","author":"Stauder","year":"2022","journal-title":"Flexible Serv Manuf J"},{"key":"ref213","doi-asserted-by":"crossref","first-page":"102864","DOI":"10.1016\/j.tre.2022.102864","article-title":"Application of blockchain and smart contracts in autonomous vehicle supply chains: an experimental design","volume":"165","author":"Arunmozhi","year":"2022","journal-title":"Transp Res Part E: Logist Transp Rev"},{"key":"ref214","series-title":"Journal of Physics: Conference Series","article-title":"Influence of artificial intelligence in automotive industry","author":"Soegoto","year":"2019"},{"key":"ref215","first-page":"10","article-title":"Revolutionizing automotive supply chain: enhancing inventory management with AI and machine learning","volume":"3","author":"Mandala","year":"2024","journal-title":"Univ J Comput Sci Commun"},{"key":"ref216","first-page":"11","author":"Evangeliou","year":"2022","journal-title":"Artificial intelligence for digitising industry\u2212applications"},{"key":"ref217","first-page":"75","article-title":"Role of artificial intelligence in supply chain","volume":"19","author":"Borodavko","year":"2021","journal-title":"Acad J Manuf Eng"},{"key":"ref218","first-page":"2","article-title":"Predictive maintenance in the automotive sector: a literature review","volume":"27","author":"Arena","year":"2021","journal-title":"Math Comput Appl"},{"key":"ref219","doi-asserted-by":"crossref","first-page":"14536","DOI":"10.3390\/su142114536","article-title":"A systematic literature review of the predictive maintenance from transportation systems aspect","volume":"14","author":"Ers\u00f6z","year":"2022","journal-title":"Sustainability"},{"key":"ref220","first-page":"951","article-title":"Artificial intelligence-driven vehicle fault diagnosis to revolutionize automotive maintenance: a review","volume":"141","author":"Hossain","year":"2024","journal-title":"Comput Model Eng Sci"},{"key":"ref221","first-page":"1","article-title":"The study of trends in AI applications for vehicle maintenance through keyword co-occurrence network analysis","volume":"14","author":"Li","year":"2023","journal-title":"Int J Progn Health Manag"},{"key":"ref222","doi-asserted-by":"crossref","first-page":"107864","DOI":"10.1016\/j.ress.2021.107864","article-title":"Predictive maintenance enabled by machine learning: use cases and challenges in the automotive industry","volume":"215","author":"Theissler","year":"2021","journal-title":"Reliab Eng Syst Saf"},{"key":"ref223","first-page":"932","article-title":"Physics model-based design for predictive maintenance in autonomous vehicles using AI","volume":"11","author":"Aravind","year":"2023","journal-title":"Int J Sci Res Manag"},{"key":"ref224","first-page":"1","article-title":"Artificial intelligence for predictive maintenance of armoured fighting vehicles engine","volume":"3","author":"Narayanan","year":"2023","journal-title":"Indian J Artif Intell Neural Netw"},{"key":"ref225","series-title":"5th International Conference on Information Science, Electrical and Automation Engineering (ISEAE 2023)","first-page":"352","article-title":"A constrained-time-based algorithm for vehicle maintain prediction","author":"Wang","year":"2023"},{"key":"ref226","series-title":"2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT)","first-page":"1","article-title":"Predictive maintenance for commercial vehicles tyres using machine learning","author":"Sharma","year":"2022"},{"key":"ref227","doi-asserted-by":"crossref","first-page":"107919","DOI":"10.1016\/j.ress.2021.107919","article-title":"An integrated deep learning-based approach for automobile maintenance prediction with GIS data","volume":"216","author":"Chen","year":"2021","journal-title":"Reliab Eng Syst Saf"},{"key":"ref228","first-page":"8645","article-title":"Predictive analytics as a service for vehicle health monitoring using edge computing and AK-NN algorithm","volume":"46","author":"Vasavi","year":"2021","journal-title":"Mater Today: Proc"},{"key":"ref229","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/s42154-021-00138-0","article-title":"A novel fault detection, identification and prediction approach for autonomous vehicle controllers using SVM","volume":"4","author":"Biddle","year":"2021","journal-title":"Autom Innov"},{"key":"ref230","doi-asserted-by":"crossref","first-page":"6626024","DOI":"10.1155\/2021\/6626024","article-title":"Health monitoring of automotive suspensions: a LSTM network approach","volume":"2021","author":"Hu","year":"2021","journal-title":"Shock Vib"},{"key":"ref231","series-title":"PHM Society European Conference","first-page":"11","article-title":"Identifying NOx sensor failure for predictive maintenance of diesel engines using explainable AI","author":"Mckinley","year":"2020"},{"key":"ref232","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s41688-020-00042-2","article-title":"Explainable AI framework for imaging-based predictive maintenance for automotive applications and beyond","volume":"4","author":"Krishnamurthy","year":"2020","journal-title":"Data-Enabled Discov Appl"},{"key":"ref233","first-page":"1","article-title":"Predictive maintenance of lead-acid batteries with sparse vehicle operational data","volume":"11","author":"Voronov","year":"2020","journal-title":"Int J Progn Health Manag"},{"key":"ref234","doi-asserted-by":"crossref","first-page":"1392","DOI":"10.1016\/j.procir.2018.03.065","article-title":"Reliability analysis for automobile engines: conditional inference trees","volume":"72","author":"Wang","year":"2018","journal-title":"Procedia CIRP"},{"key":"ref235","doi-asserted-by":"crossref","first-page":"8061514","DOI":"10.1155\/2018\/8061514","article-title":"Vehicle remote health monitoring and prognostic maintenance system","volume":"2018","author":"Shafi","year":"2018","journal-title":"J Adv Transp"},{"key":"ref236","series-title":"2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA)","first-page":"351","article-title":"Mining sensor data for predictive maintenance in the automotive industry","author":"Giobergia","year":"2018"},{"key":"ref237","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.3390\/app12031080","article-title":"The role of IoT devices in sustainable car expenses in the context of the intelligent mobility: a comparative approach","volume":"12","author":"Goikoetxea-Gonzalez","year":"2022","journal-title":"Appl Sci"},{"key":"ref238","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1007\/978-981-16-0719-6_16","author":"Jategaonkar","year":"2021","journal-title":"Emerging solutions for e-Mobility and smart grids"},{"key":"ref239","unstructured":"Morris J. Internal combustion cars will be an expensive luxury compared to electric by 2027 [Internet]. [cited 2022 Feb 26]. Available from: https:\/\/www.forbes.com\/sites\/jamesmorris\/2021\/05\/15\/internal-combustion-cars-will-be-an-expensive-luxury-compared-to-electric-by-2027\/?sh=2782225e5189."},{"key":"ref240","unstructured":"EVs to be cheaper to produce than fossil fuel vehicles by 2027 | Daily Sabah [Internet]. [cited 2022 Feb 26]. Available from: https:\/\/www.dailysabah.com\/business\/automotive\/evs-to-be-cheaper-to-produce-than-fossil-fuel-vehicles-by-2027."},{"key":"ref241","doi-asserted-by":"crossref","first-page":"5303","DOI":"10.3390\/su12135303","article-title":"Evaluation of cost competitiveness of electric vehicles in Malaysia using life cycle cost analysis approach","volume":"12","author":"Mustapa","year":"2020","journal-title":"Sustainability"},{"key":"ref242","series-title":"2018 IEEE Conference on Technologies for Sustainability (SusTech)","first-page":"1","article-title":"Improved range prediction for electric vehicles by a smart tire pressure monitoring system","author":"Fechtner","year":"2018"},{"key":"ref243","first-page":"1552","article-title":"Experimental analysis on battery based health monitoring system for electric vehicle","volume":"45","author":"Selvabharathi","year":"2021","journal-title":"Mater Today: Proc"},{"key":"ref244","doi-asserted-by":"crossref","first-page":"14","DOI":"10.3390\/wevj12010014","article-title":"Electric vehicle charging fault monitoring and warning method based on battery model","volume":"12","author":"Zhang","year":"2021","journal-title":"World Electr Veh J"},{"key":"ref245","first-page":"1","article-title":"Prognostics and health management system for electric vehicles with a hierarchy fusion framework: concepts, architectures, and methods","volume":"2021","author":"Wang","year":"2021","journal-title":"Adv Civil Eng"},{"key":"ref246","article-title":"Toward safety-critical artificial intelligence (AI)-based embedded automotive systems","volume":"8","author":"Blazevic","year":"2024","journal-title":"SAE Int J Connected Automated Veh"},{"key":"ref247","series-title":"SAE technical paper","doi-asserted-by":"crossref","DOI":"10.4271\/2023-36-0042","article-title":"Integrating ergonomic and artificial intelligence in the automotive","author":"Puertas","year":"2024"},{"key":"ref248","doi-asserted-by":"crossref","first-page":"2252","DOI":"10.3390\/rs11192252","article-title":"Sensor reliability in cyber-physical systems using internet-of-things data: a review and case study","volume":"11","author":"Casta\u00f1o","year":"2019","journal-title":"Remote Sens"},{"key":"ref249","doi-asserted-by":"crossref","first-page":"2140","DOI":"10.3390\/s21062140","article-title":"Sensor and sensor fusion technology in autonomous vehicles: a review","volume":"21","author":"Yeong","year":"2021","journal-title":"Sensors"},{"key":"ref250","series-title":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","first-page":"1018","article-title":"Automotive sensor infrastructure-challenges and opportunities","author":"Velusamy","year":"2022"},{"key":"ref251","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1007\/s40812-019-00121-1","article-title":"Micro-work, artificial intelligence and the automotive industry","volume":"46","author":"Tubaro","year":"2019","journal-title":"J Ind Bus Econ"},{"key":"ref252","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1007\/s38314-019-0128-z","article-title":"AI and automotive safety","volume":"14","author":"Wasner","year":"2019","journal-title":"ATZelectron Worldwide"},{"key":"ref253","series-title":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","first-page":"1270","article-title":"Application of AI, IOT and ML for business transformation of the automotive sector","author":"Jain","year":"2022"},{"key":"ref254","doi-asserted-by":"crossref","first-page":"2494","DOI":"10.1109\/TIV.2022.3225403","article-title":"Research on coordinated control of braking mode switching for enhancing switching quality considering communication delay and time-varying model parameters","volume":"8","author":"Zhang","year":"2022","journal-title":"IEEE Trans Intell Veh"},{"key":"ref255","doi-asserted-by":"crossref","first-page":"5450","DOI":"10.3390\/s20195450","article-title":"Cloud2edge elastic AI framework for prototyping and deployment of AI inference engines in autonomous vehicles","volume":"20","author":"Grigorescu","year":"2020","journal-title":"Sensors"},{"key":"ref256","first-page":"3333","article-title":"AI based traffic flow prediction model for connected and autonomous electric vehicles","volume":"70","author":"Thamizhazhagan","year":"2022","journal-title":"Comput Mater Contin"},{"key":"ref257","series-title":"2021 Sixth International Conference on Fog and Mobile Edge Computing (FMEC)","first-page":"1","article-title":"Bird\u2019s-eye view on the automotive cybersecurity landscape & challenges in adopting AI\/ML","author":"Siddiqui","year":"2021"},{"key":"ref258","doi-asserted-by":"crossref","first-page":"360","DOI":"10.3390\/s22010360","article-title":"Attacks to automatous vehicles: a deep learning algorithm for cybersecurity","volume":"22","author":"Aldhyani","year":"2022","journal-title":"Sensors"},{"key":"ref259","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1109\/TITS.2020.3011523","article-title":"New aspects of integrity levels in automotive industry\u2014cybersecurity of automated vehicles","volume":"23","author":"T\u00f6r\u00f6k","year":"2020","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"ref260","doi-asserted-by":"crossref","first-page":"120102","DOI":"10.1016\/j.techfore.2020.120102","article-title":"Cybersecurity threats in the auto industry: tensions in the knowledge environment","volume":"157","author":"Morris","year":"2020","journal-title":"Technol Forecast Soc Change"},{"key":"ref261","series-title":"2023 International Conference on Science, Engineering and Business for Sustainable Development Goals (SEB-SDG)","first-page":"1","article-title":"Systematic review on the recent trends of cybersecurity in automobile industry","author":"Eze","year":"2023"},{"key":"ref262","doi-asserted-by":"crossref","first-page":"1640167","DOI":"10.1155\/2018\/1640167","article-title":"Lightweight cryptographic techniques for automotive cybersecurity","volume":"2018","author":"Jadoon","year":"2018","journal-title":"Wirel Commun Mob Comput"},{"key":"ref263","doi-asserted-by":"crossref","first-page":"13024","DOI":"10.3390\/app132413024","article-title":"A hybrid-cryptography engine for securing intra-vehicle communications","volume":"13","author":"Tiberti","year":"2023","journal-title":"Appl Sci"},{"key":"ref264","series-title":"SAE technical paper","doi-asserted-by":"crossref","DOI":"10.4271\/2024-28-0037","article-title":"Automotive security solution using hardware security module (HSM)","author":"Kumar","year":"2024"},{"key":"ref265","doi-asserted-by":"crossref","first-page":"107053","DOI":"10.1016\/j.compeleceng.2021.107053","article-title":"On the application of sensor authentication with intrinsic physical features to vehicle security","volume":"91","author":"Baldini","year":"2021","journal-title":"Comput Electr Eng"},{"key":"ref266","doi-asserted-by":"crossref","first-page":"9211","DOI":"10.3390\/s22239211","article-title":"Cybersecurity testing for automotive domain: a survey","volume":"22","author":"Luo","year":"2022","journal-title":"Sensors"},{"key":"ref267","doi-asserted-by":"crossref","first-page":"101","DOI":"10.4018\/IJT.20210101.oa2","article-title":"AI4People: ethical guidelines for the automotive sector-fundamental requirements and practical recommendations","volume":"12","author":"L\u00fctge","year":"2021","journal-title":"Int J Technoethics"},{"key":"ref268","first-page":"6","article-title":"Ethical decision making in autonomous vehicles: challenges and research progress","volume":"14","author":"Wang","year":"2020","journal-title":"IEEE Intell Transp Syst Mag"},{"key":"ref269","series-title":"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)","first-page":"127","article-title":"From Sci-Fi to reality: the evolution of human\u2014computer interaction with artificial intelligence","author":"Sharma","year":"2023"},{"key":"ref270","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1109\/COMST.2018.2869360","article-title":"Autonomous cars: research results, issues, and future challenges","volume":"21","author":"Hussain","year":"2018","journal-title":"IEEE Commun Surv Tutorials"},{"key":"ref271","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":"ref272","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1002\/rob.21918","article-title":"A survey of deep learning techniques for autonomous driving","volume":"37","author":"Grigorescu","year":"2020","journal-title":"J Field Robot"},{"key":"ref273","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1109\/JAS.2020.1003021","article-title":"Artificial intelligence applications in the development of autonomous vehicles: a survey","volume":"7","author":"Ma","year":"2020","journal-title":"IEEE\/CAA J Automatica Sinica"},{"key":"ref274","first-page":"7632892","article-title":"Autonomous vehicles and intelligent automation: applications, challenges, and opportunities","volume":"2022","author":"Bathla","year":"2022","journal-title":"Mob Inf Syst"},{"key":"ref275","first-page":"4955","article-title":"Autonomous driving of vehicles based on artificial intelligence","volume":"41","author":"Gao","year":"2021","journal-title":"J Intell Fuzzy Syst"},{"key":"ref276","series-title":"2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS)","first-page":"397","article-title":"Industry 4.0 technologies for smart manufacturing: a systematic review of machine learning methods for predictive maintenance","author":"Sharma","year":"2023"},{"key":"ref277","first-page":"798","article-title":"The role of artificial intelligence in automotive manufacturing and design","volume":"3","author":"Jerry","year":"2023","journal-title":"Int J Adv Resn Sci, Commun Technol"},{"key":"ref278","doi-asserted-by":"crossref","first-page":"93","DOI":"10.57062\/ijpem-st.2022.0017","article-title":"Key enabling technologies for smart factory in automotive industry: status and applications","volume":"1","author":"Lee","year":"2023","journal-title":"Int J Precision Eng Manuf\u2014Smart Technol"},{"key":"ref279","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1007\/s10514-017-9677-2","article-title":"Progress and prospects of the human\u2014robot collaboration","volume":"42","author":"Ajoudani","year":"2018","journal-title":"Auton Robots"},{"key":"ref280","doi-asserted-by":"crossref","first-page":"5663","DOI":"10.3390\/s23125663","article-title":"Human-robot collaborations in smart manufacturing environments: review and outlook","volume":"23","author":"Othman","year":"2023","journal-title":"Sensors"},{"key":"ref281","first-page":"386","article-title":"The changing face of the automotive robotics industry","volume":"49","author":"Bogue","year":"2022","journal-title":"In Robot: Int J Robot Res Appl"},{"key":"ref282","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.mechatronics.2018.08.006","article-title":"Seamless human robot collaborative assembly\u2014an automotive case study","volume":"55","author":"Michalos","year":"2018","journal-title":"Mechatronics"},{"key":"ref283","doi-asserted-by":"crossref","first-page":"2725","DOI":"10.3390\/s22072725","article-title":"Augmented reality for human-robot collaboration and cooperation in industrial applications: a systematic literature review","volume":"22","author":"de Costa","year":"2022","journal-title":"Sensors"},{"key":"ref284","doi-asserted-by":"crossref","first-page":"28343","DOI":"10.1109\/ACCESS.2023.3258681","article-title":"Polyverif: an open-source environment for autonomous vehicle validation and verification research acceleration","volume":"11","author":"Razdan","year":"2023","journal-title":"IEEE Access"},{"key":"ref285","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1109\/TIV.2022.3196396","article-title":"Verification and validation methods for decision-making and planning of automated vehicles: a review","volume":"7","author":"Ma","year":"2022","journal-title":"IEEE Trans Intell Veh"},{"key":"ref286","series-title":"2024 International Conference on Inventive Computation Technologies (ICICT)","first-page":"319","article-title":"The impact of AI on traffic management and safety in the internet of vehicles through mobile edge computing","author":"Ebadinezhad","year":"2024"},{"key":"ref287","doi-asserted-by":"crossref","first-page":"875","DOI":"10.3390\/app13020875","article-title":"A novel deep-learning model for remote driver monitoring in SDN-based internet of autonomous vehicles using 5G technologies","volume":"13","author":"Saleh","year":"2023","journal-title":"Appl Sci"},{"key":"ref288","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11432-018-9596-5","article-title":"AI for 5G: research directions and paradigms","volume":"62","author":"You","year":"2019","journal-title":"Sci China Inf Sci"},{"key":"ref289","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1109\/MNET.011.2000245","article-title":"Research challenges and security threats to AI-driven 5G virtual emotion applications using autonomous vehicles, drones, and smart devices","volume":"34","author":"Kim","year":"2020","journal-title":"IEEE Netw"},{"key":"ref290","first-page":"100399","article-title":"Vehicular intelligence in 6G: networking, communications, and computing","volume":"33","author":"Guo","year":"2022","journal-title":"Veh Commun"},{"key":"ref291","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1038\/s42256-019-0048-x","article-title":"Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead","volume":"1","author":"Rudin","year":"2019","journal-title":"Nat Mach Intell"},{"key":"ref292","doi-asserted-by":"crossref","first-page":"113561","DOI":"10.1016\/j.dss.2021.113561","article-title":"LINDA-BN: an interpretable probabilistic approach for demystifying black-box predictive models","volume":"150","author":"Moreira","year":"2021","journal-title":"Decis Support Syst"},{"key":"ref293","series-title":"37th International Conference on Machine Learning","first-page":"5628","article-title":"Robust and stable black box explanations","author":"Lakkaraju","year":"2020"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-82-3\/TSP_CMC_61749\/TSP_CMC_61749.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T06:32:35Z","timestamp":1763101955000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v82n3\/59944"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":293,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.061749","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}