{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T06:20:22Z","timestamp":1771482022211,"version":"3.50.1"},"reference-count":240,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T00:00:00Z","timestamp":1767571200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T00:00:00Z","timestamp":1768867200000},"content-version":"vor","delay-in-days":15,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100006359","name":"Blekinge Institute of Technology","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100006359","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>This paper explores the integration of Artificial Intelligence Generated Content (AIGC), a rapidly evolving branch of generative AI, with Human-Machine intelligence (HMI) to enhance the functionality of Intelligent Transportation Systems (ITS). As transportation systems grow increasingly complex, adaptive decision-making becomes essential for interpreting vast streams of real-time data from vehicles, infrastructure, and users. AIGC plays a transformative role in optimizing traffic flow through dynamic routing and real-time traffic management, while human intelligence ensures these systems remain responsive to evolving real-world conditions. For safety, AIGC is used to simulate complex driving scenarios for autonomous vehicle training and detect traffic anomalies, with human oversight providing contextual decisions in ambiguous situations. For sustainability, AIGC supports data-driven strategies to reduce emissions and energy use, while human expertise ensures alignment with ethical and environmental goals. This synergy enhances real-time decision-making, improving both accuracy and adaptability across ITS scenarios. The paper presents a comprehensive review of core and supporting AIGC technologies and their applications across key ITS domains. Case studies and initiatives from industry leaders demonstrate practical implementations of AIGC-driven HMI collaboration. To guide future deployments, we propose a conceptual five-layer evaluation framework for assessing AIGC-HMI systems, encompassing functional performance, human interaction, explainability, ethical compliance, and robustness. We also address challenges such as legacy system integration, data privacy, model bias, and scalability. The paper concludes by outlining future research directions, emphasizing the need for scalable, interpretable, and ethically aligned AIGC models. This work contributes to the development of intelligent, adaptive, and trustworthy transportation systems.<\/jats:p>","DOI":"10.1007\/s10462-025-11467-5","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T12:04:14Z","timestamp":1767614654000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Aigc-driven human-machine intelligence in ITS: technologies, applications, evaluation framework, challenges, and future directions"],"prefix":"10.1007","volume":"59","author":[{"given":"Doreen Sebastian","family":"Sarwatt","sequence":"first","affiliation":[]},{"given":"Frank","family":"Kulwa","sequence":"additional","affiliation":[]},{"given":"Adamu Gaston","family":"Philipo","sequence":"additional","affiliation":[]},{"given":"Angela-Aida Karugila","family":"Runyoro","sequence":"additional","affiliation":[]},{"given":"Huansheng","family":"Ning","sequence":"additional","affiliation":[]},{"given":"Jianguo","family":"Ding","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,5]]},"reference":[{"issue":"5","key":"11467_CR1","doi-asserted-by":"crossref","first-page":"2742","DOI":"10.3390\/smartcities6050124","volume":"6","author":"A Adel","year":"2023","unstructured":"Adel A (2023) Unlocking the future: fostering human-machine collaboration and driving intelligent automation through industry 5.0 in smart cities. Smart Cities 6(5):2742\u20132782","journal-title":"Smart Cities"},{"key":"11467_CR2","doi-asserted-by":"crossref","DOI":"10.1016\/j.mejo.2022.105634","volume":"130","author":"J Ajayan","year":"2022","unstructured":"Ajayan J, Nirmal D IV, Binola KJ et al (2022) Advances in neuromorphic devices for the hardware implementation of neuromorphic computing systems for future artificial intelligence applications: a critical review. Microelectron J 130:105634","journal-title":"Microelectron J"},{"key":"11467_CR3","doi-asserted-by":"crossref","unstructured":"Al-Azzawi M, Doan D, Sipola T, et\u00a0al (2025) Red teaming with artificial intelligence-driven cyberattacks: a scoping review. arXiv preprint arXiv:2503.19626","DOI":"10.1007\/978-3-031-60215-3_13"},{"issue":"1","key":"11467_CR4","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1007\/s10922-022-09717-w","volume":"31","author":"M Alharby","year":"2023","unstructured":"Alharby M (2023) Transaction latency within permissionless blockchains: analysis, improvement, and security considerations. J Netw Syst Manag 31(1):22","journal-title":"J Netw Syst Manag"},{"key":"11467_CR5","doi-asserted-by":"publisher","unstructured":"Amar AN, Sanju SA (2024) Real-time and low latency dynamic computational offloading deep neural network technique in the internet of vehicles (IoV). Preprint, Research Square, https:\/\/doi.org\/10.21203\/rs.3.rs-5285396\/v1, accessed October 20, 2025","DOI":"10.21203\/rs.3.rs-5285396\/v1"},{"key":"11467_CR6","first-page":"272","volume-title":"Int Conf Emerg Internetw","author":"P Ampririt","year":"2022","unstructured":"Ampririt P, Qafzezi E, Bylykbashi K et al (2022) A fuzzy-based system for slice service level agreement in 5g wireless networks: effect of traffic load parameter. Int Conf Emerg Internetw. Springer, Data & Web Technologies, pp 272\u2013282"},{"key":"11467_CR7","doi-asserted-by":"crossref","unstructured":"Andreoni M, Lunardi WT, Lawton G, et\u00a0al (2024) Enhancing autonomous system security and resilience with generative AI: a comprehensive survey. IEEE Access","DOI":"10.1109\/ACCESS.2024.3439363"},{"key":"11467_CR8","doi-asserted-by":"crossref","unstructured":"Arnold Z, Schiff DS, Schiff KJ et al (2024). Introducing the AI governance and regulatory archive (AGORA): an analytic infrastructure for navigating the emerging AI governance landscape and society, pp 39\u201348","DOI":"10.1609\/aies.v7i1.31615"},{"key":"11467_CR9","volume":"147","author":"ZS Asaei-Moamam","year":"2023","unstructured":"Asaei-Moamam ZS, Safi-Esfahani F, Mirjalili S et al (2023) Air quality particulate-pollution prediction applying GAN network and the neural turing machine. Appl Soft Comput 147:110723","journal-title":"Appl Soft Comput"},{"issue":"6","key":"11467_CR10","doi-asserted-by":"crossref","first-page":"455","DOI":"10.3233\/AIS-220161","volume":"14","author":"B Aveno\u011flu","year":"2022","unstructured":"Aveno\u011flu B, Koeman VJ, Hindriks KV (2022) A cloud-based middleware for multi-modal interaction services and applications. J Ambient Intell Smart Environ 14(6):455\u2013481","journal-title":"J Ambient Intell Smart Environ"},{"key":"11467_CR11","doi-asserted-by":"crossref","unstructured":"Aydin MM, Da\u011fl\u0131 E (2025) The contribution of intelligent systems (IS) on transport and planning studies. In: Interdisciplinary approaches to transportation and urban planning. IGI Global, pp 83\u2013120","DOI":"10.4018\/979-8-3693-6695-0.ch004"},{"key":"11467_CR12","doi-asserted-by":"crossref","unstructured":"Aziz AFA, Tiun S, Ruslan N (2023) End to end text to speech synthesis for malay language using tacotron and tacotron 2. Int J Adv Comput Sci Appl, 14(6)","DOI":"10.14569\/IJACSA.2023.0140644"},{"key":"11467_CR13","doi-asserted-by":"crossref","unstructured":"Banerjee S (2024) Intelligent cloud systems: AI-driven enhancements in scalability and predictive resource management. Int Adv Res Sci, Commun Technol. pp 266\u2013276","DOI":"10.48175\/IJARSCT-22840"},{"key":"11467_CR14","unstructured":"Bang H, Dave A, Tzortzoglou FN, et\u00a0al (2024) On mobility equity and the promise of emerging transportation systems. arXiv preprint arXiv:2408.15401"},{"key":"11467_CR15","doi-asserted-by":"crossref","unstructured":"Behura A, Patra R (2025) Challenges and future prospects of integrating quantum computing into intelligent transportation systems: exploring quantum innovations in transportation. In: Integration of AI, quantum computing, and semiconductor technology, pp 183\u2013208","DOI":"10.4018\/979-8-3693-7076-6.ch009"},{"issue":"4\/5","key":"11467_CR16","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1147\/JRD.2019.2942287","volume":"63","author":"RK Bellamy","year":"2019","unstructured":"Bellamy RK, Dey K, Hind M et al (2019) Ai fairness 360: an extensible toolkit for detecting and mitigating algorithmic bias. IBM J Res Dev 63(4\/5):4","journal-title":"IBM J Res Dev"},{"key":"11467_CR17","doi-asserted-by":"crossref","unstructured":"Bengesi S, El-Sayed H, Sarker MK, et\u00a0al (2024) Advancements in generative AI: a comprehensive review of GANs, GPT, autoencoders, diffusion models, and transformers. IEEE Access","DOI":"10.1109\/ACCESS.2024.3397775"},{"key":"11467_CR18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.neunet.2021.02.003","volume":"139","author":"A Bihlo","year":"2021","unstructured":"Bihlo A (2021) A generative adversarial network approach to (ensemble) weather prediction. Neural Netw 139:1\u201316","journal-title":"Neural Netw"},{"key":"11467_CR19","unstructured":"Blanchfield D (2023) Artificial intelligence generated content (aigc) is transforming the digital landscape. https:\/\/elnion.com\/2023\/08\/10\/artificial-intelligence-generated-content-aigc-is-transforming-the-digital-landscape\/, accessed October 17, 2025"},{"key":"11467_CR20","doi-asserted-by":"crossref","unstructured":"Boujezza H, Boubakri A (2024) A new redundant intelligent architecture to improve the operational safety of autonomous vehicles. pp 140\u2013152","DOI":"10.1007\/978-3-031-57840-3_13"},{"key":"11467_CR21","doi-asserted-by":"crossref","unstructured":"Butt TA (2021) Future smart cities: vision, challenges and technology trends. pp 353\u2013359","DOI":"10.1145\/3512576.3512639"},{"key":"11467_CR22","doi-asserted-by":"crossref","unstructured":"Ca\u00f1as PN, Nieto M, Otaegui O, et\u00a0al (2024) A methodology to enhance transparency for trustworthy artificial intelligence for cooperative, connected, and automated mobility. In: SAE international journal of connected and automated vehicles 8(12-08-01-0010)","DOI":"10.4271\/12-08-01-0010"},{"key":"11467_CR23","doi-asserted-by":"crossref","unstructured":"Carlosama-Perachimba D, C\u00e1rdenas LL, Le\u00f3n JPA (2024) Impact of Data Augmentation using SMOTE and GAN on machine learning predictions for vehicular routing datasets. pp 1\u20136","DOI":"10.1109\/ETCM63562.2024.10746230"},{"key":"11467_CR24","unstructured":"Casale P (2020) How does artificial intelligence improve mapmaking? https:\/\/www.tomtom.com\/newsroom\/behind-the-map\/artificial-intelligence-map-making\/, accessed October 18, 2025"},{"key":"11467_CR25","doi-asserted-by":"crossref","first-page":"34080","DOI":"10.1109\/ACCESS.2023.3264216","volume":"11","author":"RKC Chan","year":"2023","unstructured":"Chan RKC, Lim JMY, Parthiban R (2023) Missing traffic data imputation for artificial intelligence in intelligent transportation systems: review of methods, limitations, and challenges. IEEE Access 11:34080\u201334093","journal-title":"IEEE Access"},{"key":"11467_CR26","doi-asserted-by":"crossref","first-page":"e000078","DOI":"10.55329\/xwwy8052","volume":"9","author":"C Chand","year":"2025","unstructured":"Chand C, Jashami H, Wang H et al (2025) Evaluation of the human interaction with automated vehicles on highways. Traffic Saf Res 9:e000078\u2013e000078","journal-title":"Traffic Saf Res"},{"issue":"1","key":"11467_CR27","doi-asserted-by":"crossref","first-page":"93","DOI":"10.5817\/MUJLT2024-1-4","volume":"18","author":"G Chaudhary","year":"2024","unstructured":"Chaudhary G (2024) Unveiling the black box: bringing algorithmic transparency to AI. Masaryk Univer J Law Technol 18(1):93\u2013122","journal-title":"Masaryk Univer J Law Technol"},{"key":"11467_CR28","unstructured":"Chen E (2024) The critical role of transparency & explainability in aigc-driven systems for ethical & trustworthy implementation. Accessed October. 18, 2025, https:\/\/quickcreator.io\/articles2\/aigc-transparency-explainability-ethical-trustworthy-implementation\/"},{"issue":"11","key":"11467_CR29","doi-asserted-by":"crossref","first-page":"2909","DOI":"10.1093\/comjnl\/bxac085","volume":"65","author":"P Chen","year":"2022","unstructured":"Chen P, Liu H, Xin R et al (2022) Effectively detecting operational anomalies in large-scale IoT data infrastructures by using a GAN-based predictive model. Comput J 65(11):2909\u20132925","journal-title":"Comput J"},{"key":"11467_CR30","doi-asserted-by":"crossref","unstructured":"Chen X, Wang Z, Dong F, et\u00a0al (2025) Multimodal air-quality prediction: a multimodal feature fusion network based on shared-specific modal feature decoupling. Environ Modell Softw, p 106553","DOI":"10.1016\/j.envsoft.2025.106553"},{"issue":"1","key":"11467_CR31","first-page":"158","volume":"62","author":"DKY Cheng","year":"2026","unstructured":"Cheng DKY, Sazali N, Kettner M et al (2026) Synthetic image data generation via rendering techniques for training ai-based instance segmentation. J Adv Res Appl Sci Eng Technol 62(1):158\u2013169","journal-title":"J Adv Res Appl Sci Eng Technol"},{"key":"11467_CR32","doi-asserted-by":"crossref","first-page":"29316","DOI":"10.36948\/ijfmr.2024.v06i05.29316","volume":"6","author":"BR Cherukuri","year":"2024","unstructured":"Cherukuri BR (2024) Edge computing vs. cloud computing: a comparative analysis for real-time ai applications. Int J Multidiscip Res 6:29316","journal-title":"Int J Multidiscip Res"},{"key":"11467_CR33","doi-asserted-by":"crossref","unstructured":"Coeurdoux F, Dobigeon N, Chainais P (2022) Learning optimal transport between two empirical distributions with normalizing flows. In: Joint European conference on machine learning and knowledge discovery in databases, Springer, pp 275\u2013290","DOI":"10.1007\/978-3-031-26419-1_17"},{"issue":"5","key":"11467_CR34","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1111\/tesg.12476","volume":"112","author":"A Collins","year":"2021","unstructured":"Collins A, Cox A, Torrisi G (2021) Searching for a smart city: a bibliographic analysis of \u2018public facing\u2019eu smart city projects. Tijdschr Econ Soc Geogr 112(5):549\u2013565","journal-title":"Tijdschr Econ Soc Geogr"},{"key":"11467_CR35","unstructured":"Daws R (2023) TOMTOM and Microsoft unveil Generative AI for connected vehicles. Accessed October. 21, 2025, https:\/\/iottechnews.com\/news\/tomtom-microsoft-unveil-generative-ai-connected-vehicles\/"},{"key":"11467_CR36","doi-asserted-by":"crossref","DOI":"10.1016\/j.sysarc.2023.102929","volume":"142","author":"X Deng","year":"2023","unstructured":"Deng X, Wang L, Gui J et al (2023) A review of 6g autonomous intelligent transportation systems: mechanisms, applications and challenges. J Syst Architect 142:102929","journal-title":"J Syst Architect"},{"key":"11467_CR37","doi-asserted-by":"crossref","unstructured":"Dey D, Bhaumik D (2024) In: Proceedings of the AAAI\/ACM conference on AI, APPRAISE: a governance framework for innovation with artificial intelligence systems and society, pp 328\u2013340","DOI":"10.1609\/aies.v7i1.31640"},{"issue":"6","key":"11467_CR38","doi-asserted-by":"crossref","first-page":"2938","DOI":"10.3390\/s23062938","volume":"23","author":"E Dilek","year":"2023","unstructured":"Dilek E, Dener M (2023) Computer vision applications in intelligent transportation systems: a survey. Sensors 23(6):2938","journal-title":"Sensors"},{"key":"11467_CR39","unstructured":"Dou F, Ye J, Yuan G et al (2023) Towards artificial general intelligence (agi), in the internet of things (iot): opportunities and challenges. arXiv preprint arXiv:2309.07438"},{"issue":"11","key":"11467_CR40","doi-asserted-by":"crossref","first-page":"8533","DOI":"10.3390\/su15118533","volume":"15","author":"Y Du","year":"2023","unstructured":"Du Y, Sun F, Jiao F et al (2023) The identification of intersection entrance accidents based on autoencoder. Sustainability 15(11):8533","journal-title":"Sustainability"},{"key":"11467_CR41","doi-asserted-by":"crossref","unstructured":"Duran K, Shin H, Duong TQ et al (2025) Gentwin: Generative ai-powered digital twinning for adaptive management in iot networks. In: IEEE transactions on cognitive communications and networking","DOI":"10.1109\/TCCN.2025.3527719"},{"key":"11467_CR42","doi-asserted-by":"crossref","unstructured":"Ercan SIA, Akin O (2024) 2024 8th international artificial intelligence and data processing symposium (IDAP)In: IEEE, international insights on ai risk: comparative analysis of international organizations. pp 1\u20138","DOI":"10.1109\/IDAP64064.2024.10711117"},{"issue":"21","key":"11467_CR43","doi-asserted-by":"crossref","first-page":"4261","DOI":"10.3390\/electronics13214261","volume":"13","author":"M Erel-\u00d6z\u00e7evik","year":"2024","unstructured":"Erel-\u00d6z\u00e7evik M, \u00d6z\u00e7ift A, \u00d6z\u00e7evik Y et al (2024) A genetic optimized federated learning approach for joint consideration of end-to-end delay and data privacy in vehicular networks. Electronics 13(21):4261","journal-title":"Electronics"},{"key":"11467_CR44","unstructured":"European Commission (2022) Liability rules for artificial intelligence. Accessed October. 18, 2025, https:\/\/commission.europa.eu\/business-economy-euro\/doing-business-eu\/contract-rules\/digital-contracts\/liability-rules-artificial-intelligence_en"},{"issue":"3","key":"11467_CR45","doi-asserted-by":"crossref","first-page":"606","DOI":"10.51594\/csitrj.v5i3.909","volume":"5","author":"OA Farayola","year":"2024","unstructured":"Farayola OA, Olorunfemi OL, Shoetan PO (2024) Data privacy and security in it: a review of techniques and challenges. Comput Sci IT Res J 5(3):606\u2013615","journal-title":"Comput Sci IT Res J"},{"key":"11467_CR46","doi-asserted-by":"crossref","unstructured":"Fenoglio E, Kazim E (2024) AI explainability, interpretability, and transparency. In: The Elgar companion to applied AI ethics. Edward Elgar Publishing, pp 66\u201394","DOI":"10.4337\/9781803928241.00010"},{"key":"11467_CR48","doi-asserted-by":"crossref","unstructured":"Fu R, Bi Y, Han G, et\u00a0al (2023) MAGVA: an open-set fault diagnosis model based on multi-hop attentive graph variational autoencoder for autonomous vehicles. In: IEEE transactions on intelligent transportation systems","DOI":"10.1109\/TITS.2023.3300911"},{"issue":"1","key":"11467_CR47","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1007\/s44212-024-00042-y","volume":"3","author":"J Fu","year":"2024","unstructured":"Fu J, Han H, Su X et al (2024) Towards human-ai collaborative urban science research enabled by pre-trained large language models. Urban Inform 3(1):8","journal-title":"Urban Inform"},{"issue":"5","key":"11467_CR49","doi-asserted-by":"crossref","first-page":"3798","DOI":"10.1109\/TMECH.2021.3132459","volume":"27","author":"Y Gao","year":"2021","unstructured":"Gao Y, Liu X, Xiang J (2021) Fault detection in gears using fault samples enlarged by a combination of numerical simulation and a generative adversarial network. IEEE\/ASME Trans Mechatron 27(5):3798\u20133805","journal-title":"IEEE\/ASME Trans Mechatron"},{"key":"11467_CR51","doi-asserted-by":"crossref","unstructured":"Ge Q, Ma S (2024) Parking space detection based on semi-supervised autoencoders. In: 2024 5th International conference on artificial intelligence and electromechanical automation (AIEA), IEEE, pp 1121\u20131125","DOI":"10.1109\/AIEA62095.2024.10692361"},{"issue":"12","key":"11467_CR50","doi-asserted-by":"crossref","first-page":"2325","DOI":"10.1049\/itr2.12539","volume":"18","author":"C Ge","year":"2024","unstructured":"Ge C, Qin S (2024) Digital twin intelligent transportation system (dt-its)\u2014a systematic review. IET Intel Transport Syst 18(12):2325\u20132358","journal-title":"IET Intel Transport Syst"},{"issue":"1","key":"11467_CR52","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3630266","volume":"23","author":"SK Ghosh","year":"2024","unstructured":"Ghosh SK, Raha A, Raghunathan V et al (2024) Partnner: Platform-agnostic adaptive edge-cloud dnn partitioning for minimizing end-to-end latency. ACM Trans Embedded Comput Syst 23(1):1\u201338","journal-title":"ACM Trans Embedded Comput Syst"},{"key":"11467_CR53","doi-asserted-by":"crossref","unstructured":"Golam M, Tayeb AM, Khatun MA, et\u00a0al (2025) Blackicenet: Explainable ai-enhanced multimodal for black ice detection to prevent accident in intelligent vehicles. IEEE Internet Things J","DOI":"10.1109\/JIOT.2025.3530565"},{"issue":"1","key":"11467_CR54","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1186\/s13677-022-00297-3","volume":"11","author":"J Gu","year":"2022","unstructured":"Gu J, Anjum A, Wu Y et al (2022) The least-used key selection method for information retrieval in large-scale cloud-based service repositories. J Cloud Comput 11(1):30","journal-title":"J Cloud Comput"},{"key":"11467_CR55","doi-asserted-by":"crossref","unstructured":"Guo J, Wang M, Yin H, et\u00a0al (2024) Large language models and artificial intelligence generated content technologies meet communication networks. IEEE Internet Things J","DOI":"10.1109\/JIOT.2024.3496491"},{"issue":"2","key":"11467_CR56","volume":"18","author":"NR Haddaway","year":"2022","unstructured":"Haddaway NR, Page MJ, Pritchard CC et al (2022) Prisma 2020: An R package and shiny app for producing prisma 2020-compliant flow diagrams, with interactivity for optimised digital transparency and open synthesis. Campbell Syst Rev 18(2):e1230","journal-title":"Campbell Syst Rev"},{"key":"11467_CR57","unstructured":"Hanif U (2023) Research paper summarization using text-to-text transfer transformer (T5) model. PhD thesis, Dublin, National College of Ireland"},{"key":"11467_CR58","doi-asserted-by":"crossref","unstructured":"Hart SG, Staveland LE (1988) Development of nasa-tlx (task load index): results of empirical and theoretical research. In: Advances in psychology, vol\u00a052. Elsevier, pp 139\u2013183","DOI":"10.1016\/S0166-4115(08)62386-9"},{"key":"11467_CR59","doi-asserted-by":"crossref","unstructured":"Haruna R, Obiniyi A, Abdulkarim M et al (2022) Automatic summarization of scientific documents using transformer architectures: a review. In: 2022 5th Information technology for education and development (ITED), pp 1\u20136","DOI":"10.1109\/ITED56637.2022.10051602"},{"key":"11467_CR60","unstructured":"Hayagreevan H, Khamaru S (2024) Security of and by generative AI platforms. arXiv preprint arXiv:2410.13899"},{"issue":"4","key":"11467_CR61","doi-asserted-by":"crossref","first-page":"1581","DOI":"10.1109\/TR.2021.3090310","volume":"70","author":"A He","year":"2021","unstructured":"He A, Jin X (2021) Deep variational autoencoder classifier for intelligent fault diagnosis adaptive to unseen fault categories. IEEE Trans Reliab 70(4):1581\u20131595","journal-title":"IEEE Trans Reliab"},{"key":"11467_CR62","doi-asserted-by":"crossref","unstructured":"He J, Lai B, Kang J, et\u00a0al (2024) Securing federated diffusion model with dynamic quantization for generative AI services in multiple-access artificial intelligence of things. IEEE Internet Things J","DOI":"10.1109\/JIOT.2024.3420696"},{"key":"11467_CR63","unstructured":"Hennessy J (2022) Colossal-AI accelerates AIGC, snowpark for python is GA and the new beta release of NVIDIA omniverse. Accessed October 22, 2025, https:\/\/lightning.ai\/pages\/community\/colossal-ais-accelerates-accelerates-aigc-snowpark-for-python-is-ga-and-the-new-beta-release-of-nvidia-omniverse\/"},{"issue":"2","key":"11467_CR64","first-page":"68","volume":"1","author":"C Hern\u00e1ndez","year":"2021","unstructured":"Hern\u00e1ndez C (2021) Human-machine collaboration in cyber incident response for autonomous vehicles-a case study approach: investigates human-machine collaboration in cyber incident response for AVs through a series of case studies. Afr J Artif Intell Sustain Dev 1(2):68\u201374","journal-title":"Afr J Artif Intell Sustain Dev"},{"key":"11467_CR65","unstructured":"Heusel M, Ramsauer H, Unterthiner T et al (2017) Gans trained by a two time-scale update rule converge to a local nash equilibrium, Adv Neural Inform Process Syst 30"},{"key":"11467_CR66","doi-asserted-by":"crossref","unstructured":"Holistic AI (2023) Iso and iec make foundational standard on artificial intelligence publicly availables. Accessed October. 19, 2025, https:\/\/www.holisticai.com\/news\/iso-iec-22989-foundational-standard-on-ai-open-source","DOI":"10.4324\/9781003463979-4"},{"key":"11467_CR67","first-page":"1","volume-title":"2024 Third international conference on sustainable mobility applications","author":"M Hossain","year":"2024","unstructured":"Hossain M, Khalid H, Rao AP et al (2024a) Comprehensive review of AI, IoT, and ML in enhancing urban mobility and reducing carbon footprints. 2024 Third international conference on sustainable mobility applications. IEEE, Renewables and Technology (SMART), pp 1\u20136"},{"key":"11467_CR68","doi-asserted-by":"crossref","unstructured":"Hossain MT, La H, Badsha S (2024b) Rampart: Reinforcing autonomous multi-agent protection through adversarial resistance in transportation. J Autonom Transp Syst","DOI":"10.1145\/3643137"},{"key":"11467_CR69","doi-asserted-by":"crossref","unstructured":"Hu Y, Ye D, Kang J, et\u00a0al (2024) A cloud-edge collaborative architecture for multimodal llms-based advanced driver assistance systems in iot networks. IEEE Internet Things J","DOI":"10.1109\/JIOT.2024.3509628"},{"key":"11467_CR71","doi-asserted-by":"crossref","unstructured":"Huang Y (2024) Exploring deep learning-based generative image techniques: methods and applications. In: 2024 International conference on artificial intelligence and communication (ICAIC 2024), Atlantis Press, pp 488\u2013501","DOI":"10.2991\/978-94-6463-512-6_52"},{"issue":"11","key":"11467_CR70","doi-asserted-by":"crossref","first-page":"16181","DOI":"10.1109\/TITS.2024.3420959","volume":"25","author":"W Huang","year":"2024","unstructured":"Huang W, Liu H, Huang Z et al (2024) Safety-aware human-in-the-loop reinforcement learning with shared control for autonomous driving. IEEE Trans Intell Transp Syst 25(11):16181\u201316192","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"11467_CR72","doi-asserted-by":"crossref","DOI":"10.1016\/j.cosrev.2023.100553","volume":"48","author":"G Iglesias","year":"2023","unstructured":"Iglesias G, Talavera E, D\u00edaz-\u00c1lvarez A (2023) A survey on gans for computer vision: recent research, analysis and taxonomy. Comput Sci Rev 48:100553","journal-title":"Comput Sci Rev"},{"key":"11467_CR73","unstructured":"INRIX (2023) INRIX announces compass, a new mobility intelligence technology powered by 20+ years of proprietary data and amazon bedrock generative AI. Accessed October 20, 2025, https:\/\/inrix.com\/press-releases\/bedrock-compass-gen-ai\/"},{"key":"11467_CR74","unstructured":"INRIX (2024) INRIX launches new artificial intelligence traffic solution. Accessed October. 17, 2025, https:\/\/inrix.com\/press-releases\/inrix-launches-new-artificial-intelligence-traffic-solution\/#:~:text=INRIX"},{"key":"11467_CR75","doi-asserted-by":"crossref","unstructured":"Irfan MS, Dasgupta S, Rahman M (2024) Towards transportation digital twin systems for traffic safety and mobility: a review. IEEE Internet Things J","DOI":"10.1109\/JIOT.2024.3395186"},{"issue":"2","key":"11467_CR76","first-page":"277","volume":"25","author":"S Jamal","year":"2024","unstructured":"Jamal S, Wimmer H, Rebman CM Jr (2024) Perception and evaluation of text-to-image generative AI models: a comparative study of DALL-E, Google Imagen, GROK, and stable diffusion. Issues Inf Syst 25(2):277\u2013292","journal-title":"Issues Inf Syst"},{"issue":"3","key":"11467_CR77","doi-asserted-by":"crossref","first-page":"749","DOI":"10.3390\/s25030749","volume":"25","author":"SL Jeng","year":"2025","unstructured":"Jeng SL (2025) Generative adversarial network for synthesizing multivariate time-series data in electric vehicle driving scenarios. Sensors 25(3):749","journal-title":"Sensors"},{"issue":"2","key":"11467_CR78","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1007\/s11227-022-04686-y","volume":"79","author":"CH Jeong","year":"2023","unstructured":"Jeong CH, Yi MY (2023) Correcting rainfall forecasts of a numerical weather prediction model using generative adversarial networks. J Supercomput 79(2):1289\u20131317","journal-title":"J Supercomput"},{"issue":"2","key":"11467_CR79","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s11235-024-01126-5","volume":"86","author":"AV Jha","year":"2024","unstructured":"Jha AV, Appasani B, Khan MS et al (2024) 6g for intelligent transportation systems: standards, technologies, and challenges. Telecommun Syst 86(2):241\u2013268","journal-title":"Telecommun Syst"},{"issue":"12","key":"11467_CR80","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3571730","volume":"55","author":"Z Ji","year":"2023","unstructured":"Ji Z, Lee N, Frieske R et al (2023) Survey of hallucination in natural language generation. ACM Comput Surv 55(12):1\u201338","journal-title":"ACM Comput Surv"},{"issue":"2","key":"11467_CR81","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1007\/s11633-022-1372-x","volume":"20","author":"L Jing","year":"2023","unstructured":"Jing L, Li Y, Xu J et al (2023) Vision enhanced generative pre-trained language model for multimodal sentence summarization. Mach Intell Res 20(2):289\u2013298","journal-title":"Mach Intell Res"},{"issue":"3","key":"11467_CR82","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1093\/ulr\/unae040","volume":"29","author":"P Kashefi","year":"2024","unstructured":"Kashefi P, Kashefi Y, Ghafouri Mirsaraei A (2024) Shaping the future of AI: balancing innovation and ethics in global regulation. Uniform Law Rev 29(3):524\u2013548","journal-title":"Uniform Law Rev"},{"key":"11467_CR83","doi-asserted-by":"crossref","unstructured":"Khalil RA, Safelnasr Z, Yemane N, et\u00a0al (2024) Advanced learning technologies for intelligent transportation systems: prospects and challenges. IEEE Open J Vehic Technol","DOI":"10.36227\/techrxiv.170906004.46353480\/v1"},{"key":"11467_CR85","doi-asserted-by":"crossref","unstructured":"Kim SW, Philion J, Torralba A et al (2021) DriveGAN: Towards a controllable high-quality neural simulation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 5820\u20135829","DOI":"10.1109\/CVPR46437.2021.00576"},{"key":"11467_CR84","unstructured":"Kim D, Hong S, Choi YH (2023) SC VALL-E: style-controllable zero-shot text to speech synthesizer. arXiv preprint arXiv:2307.10550"},{"key":"11467_CR86","doi-asserted-by":"crossref","unstructured":"Li J, Zhu S, Yang HH, et\u00a0al (2024a) What does artificial intelligence generated content bring to teaching and learning? A literature review on AIGC in education. In: 2024 International symposium on educational technology (ISET), IEEE, pp 18\u201323","DOI":"10.1109\/ISET61814.2024.00013"},{"key":"11467_CR88","doi-asserted-by":"crossref","unstructured":"Li Y, Jin K, Tang J, et\u00a0al (2024b) Diffusion-enabled digital twin synchronization for aigc services in space-air-ground integrated networks. IEEE Internet Things J","DOI":"10.1109\/JIOT.2024.3523324"},{"key":"11467_CR87","doi-asserted-by":"crossref","unstructured":"Li X, Deng R, Wei J, et\u00a0al (2025) Aigc-driven real-time interactive 4d traffic scene generation in vehicular networks. IEEE Netw","DOI":"10.22541\/au.173627558.87858747\/v1"},{"key":"11467_CR89","doi-asserted-by":"crossref","unstructured":"Liang J, Li X (2024) Construction of emergency rescue virtual exercise platform based on AIGC perspective. In: Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area international conference on education digitalization and computer science, pp 312\u2013316","DOI":"10.1145\/3686424.3686477"},{"key":"11467_CR90","unstructured":"Lin CY (2004) Rouge: a package for automatic evaluation of summaries. Text Summarization Branches Out pp 74\u201381"},{"key":"11467_CR91","doi-asserted-by":"crossref","unstructured":"Lin H, Liu Y, Li S, et\u00a0al (2023a) How generative adversarial networks promote the development of intelligent transportation systems: a survey. IEEE\/CAA J Automatica Sinica","DOI":"10.1109\/JAS.2023.123744"},{"key":"11467_CR93","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1109\/OJCS.2023.3260732","volume":"4","author":"Y Lin","year":"2023","unstructured":"Lin Y, Du H, Niyato D et al (2023b) Blockchain-aided secure semantic communication for ai-generated content in metaverse. IEEE Open J Comput Soc 4:72\u201383","journal-title":"IEEE Open J Comput Soc"},{"key":"11467_CR92","doi-asserted-by":"crossref","unstructured":"Lin H, Liu J, Qiu H, et\u00a0al (2024a) Framework for large-scale urban traffic state estimation based on AIGC. In: Proceedings of KES-STS international symposium, Springer, pp 81\u201390","DOI":"10.1007\/978-981-97-6748-9_8"},{"key":"11467_CR94","doi-asserted-by":"crossref","unstructured":"Lin Y, Gao Z, Du H, et\u00a0al (2024b) Blockchain-based efficient and trustworthy aigc services in metaverse. IEEE Trans Serv Comput","DOI":"10.1109\/TSC.2024.3382958"},{"key":"11467_CR95","doi-asserted-by":"crossref","unstructured":"Lin YK, Tu CY, Kurosawa L, et\u00a0al (2024c) Applications of computer vision in transportation systems: a systematic literature review. In: SHS Web of conferences, EDP sciences, p 01004","DOI":"10.1051\/shsconf\/202419401004"},{"key":"11467_CR96","unstructured":"Liu G, Van\u00a0Huynh N, Du H, et\u00a0al (2024a) Generative ai for unmanned vehicle swarms: challenges, applications and opportunities. arXiv preprint arXiv:2402.18062"},{"key":"11467_CR97","doi-asserted-by":"crossref","unstructured":"Liu Y, Cun X, Liu X, et\u00a0al (2024b) Evalcrafter: Benchmarking and evaluating large video generation models. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 22139\u201322149","DOI":"10.1109\/CVPR52733.2024.02090"},{"key":"11467_CR98","doi-asserted-by":"crossref","unstructured":"Liu Y, Du H, Niyato D, et\u00a0al (2024c) Prosecutor: Protecting mobile aigc services on two-layer blockchain via reputation and contract theoretic approaches. IEEE Trans Mob Comput","DOI":"10.1109\/TMC.2024.3390208"},{"key":"11467_CR99","volume":"599","author":"H Luo","year":"2024","unstructured":"Luo H, Luo J, Vasilakos AV (2024a) Bc4llm: A perspective of trusted artificial intelligence when blockchain meets large language models. Neurocomputing 599:128089","journal-title":"Neurocomputing"},{"key":"11467_CR100","doi-asserted-by":"crossref","unstructured":"Luo X, Wei Z, Zhang G, et\u00a0al (2024b) High-risk powered two-wheelers scenarios generation for autonomous vehicle testing using WGAN. Traffic Injury Prev, pp 1\u20139","DOI":"10.1080\/15389588.2024.2399305"},{"issue":"21","key":"11467_CR101","doi-asserted-by":"crossref","first-page":"3382","DOI":"10.3390\/math13213382","volume":"13","author":"X Luo","year":"2025","unstructured":"Luo X, Wang A, Zhang X et al (2025) Toward intelligent aiot: a comprehensive survey on digital twin and multimodal generative ai integration. Mathematics 13(21):3382","journal-title":"Mathematics"},{"issue":"5","key":"11467_CR102","first-page":"2","volume":"15","author":"Y Lv","year":"2023","unstructured":"Lv Y (2023) Artificial intelligence-generated content in intelligent transportation systems: learning to copy, change, and create![Editor\u2019s Column]. IEEE Intell Transp Syst Mag 15(5):2\u20133","journal-title":"IEEE Intell Transp Syst Mag"},{"key":"11467_CR103","unstructured":"MacVittie L (2024) Crucial concepts in AI: transparency and explainability. Accessed October. 18, 2025, https:\/\/www.f5.com\/company\/blog\/crucial-concepts-in-ai-transparency-and-explainability"},{"issue":"1","key":"11467_CR104","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1111\/mice.12561","volume":"36","author":"H Maeda","year":"2021","unstructured":"Maeda H, Kashiyama T, Sekimoto Y et al (2021) Generative adversarial network for road damage detection. Comput-Aided Civil Infrastruct Eng 36(1):47\u201360","journal-title":"Comput-Aided Civil Infrastruct Eng"},{"key":"11467_CR105","doi-asserted-by":"crossref","unstructured":"Maennel K, Maennel OM (2024) Human-AI collaboration and cyber security training: learning analytics opportunities and challenges. In: 2024 17th International conference on security of information and networks (SIN), IEEE, pp 01\u201308","DOI":"10.1109\/SIN63213.2024.10871610"},{"key":"11467_CR106","doi-asserted-by":"crossref","unstructured":"Mario S, Pothamsetti PT, Thalakottor LA, et\u00a0al (2024) Quantum annealing based hybrid strategies for real time route optimization. arXiv preprint arXiv:2412.02720","DOI":"10.2139\/ssrn.4970901"},{"issue":"9","key":"11467_CR107","doi-asserted-by":"crossref","first-page":"1581","DOI":"10.1587\/transinf.2021EDP7236","volume":"105","author":"K Matsumoto","year":"2022","unstructured":"Matsumoto K, Hara S, Abe M (2022) Speech-like emotional sound generation using wavenet. IEICE Trans Inf Syst 105(9):1581\u20131589","journal-title":"IEICE Trans Inf Syst"},{"key":"11467_CR108","doi-asserted-by":"crossref","unstructured":"Matsumoto K, Hyodo Y, Kurazume R (2024) Crowd-aware robot navigation with switching between learning-based and rule-based methods using normalizing flows. In: 2024 IEEE\/RSJ international conference on intelligent robots and systems (IROS), IEEE, pp 4823\u20134830","DOI":"10.1109\/IROS58592.2024.10802676"},{"key":"11467_CR109","unstructured":"Medium (2023) Magic training\u2014AIGC entering autonomous driving simulation by 51WORLD. https:\/\/51world.medium.com\/magic-training-aigc-entering-autonomous-driving-simulation-by-51world-691651c45268, accessed October 16, 2025"},{"key":"11467_CR110","doi-asserted-by":"crossref","unstructured":"Meftah LH, Cherif A, Braham R (2024) Improving autonomous vehicles maneuverability and collision avoidance in adverse weather conditions using generative adversarial networks. IEEE Access","DOI":"10.1109\/ACCESS.2024.3419029"},{"key":"11467_CR111","doi-asserted-by":"crossref","unstructured":"Meneguzzo S, Selabi EGK, Favenza A et al (2024) Enabling citizen sustainable behaviors in urban mobility through blockchain and tokenization. In: Blockchain technology in the automotive industry. CRC Press, pp 245\u2013279","DOI":"10.1201\/9781003450306-17"},{"key":"11467_CR112","unstructured":"Mishra S, Mishra M, Kim T, et\u00a0al (2023) Road redesign technique achieving enhanced road safety by inpainting with a diffusion model. arXiv preprint arXiv:2302.07440"},{"key":"11467_CR113","unstructured":"Mohamadi S, Mujtaba G, Le N, et\u00a0al (2023) Chatgpt in the age of generative AI and large language models: a concise survey. arXiv preprint arXiv:2307.04251"},{"key":"11467_CR114","doi-asserted-by":"crossref","unstructured":"M\u00f6ller DP (2023) Nist cybersecurity framework and mitre cybersecurity criteria. In: Guide to cybersecurity in digital transformation: trends. methods, technologies, applications and best practices. Springer, pp 231\u2013271","DOI":"10.1007\/978-3-031-26845-8_5"},{"key":"11467_CR115","unstructured":"Mossbridge J (2024) Shifting the human-AI relationship: toward a dynamic relational learning-partner model. arXiv preprint arXiv:2410.11864"},{"key":"11467_CR116","unstructured":"Multimodal (2024) 34 AI KPIs: the most comprehensive list of success metrics. Accessed October 21, 2025, https:\/\/www.multimodal.dev\/post\/ai-kpis"},{"key":"11467_CR117","doi-asserted-by":"crossref","unstructured":"Munoz A, Zolfaghari M, Argus M et al (2021) Temporal shift GAN for large scale video generation. In: Proceedings of the IEEE\/CVF winter conference on applications of computer vision, pp 3179\u20133188","DOI":"10.1109\/WACV48630.2021.00322"},{"key":"11467_CR118","doi-asserted-by":"crossref","unstructured":"Muriuki KP, Okello JO, Chepkoech J (2024) Advanced intelligent traffic management system (AITMS): a generative AI-enhanced model. In: 2024 IEEE PES\/IAS PowerAfrica, pp 1\u20133","DOI":"10.1109\/PowerAfrica61624.2024.10759478"},{"key":"11467_CR119","unstructured":"Muzahid AJM, Zhao X, Wang Z (2024) Survey on human-vehicle interactions and AI collaboration for optimal decision-making in automated driving. arXiv preprint arXiv:2412.08005"},{"key":"11467_CR120","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2023.102050","volume":"102","author":"SM Nagarajan","year":"2024","unstructured":"Nagarajan SM, Devarajan GG, Ramana T et al (2024) Adversarial deep learning based Dampster-Shafer data fusion model for intelligent transportation system. Inform Fusion 102:102050","journal-title":"Inform Fusion"},{"key":"11467_CR121","doi-asserted-by":"crossref","unstructured":"Naveen S, Kounte MR (2024) Optimized convolutional neural network at the IoT edge for image detection using pruning and quantization. Multimedia Tools Appl, pp 1\u201321","DOI":"10.1007\/s11042-024-20523-1"},{"key":"11467_CR122","doi-asserted-by":"crossref","unstructured":"Nesen A, Bhargava B (2021) Towards situational awareness with multimodal streaming data fusion: serverless computing approach. In: Proceedings of the international workshop on big data in emergent distributed environments, pp 1\u20136","DOI":"10.1145\/3460866.3461769"},{"key":"11467_CR123","unstructured":"Niedoba M, Lavington J, Liu Y et al (2024) A diffusion-model of joint interactive navigation"},{"issue":"6","key":"11467_CR124","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1109\/JPROC.2022.3173031","volume":"110","author":"M Noor-A-Rahim","year":"2022","unstructured":"Noor-A-Rahim M, Liu Z, Lee H et al (2022) 6g for vehicle-to-everything (v2x) communications: enabling technologies, challenges, and opportunities. Proc IEEE 110(6):712\u2013734","journal-title":"Proc IEEE"},{"key":"11467_CR125","unstructured":"NVIDIA (2023) Data augmentation and segmentation with generative networks for medical imaging. https:\/\/learn.nvidia.com\/courses\/course-detail?course_id=course-v1:DLI+L-HX-09+V1, accessed May 18, 2025"},{"key":"11467_CR126","unstructured":"NVIDIA (2025) Text-to-speech. Accessed May. 17, 2025, https:\/\/www.nvidia.com\/en-eu\/glossary\/text-to-speech\/"},{"key":"11467_CR127","unstructured":"NVIDIA Corporation (2021) NVIDIA DRIVE Sim. https:\/\/developer.nvidia.com\/drive\/simulation, accessed October 21, 2025"},{"key":"11467_CR128","doi-asserted-by":"crossref","unstructured":"Panda AK, Lenka AA, Mohapatra A, et\u00a0al (2025) Integrating cloud computing for intelligent transportation solutions in smart cities: a short review. Interdisciplinary approaches to transportation and urban planning, pp 121\u2013142","DOI":"10.4018\/979-8-3693-6695-0.ch005"},{"key":"11467_CR129","unstructured":"Papandreou T (2024) Generative AI is coming to the transportation industry\u2014is it ready? Forbes. Accessed October 10, 2025, https:\/\/www.forbes.com\/sites\/timothypapandreou\/2024\/03\/04\/generative-ai-is-coming-to-the-transportation-industry-is-it-ready\/"},{"key":"11467_CR130","doi-asserted-by":"crossref","unstructured":"Papineni K, Roukos S, Ward T et al (2002) Bleu: a method for automatic evaluation of machine translation. In: Proceedings of the 40th annual meeting of the association for computational linguistics, pp 311\u2013318","DOI":"10.3115\/1073083.1073135"},{"key":"11467_CR131","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.trf.2024.11.013","volume":"108","author":"MT Pascale","year":"2025","unstructured":"Pascale MT, Rodwell D, Bond A et al (2025) Examining longitudinal experiences with connected vehicle technology in Australia\u2019s largest c-its pilot. Transport Res F: Traffic Psychol Behav 108:89\u2013106","journal-title":"Transport Res F: Traffic Psychol Behav"},{"key":"11467_CR132","doi-asserted-by":"crossref","unstructured":"Patil D, Rane N, Rane J, et\u00a0al (2024) Artificial intelligence and generative AI, such as ChatGPT, in transportation: applications, technologies, challenges, and ethical considerations. Trustworthy artificial intelligence in industry and society, pp 185\u2013232","DOI":"10.70593\/978-81-981367-4-9_6"},{"issue":"2","key":"11467_CR133","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1007\/s13735-022-00227-8","volume":"11","author":"DR Patrikar","year":"2022","unstructured":"Patrikar DR, Parate MR (2022) Anomaly detection using edge computing in video surveillance system. Int J Multimed Inf Retr 11(2):85\u2013110","journal-title":"Int J Multimed Inf Retr"},{"issue":"1","key":"11467_CR134","first-page":"1","volume":"18","author":"H Pettinen","year":"2022","unstructured":"Pettinen H, H\u00e4stbacka D (2022) Service orchestration for object detection on edge and cloud in dependable industrial vehicles. J Mob Multimedia 18(1):1\u201326","journal-title":"J Mob Multimedia"},{"key":"11467_CR135","doi-asserted-by":"crossref","unstructured":"Pitale M, Abbaspour A, Upadhyay D (2024) Inherent diverse redundant safety mechanisms for AI-based software elements in automotive applications. arXiv preprint arXiv:2402.08208","DOI":"10.4271\/2024-01-2864"},{"key":"11467_CR136","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2024.121316","volume":"686","author":"J Qian","year":"2025","unstructured":"Qian J, Zheng M, Yu Y et al (2025) A dynamic anonymization privacy-preserving model based on hierarchical sequential three-way decisions. Inf Sci 686:121316","journal-title":"Inf Sci"},{"key":"11467_CR137","doi-asserted-by":"crossref","unstructured":"Qu X, Lin H, Liu Y (2023) Envisioning the future of transportation: Inspiration of ChatGPT and large models","DOI":"10.1016\/j.commtr.2023.100103"},{"key":"11467_CR138","doi-asserted-by":"crossref","unstructured":"Ramakrishna S, Luo B, Kuhn CB et al (2022) Anti-carla: An adversarial testing framework for autonomous vehicles in carla. In: 2022 IEEE 25th international conference on intelligent transportation systems (ITSC), IEEE, pp 2620\u20132627","DOI":"10.1109\/ITSC55140.2022.9921776"},{"issue":"11","key":"11467_CR139","doi-asserted-by":"crossref","first-page":"728","DOI":"10.3390\/info15110728","volume":"15","author":"IF Ramos","year":"2024","unstructured":"Ramos IF, Gianini G, Leva MC et al (2024) Collaborative intelligence for safety-critical industries: a literature review. Information 15(11):728","journal-title":"Information"},{"issue":"2","key":"11467_CR140","doi-asserted-by":"publisher","first-page":"826","DOI":"10.30574\/ijsra.2024.13.2.2208","volume":"13","author":"K Randhi","year":"2024","unstructured":"Randhi K, Bandarapu SR (2024) Efficient resource allocation for generative ai workloads in cloud-native infrastructures: a multi-tiered approach. Int J Sci Res Arch 13(2):826\u2013839. https:\/\/doi.org\/10.30574\/ijsra.2024.13.2.2208","journal-title":"Int J Sci Res Arch"},{"key":"11467_CR141","first-page":"136","volume":"4","author":"J Rane","year":"2024","unstructured":"Rane J, Mallick S, Kaya O et al (2024) Enhancing black-box models: advances in explainable artificial intelligence for ethical decision-making. Future Res Opport Artif Intell Ind 4:136\u2013180","journal-title":"Future Res Opport Artif Intell Ind"},{"issue":"1s","key":"11467_CR142","first-page":"77","volume":"10","author":"GS Rao","year":"2024","unstructured":"Rao GS, Naveen V, Kumar PA et al (2024) Accelerating text-to-speech conversion with fpt ai an end-to-end performance study. Macaw Int J Adv Res Comput Sci Eng 10(1s):77\u201385","journal-title":"Macaw Int J Adv Res Comput Sci Eng"},{"key":"11467_CR143","unstructured":"Rempe D, Litany (2023) Generating ai-based potential accident scenarios for autonomous vehicles. Accessed October. 16, 2025, https:\/\/developer.nvidia.com\/blog\/generating-ai-based-accident-scenarios-for-autonomous-vehicles\/"},{"issue":"1","key":"11467_CR144","first-page":"23","volume":"6","author":"X Ren","year":"2024","unstructured":"Ren X (2024) Application of artificial intelligence of generative content (AIGC) in the field of urban intelligent traffic management. SCIREA J Traffic Transp 6(1):23\u201342","journal-title":"SCIREA J Traffic Transp"},{"key":"11467_CR145","doi-asserted-by":"crossref","unstructured":"Rezaei S, Masoud N, Khojandi A (2024) GAAD: GAN-enabled autoencoder for real-time sensor anomaly detection and recovery in autonomous driving. IEEE Sens J","DOI":"10.1109\/JSEN.2024.3361460"},{"key":"11467_CR146","doi-asserted-by":"crossref","unstructured":"Rodrigues J, Branco A (2024) Meta-prompting optimized retrieval-augmented generation. In: EPIA conference on artificial intelligence, pp 203\u2013214","DOI":"10.1007\/978-3-031-73503-5_17"},{"key":"11467_CR147","doi-asserted-by":"crossref","unstructured":"Rong R, Ma S, Ren N, et\u00a0al (2025) Generative artificial intelligence in intelligent transportation systems: a systematic review of applications. Front Eng Manag, pp 1\u201317","DOI":"10.1007\/s42524-025-4241-9"},{"key":"11467_CR148","doi-asserted-by":"crossref","unstructured":"Rousseau T, Amokrane K, Meddeb M, et\u00a0al (2024) Cooperation between a human traffic manager and an AI assistant for an improved railway infrastructure resilience. In: Transport research arena (TRA2024)","DOI":"10.1007\/978-3-032-04774-8_36"},{"key":"11467_CR149","unstructured":"Ruan BK, Tsui HT, Li YH, et\u00a0al (2024) Traffic scene generation from natural language description for autonomous vehicles with large language model. arXiv preprint arXiv:2409.09575"},{"key":"11467_CR150","unstructured":"Sahoo P, Meharia P, Ghosh A, et\u00a0al (2024) Unveiling hallucination in text, image, video, and audio foundation models: a comprehensive survey. arXiv preprint arXiv:2405.09589"},{"key":"11467_CR151","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez-Naval\u00f3n H, Monserrat C, Garigliotti D et al (2024) Evaluating performance and trustworthiness of rag systems for generating administrative text. In: International conference on intelligent data engineering and automated learning, pp 410\u2013421","DOI":"10.1007\/978-3-031-77731-8_37"},{"key":"11467_CR152","doi-asserted-by":"crossref","DOI":"10.1016\/j.iot.2022.100528","volume":"19","author":"IH Sarker","year":"2022","unstructured":"Sarker IH (2022) Smart city data science: towards data-driven smart cities with open research issues. Internet Things 19:100528","journal-title":"Internet Things"},{"key":"11467_CR153","doi-asserted-by":"crossref","unstructured":"Sarwatt DS, Kulwa F, Ding J, et\u00a0al (2024a) Adapting image classification adversarial detection methods for traffic sign classification in autonomous vehicles: a comparative study. IEEE Trans Intell Transp Syst","DOI":"10.36227\/techrxiv.174123711.16301456\/v1"},{"key":"11467_CR154","doi-asserted-by":"crossref","unstructured":"Sarwatt DS, Lin Y, Ding J et al (2024b) Metaverse for intelligent transportation systems (ITS): a comprehensive review of technologies, applications, implications. challenges and future directions. IEEE Trans Intell Transp Syst","DOI":"10.1109\/TITS.2023.3347280"},{"key":"11467_CR155","doi-asserted-by":"crossref","unstructured":"Satpathy I, Nayak A, Khang A (2025) Transformative impact of generative artificial intelligence (Gen AI) on smart transportation system. In: Driving green transportation system through artificial intelligence and automation: approaches, technologies and applications. Springer, pp 563\u2013579","DOI":"10.1007\/978-3-031-72617-0_29"},{"key":"11467_CR156","doi-asserted-by":"crossref","DOI":"10.1016\/j.techfore.2024.123417","volume":"204","author":"K Saurabh","year":"2024","unstructured":"Saurabh K, Rani N, Upadhyay P (2024) Towards novel blockchain decentralised autonomous organisation (DAO) led corporate governance framework. Technol Forecast Soc Chang 204:123417","journal-title":"Technol Forecast Soc Chang"},{"issue":"1","key":"11467_CR157","doi-asserted-by":"crossref","first-page":"1672","DOI":"10.3934\/mbe.2024073","volume":"21","author":"L Shao","year":"2024","unstructured":"Shao L, Chen B, Zhang Z et al (2024) Artificial intelligence generated content (AIGC) in medicine: a narrative review. Math Biosci Eng 21(1):1672\u20131711","journal-title":"Math Biosci Eng"},{"key":"11467_CR158","unstructured":"Shi J, Jain R, Doh H, et\u00a0al (2023) An hci-centric survey and taxonomy of human-generative-ai interactions. arXiv preprint arXiv:2310.07127"},{"key":"11467_CR159","doi-asserted-by":"crossref","unstructured":"Shin H, Chung H, Park C, et\u00a0al (2024) Enhancing the multi-user experience in fully autonomous vehicles through explainable AI voice agents. Int J Human\u2013Comput Interact, pp 1\u201315","DOI":"10.1080\/10447318.2024.2383034"},{"key":"11467_CR160","doi-asserted-by":"crossref","unstructured":"Shrimal H (2024) Integration of AI-powered vehicles with smart city infrastructure to transform the future of automotive world. Tech. rep, SAE Technical Paper","DOI":"10.4271\/2024-28-0028"},{"key":"11467_CR161","unstructured":"Smyth OS (2025) Explainable ai in autonomous vehicles: building transparency and trust on the road. Accessed October. 19, 2025, https:\/\/smythos.com\/ai-industry-solutions\/automotive\/explainable-ai-in-autonomous-vehicles\/"},{"issue":"3","key":"11467_CR162","doi-asserted-by":"crossref","first-page":"1","DOI":"10.56397\/JPEPS.2024.09.01","volume":"3","author":"W Song","year":"2024","unstructured":"Song W (2024) Data analysis and congestion prediction model in intelligent transportation systems. J Prog Eng Phys Sci 3(3):1\u20138","journal-title":"J Prog Eng Phys Sci"},{"key":"11467_CR163","doi-asserted-by":"crossref","unstructured":"Sperrle F, El-Assady M, Guo G, et\u00a0al (2021) A survey of human-centered evaluations in human-centered machine learning. In: Computer graphics forum, Wiley Online Library, pp 543\u2013568","DOI":"10.1111\/cgf.14329"},{"key":"11467_CR164","doi-asserted-by":"crossref","unstructured":"Sznajder B, Fadnis K, Danilevsky M et al (2025) Inspectorraget: An introspection platform for rag evaluation. In: Annual conference of the north American chapter of the association for computational linguistics","DOI":"10.18653\/v1\/2025.naacl-demo.13"},{"issue":"20","key":"11467_CR165","doi-asserted-by":"crossref","first-page":"9269","DOI":"10.3390\/app14209269","volume":"14","author":"D Tamayo-Urgil\u00e9s","year":"2024","unstructured":"Tamayo-Urgil\u00e9s D, Sanchez-Gordon S, Valdivieso Caraguay \u00c1L et al (2024) GAN-based generation of synthetic data for vehicle driving events. Appl Sci 14(20):9269","journal-title":"Appl Sci"},{"issue":"9","key":"11467_CR166","doi-asserted-by":"crossref","first-page":"13954","DOI":"10.1109\/TITS.2021.3127217","volume":"23","author":"Z Tan","year":"2021","unstructured":"Tan Z, Dai N, Su Y et al (2021) Human-machine interaction in intelligent and connected vehicles: a review of status quo, issues, and opportunities. IEEE Trans Intell Transp Syst 23(9):13954\u201313975","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"11467_CR167","doi-asserted-by":"crossref","unstructured":"Teef D, Muhammad K, Nassisid K, et\u00a0al (2024) Enhancing vehicular networks with generative AI: opportunities and challenges. Authorea Preprints","DOI":"10.36227\/techrxiv.172101192.26104590\/v1"},{"key":"11467_CR168","doi-asserted-by":"crossref","unstructured":"Teo ZL, Ning CQW, Wong JLY, et\u00a0al (2024) Cybersecurity in the generative artificial intelligence era. Asia-Pacific J Ophthalmol, p 100091","DOI":"10.1016\/j.apjo.2024.100091"},{"key":"11467_CR169","doi-asserted-by":"crossref","unstructured":"Ton-Thien MA, Nguyen CT, Le QM et al (2023) Air pollution forecasting using multimodal data. In: International conference on industrial, engineering and other applications of applied intelligent systems. Springer, pp 360\u2013371","DOI":"10.1007\/978-3-031-36822-6_31"},{"key":"11467_CR170","doi-asserted-by":"crossref","first-page":"2733","DOI":"10.1109\/OJCOMS.2023.3324952","volume":"4","author":"SE Trevlakis","year":"2023","unstructured":"Trevlakis SE, Boulogeorgos AAA, Pliatsios D et al (2023) Localization as a key enabler of 6g wireless systems: a comprehensive survey and an outlook. IEEE Open J Commun Soc 4:2733\u20132801","journal-title":"IEEE Open J Commun Soc"},{"key":"11467_CR171","doi-asserted-by":"crossref","unstructured":"Tulyakov S, Liu MY, Yang X et al (2018) Mocogan: Decomposing motion and content for video generation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1526\u20131535","DOI":"10.1109\/CVPR.2018.00165"},{"key":"11467_CR172","doi-asserted-by":"crossref","unstructured":"Tyburzy L, Jameel M, Hunger R et al (2024) Empowering human-AI collaboration in air traffic control through smart interaction design. In: 2024 AIAA DATC\/IEEE 43rd digital avionics systems conference (DASC), IEEE, pp 1\u20139","DOI":"10.1109\/DASC62030.2024.10749379"},{"key":"11467_CR173","doi-asserted-by":"crossref","unstructured":"Veretennikov S, Minartz K, Menkovski V, et\u00a0al (2022) Simulation of scientific experiments with generative models. In: International symposium on intelligent data analysis, Springer, pp 341\u2013353","DOI":"10.1007\/978-3-031-01333-1_27"},{"key":"11467_CR174","doi-asserted-by":"crossref","unstructured":"Voigt P, Von dem Bussche A (2017) The eu general data protection regulation (gdpr). A practical guide, vol 10, 1st edn. Springer, Cham, pp 10\u20135555","DOI":"10.1007\/978-3-319-57959-7_1"},{"key":"11467_CR175","doi-asserted-by":"crossref","first-page":"1248426","DOI":"10.3389\/fevo.2023.1248426","volume":"11","author":"Q Wan","year":"2023","unstructured":"Wan Q, Liu J (2023) Energy efficiency optimization and carbon emission reduction targets of resource-based cities based on BiLSTM-CNN-GAN model. Front Ecol Evol 11:1248426","journal-title":"Front Ecol Evol"},{"issue":"9","key":"11467_CR178","doi-asserted-by":"crossref","first-page":"1196","DOI":"10.3390\/sym16091196","volume":"16","author":"J Wang","year":"2024","unstructured":"Wang J (2024) Hallucination reduction and optimization for large language model-based autonomous driving. Symmetry 16(9):1196","journal-title":"Symmetry"},{"key":"11467_CR184","doi-asserted-by":"crossref","unstructured":"Wang X, Wu YC (2024) Balancing innovation and regulation in the age of generative artificial intelligence. J Inform Policy, 14","DOI":"10.5325\/jinfopoli.14.2024.0012"},{"issue":"4","key":"11467_CR187","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang Z, Bovik AC, Sheikh HR et al (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600\u2013612","journal-title":"IEEE Trans Image Process"},{"issue":"9","key":"11467_CR179","doi-asserted-by":"crossref","first-page":"9840","DOI":"10.1109\/TVT.2022.3176653","volume":"71","author":"P Wang","year":"2022","unstructured":"Wang P, Zhu C, Wang X et al (2022a) Inferring intersection traffic patterns with sparse video surveillance information: an ST-GAN method. IEEE Trans Veh Technol 71(9):9840\u20139852","journal-title":"IEEE Trans Veh Technol"},{"key":"11467_CR180","doi-asserted-by":"crossref","unstructured":"Wang R, He F, Gan B (2022b) Anti-collision warning algorithm of vehicle intersection based on V2X. In: Proceedings of the 7th international conference on cyber security and information engineering, pp 24\u201329","DOI":"10.1145\/3558819.3558824"},{"key":"11467_CR182","doi-asserted-by":"crossref","unstructured":"Wang T, Huang P, Dong G, et\u00a0al (2023a) A diffusion-based reactive approach to road network cooperative persistent surveillance. IEEE Trans Intell Transp Syst","DOI":"10.1109\/TITS.2023.3329001"},{"key":"11467_CR185","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1109\/OJCS.2023.3300321","volume":"4","author":"Y Wang","year":"2023","unstructured":"Wang Y, Pan Y, Yan M et al (2023b) A survey on chatgpt: Ai-generated contents, challenges, and solutions. IEEE Open J Comput 4:280\u2013302","journal-title":"IEEE Open J Comput"},{"key":"11467_CR186","doi-asserted-by":"crossref","first-page":"2952","DOI":"10.1109\/OJCOMS.2023.3320646","volume":"4","author":"YC Wang","year":"2023","unstructured":"Wang YC, Xue J, Wei C et al (2023c) An overview on generative ai at scale with edge-cloud computing. IEEE Open J Commun Soc 4:2952\u20132971","journal-title":"IEEE Open J Commun Soc"},{"key":"11467_CR176","unstructured":"Wang D, McFarland J, Mashhadi A, et\u00a0al (2024a) Comparing fairness of generative mobility models. arXiv preprint arXiv:2411.04453"},{"key":"11467_CR177","doi-asserted-by":"crossref","unstructured":"Wang H, Jiao L, Zhao T, et\u00a0al (2024b) A cloud-edge intelligent collaborative framework and its applications in aigc and digital twins. In: IECON 2024-50th annual conference of the IEEE industrial electronics society, IEEE, pp 1\u20134","DOI":"10.1109\/IECON55916.2024.10905560"},{"issue":"2","key":"11467_CR181","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1007\/s11554-023-01400-w","volume":"21","author":"S Wang","year":"2024","unstructured":"Wang S, Deng Y, Hu L et al (2024c) Edge-computing-assisted intelligent processing of ai-generated image content. J Real-Time Image Proc 21(2):39","journal-title":"J Real-Time Image Proc"},{"issue":"4","key":"11467_CR183","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3703626","volume":"57","author":"T Wang","year":"2024","unstructured":"Wang T, Zhang Y, Qi S et al (2024d) Security and privacy on generative data in AIGC: a survey. ACM Comput Surv 57(4):1\u201334","journal-title":"ACM Comput Surv"},{"key":"11467_CR189","doi-asserted-by":"crossref","unstructured":"Wei W, Ke Q, Zielonka A, et\u00a0al (2023) Vehicle parking navigation based on edge computing with diffusion model and information potential field. IEEE Trans Serv Comput","DOI":"10.1109\/TSC.2023.3286332"},{"key":"11467_CR188","doi-asserted-by":"crossref","unstructured":"Wei C, Wu G, Barth MJ et al (2024) KI-GAN: knowledge-informed generative adversarial networks for enhanced multi-vehicle trajectory forecasting at signalized intersections. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 7115\u20137124","DOI":"10.1109\/CVPRW63382.2024.00706"},{"key":"11467_CR190","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.jhtm.2023.06.022","volume":"56","author":"IA Wong","year":"2023","unstructured":"Wong IA, Lian QL, Sun D (2023) Autonomous travel decision-making: an early glimpse into chatgpt and generative ai. J Hosp Tour Manag 56:253\u2013263","journal-title":"J Hosp Tour Manag"},{"key":"11467_CR192","unstructured":"Wu S, Irsoy O, Lu S et al (2023a) Bloomberggpt: a large language model for finance. arXiv preprint arXiv:2303.17564"},{"key":"11467_CR193","volume":"55","author":"Y Wu","year":"2023","unstructured":"Wu Y, Ma L, Yuan X et al (2023b) Human-machine hybrid intelligence for the generation of car frontal forms. Adv Eng Inform 55:101906","journal-title":"Adv Eng Inform"},{"key":"11467_CR191","doi-asserted-by":"crossref","unstructured":"Wu K, Li W, Xiao X (2024) Accidentgpt: Large multi-modal foundation model for traffic accident analysis. arXiv preprint arXiv:2401.03040","DOI":"10.5220\/0012422100003636"},{"key":"11467_CR194","unstructured":"Xiao W, Wang TH, Gan C et al (2023) Safediffuser: Safe planning with diffusion probabilistic models. In: The thirteenth international conference on learning representations"},{"key":"11467_CR196","doi-asserted-by":"crossref","unstructured":"Xie X, Zhao J, Chen C et al (2021) Af-tcp: Traffic congestion prediction at arbitrary road segment and flexible future time. In: International conference on algorithms and architectures for parallel processing, pp 167\u2013181","DOI":"10.1007\/978-3-030-95391-1_11"},{"key":"11467_CR195","doi-asserted-by":"crossref","unstructured":"Xie G, Xie R, Zhang X et al (2024) Giov: Achieving generative ai services in internet of vehicles via collaborative edge intelligence. In: 2024 IEEE wireless communications and networking conference (WCNC), IEEE, pp 1\u20136","DOI":"10.1109\/WCNC57260.2024.10571334"},{"issue":"2","key":"11467_CR197","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3696415","volume":"57","author":"Z Xing","year":"2024","unstructured":"Xing Z, Feng Q, Chen H et al (2024) A survey on video diffusion models. ACM Comput Surv 57(2):1\u201342","journal-title":"ACM Comput Surv"},{"key":"11467_CR203","unstructured":"Xu M, Niyato D, Zhang H, et\u00a0al (2023a) Sparks of gpts in edge intelligence for metaverse: caching and inference for mobile aigc services. arXiv preprint arXiv:2304.08782"},{"key":"11467_CR206","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.actaastro.2023.02.009","volume":"205","author":"Z Xu","year":"2023","unstructured":"Xu Z, Cheng Z, Guo B (2023b) A hybrid data-driven framework for satellite telemetry data anomaly detection. Acta Astronaut 205:281\u2013294","journal-title":"Acta Astronaut"},{"key":"11467_CR198","doi-asserted-by":"crossref","unstructured":"Xu C, Guo J, Zeng J, et\u00a0al (2024a) Enhancing AI-generated content efficiency through adaptive multi-edge collaboration. In: 2024 IEEE 44th international conference on distributed computing systems (ICDCS), IEEE, pp 960\u2013970","DOI":"10.1109\/ICDCS60910.2024.00093"},{"issue":"1","key":"11467_CR200","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1007\/s44212-024-00060-w","volume":"3","author":"H Xu","year":"2024","unstructured":"Xu H, Omitaomu F, Sabri S et al (2024b) Leveraging generative ai for urban digital twins: a scoping review on the autonomous generation of urban data, scenarios, designs, and 3d city models for smart city advancement. Urban Inform 3(1):29","journal-title":"Urban Inform"},{"key":"11467_CR201","unstructured":"Xu H, Yuan J, Zhou A, et\u00a0al (2024c) GenAI-powered multi-agent paradigm for smart urban mobility: opportunities and challenges for integrating large language models (LLMS) and retrieval-augmented generation (rag) with intelligent transportation systems. arXiv preprint arXiv:2409.00494"},{"issue":"2","key":"11467_CR204","doi-asserted-by":"crossref","first-page":"1127","DOI":"10.1109\/COMST.2024.3353265","volume":"26","author":"M Xu","year":"2024","unstructured":"Xu M, Du H, Niyato D et al (2024d) Unleashing the power of edge-cloud generative ai in mobile networks: a survey of aigc services. IEEE Commun Surv Tutor 26(2):1127\u20131170","journal-title":"IEEE Commun Surv Tutor"},{"key":"11467_CR205","doi-asserted-by":"crossref","unstructured":"Xu X, Xu T, Ma F, et\u00a0al (2024e) From bird\u2019s-eye to street view: crafting diverse and condition-aligned images with latent diffusion model. In: 2024 IEEE international conference on robotics and automation (ICRA), IEEE, pp 16795\u201316802","DOI":"10.1109\/ICRA57147.2024.10611235"},{"key":"11467_CR207","doi-asserted-by":"crossref","unstructured":"Xu Z, Zhang Y, Xie E, et\u00a0al (2024f) Drivegpt4: Interpretable end-to-end autonomous driving via large language model. IEEE Robot Automat Lett","DOI":"10.1109\/LRA.2024.3440097"},{"key":"11467_CR199","doi-asserted-by":"crossref","unstructured":"Xu C, Petiushko A, Zhao D, et\u00a0al (2025a) Diffscene: Diffusion-based safety-critical scenario generation for autonomous vehicles. In: Proceedings of the AAAI conference on artificial intelligence, pp 8797\u20138805","DOI":"10.1609\/aaai.v39i8.32951"},{"key":"11467_CR202","unstructured":"Xu J, Zhang Q, Zhong Z, et\u00a0al (2025b) Openrca: Can large language models locate the root cause of software failures? In: The thirteenth international conference on learning representations"},{"key":"11467_CR208","doi-asserted-by":"crossref","unstructured":"Xu Z, Chen T, Huang Z, et\u00a0al (2025c) Personalizing driver agent using large language models for driving safety and smarter Human-Machine interactions. IEEE Intell Transp Syst Mag","DOI":"10.1109\/MITS.2025.3551736"},{"key":"11467_CR209","doi-asserted-by":"crossref","unstructured":"Xue Z, Hu R, Huang C, et\u00a0al (2024) Video anomaly detection via motion completion diffusion for intelligent surveillance system. IEEE Sens J","DOI":"10.1109\/JSEN.2024.3453437"},{"key":"11467_CR210","unstructured":"Yan H, Li Y (2023) A survey of generative AI for intelligent transportation systems. arXiv preprint arXiv:2312.08248"},{"key":"11467_CR213","doi-asserted-by":"crossref","unstructured":"Yang L (2024) Image-text multimodal translation based on AIGC human-machine interaction. In: Proceedings of the 2024 4th international conference on human-machine interaction, pp 44\u201351","DOI":"10.1145\/3678429.3678436"},{"key":"11467_CR211","doi-asserted-by":"crossref","unstructured":"Yang F, Abedin MZ, Qiao Y, et\u00a0al (2024a) Towards trustworthy governance of AI-generated content (AIGC): a blockchain-driven regulatory framework for secure digital ecosystems. IEEE Trans Eng Manag","DOI":"10.1109\/TEM.2024.3472292"},{"key":"11467_CR212","doi-asserted-by":"crossref","unstructured":"Yang H, Siew M, Joe-Wong C (2024b) An llm-based digital twin for optimizing human-in-the loop systems. In: 2024 IEEE international workshop on foundation models for cyber-physical systems & internet of things (FMSys), IEEE, pp 26\u201331","DOI":"10.1109\/FMSys62467.2024.00009"},{"key":"11467_CR214","doi-asserted-by":"crossref","unstructured":"Ye D, Cai S, Du H, et\u00a0al (2024) Optimizing aigc services by prompt engineering and edge computing: a generative diffusion model-based contract theory approach. IEEE Trans Vehic Technol","DOI":"10.1109\/TVT.2024.3463420"},{"key":"11467_CR215","doi-asserted-by":"crossref","unstructured":"Yenduri G, Ramalingam M, Selvi GC, et\u00a0al (2024) Gpt (generative pre-trained transformer)\u2013a comprehensive review on enabling technologies, potential applications, emerging challenges, and future directions. IEEE Access","DOI":"10.1109\/ACCESS.2024.3389497"},{"issue":"2","key":"11467_CR216","doi-asserted-by":"crossref","first-page":"664","DOI":"10.3390\/app14020664","volume":"14","author":"B Yoo","year":"2024","unstructured":"Yoo B, Kim J, Park S et al (2024) Harnessing generative pre-trained transformers for construction accident prediction with saliency visualization. Appl Sci 14(2):664","journal-title":"Appl Sci"},{"key":"11467_CR217","unstructured":"Youtube (2024) Introducing INRIX Compass$$^{TM}$$. Accessed October. 13, 2025, https:\/\/www.youtube.com\/watch?v=Rwrc0QPs2ic"},{"key":"11467_CR218","doi-asserted-by":"publisher","unstructured":"Yu Q, Xu Z, Zhou Y, et\u00a0al (2024) Spatiotemporal variational autoencoder for intersection pedestrian trajectory prediction. Preprint, Research Squarhttps:\/\/doi.org\/10.21203\/rs.3.rs-4151226\/v1, accessed October 21, 2025","DOI":"10.21203\/rs.3.rs-4151226\/v1"},{"key":"11467_CR219","doi-asserted-by":"crossref","unstructured":"Yulianto S, Gaol FL, Supangkat SH et al (2023) A comprehensive model for enhancing cybersecurity resilience and it governance through red teaming exercises. In: 2023 29th International conference on telecommunications (ICT), IEEE, pp 1\u20137","DOI":"10.1109\/ICT60153.2023.10374068"},{"key":"11467_CR220","doi-asserted-by":"crossref","unstructured":"Zeng W, Zheng J, Wang H et al (2024) Delay-aware parallel offloading aigc service in edge computing. In: 2024 IEEE\/CIC international conference on communications in China (ICCC Workshops), IEEE, pp 208\u2013213","DOI":"10.1109\/ICCCWorkshops62562.2024.10693717"},{"key":"11467_CR223","doi-asserted-by":"crossref","unstructured":"Zhang L (2025) Smart city multilingual exhibition navigation with graph neural networks and cross-lingual knowledge graphs. In: Second international conference on intelligent transportation and smart cities (ICITSC 2025), SPIE, pp 479\u2013487","DOI":"10.1117\/12.3073469"},{"key":"11467_CR225","doi-asserted-by":"crossref","unstructured":"Zhang S, Li J, Shi L et al (2023) Federated learning in intelligent transportation systems: recent applications and open problems. IEEE Trans Intell Transp Syst","DOI":"10.1109\/TITS.2023.3324962"},{"key":"11467_CR221","doi-asserted-by":"crossref","unstructured":"Zhang C, Zhang Y, Shao Q, et\u00a0al (2024a) ChatTraffic: Text-to-traffic generation via diffusion model. IEEE Trans Intell Transp Syst","DOI":"10.1109\/TITS.2024.3510402"},{"issue":"4","key":"11467_CR222","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1109\/MWC.004.2300572","volume":"31","author":"J Zhang","year":"2024","unstructured":"Zhang J, Wei Z, Liu B et al (2024b) Cloud-edge-terminal collaborative AIGC for autonomous driving. IEEE Wirel Commun 31(4):40\u201347","journal-title":"IEEE Wirel Commun"},{"key":"11467_CR224","doi-asserted-by":"crossref","unstructured":"Zhang R, Xiong K, Du H, et\u00a0al (2024c) Generative AI-enabled vehicular networks: fundamentals, framework, and case study. IEEE Netw","DOI":"10.1109\/MNET.2024.3391767"},{"key":"11467_CR226","doi-asserted-by":"crossref","unstructured":"Zhang X, Li S, Tang J, et\u00a0al (2024d) Drl-enabled computation offloading for aigc services in ioit-assisted edge computing networks. IEEE Internet Things J","DOI":"10.1109\/JIOT.2024.3523919"},{"key":"11467_CR227","unstructured":"Zhang Z, Li X, Sun W, et\u00a0al (2024e) Benchmarking aigc video quality assessment: a dataset and unified model. arXiv preprint arXiv:2407.21408"},{"key":"11467_CR228","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.future.2024.03.009","volume":"157","author":"Z Zhang","year":"2024","unstructured":"Zhang Z, Zhang Y, Bao W et al (2024f) Coarse-to-fine: a hierarchical dnn inference framework for edge computing. Future Gener Comput Syst 157:180\u2013192","journal-title":"Future Gener Comput Syst"},{"key":"11467_CR230","doi-asserted-by":"crossref","unstructured":"Zhao Y, Wang X, Juvela L et al (2020) Transferring neural speech waveform synthesizers to musical instrument sounds generation. ICASSP 2020\u20132020 IEEE international conference on acoustics. IEEE, speech and signal processing (ICASSP), pp 6269\u20136273","DOI":"10.1109\/ICASSP40776.2020.9053047"},{"key":"11467_CR229","doi-asserted-by":"crossref","unstructured":"Zhao H, Wang J, Zhang T et al (2024) A prediction method for atmospheric monitoring data based on transformer and GAN. In: 2024 IEEE 7th information technology, networking, electronic and automation control conference (ITNEC), IEEE, pp 1472\u20131477","DOI":"10.1109\/ITNEC60942.2024.10733223"},{"key":"11467_CR231","doi-asserted-by":"crossref","unstructured":"Zhong Z, Rempe D, Xu D et al (2023) Guided conditional diffusion for controllable traffic simulation. In: 2023 IEEE international conference on robotics and automation (ICRA), IEEE, pp 3560\u20133566","DOI":"10.1109\/ICRA48891.2023.10161463"},{"key":"11467_CR236","doi-asserted-by":"crossref","unstructured":"Zhou W, Wang C, Ge Y, et\u00a0al (2023) All-day vehicle detection from surveillance videos based on illumination-adjustable generative adversarial network. IEEE Trans Intell Transp Syst","DOI":"10.1109\/TITS.2023.3328195"},{"key":"11467_CR232","doi-asserted-by":"crossref","unstructured":"Zhou CH, Ku HC, Chen YA, et\u00a0al (2024a) Using large language model and speech synthesis technology to achieve realistic interactive experiences in smart city applications. In: 2024 International conference on consumer electronics-Taiwan (ICCE-Taiwan), IEEE, pp 811\u2013812","DOI":"10.1109\/ICCE-Taiwan62264.2024.10674564"},{"issue":"4","key":"11467_CR233","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1109\/MWC.2024.10628029","volume":"31","author":"H Zhou","year":"2024","unstructured":"Zhou H, Dai HN, Cheng X et al (2024b) Guest editorial: mobile AI-generated content (AIGC) in 6G era. IEEE Wirel Commun 31(4):12\u201313","journal-title":"IEEE Wirel Commun"},{"key":"11467_CR234","doi-asserted-by":"crossref","unstructured":"Zhou J, Yi J, Wang T, et\u00a0al (2024c) Traceablespeech: Towards proactively traceable text-to-speech with watermarking. arXiv preprint arXiv:2406.04840","DOI":"10.21437\/Interspeech.2024-534"},{"key":"11467_CR235","doi-asserted-by":"crossref","unstructured":"Zhou M, Yu S, Zhou C, et\u00a0al (2025) Navigating the future: a longitudinal exploration of public acceptance of autonomous taxis from initial trials to stepwise habituation. Comput Human Behav, p 108678","DOI":"10.1016\/j.chb.2025.108678"},{"issue":"46","key":"11467_CR237","doi-asserted-by":"crossref","first-page":"17667","DOI":"10.1021\/acs.est.3c01818","volume":"57","author":"JJ Zhu","year":"2023","unstructured":"Zhu JJ, Jiang J, Yang M et al (2023) ChatGPT and environmental research. Environ Sci Technol 57(46):17667\u201317670","journal-title":"Environ Sci Technol"},{"issue":"1","key":"11467_CR239","doi-asserted-by":"crossref","first-page":"2358211","DOI":"10.1080\/21680566.2024.2358211","volume":"12","author":"W Zhu","year":"2024","unstructured":"Zhu W, L\u00fc C, Chen X (2024) A crash occurrence risk prediction model based on variational autoencoder and generative adversarial network. Transportmetrica B Transport Dyn 12(1):2358211","journal-title":"Transportmetrica B Transport Dyn"},{"key":"11467_CR238","doi-asserted-by":"crossref","unstructured":"Zhu L, Ye Z, Wang H, et\u00a0al (2025) Iot-enhanced generative al for dynamic train control in virtually coupled train set systems. IEEE Internet Things J","DOI":"10.1109\/JIOT.2025.3546016"},{"key":"11467_CR240","doi-asserted-by":"crossref","first-page":"1499165","DOI":"10.3389\/fcomp.2024.1499165","volume":"6","author":"Z Zou","year":"2025","unstructured":"Zou Z, Khan A, Lwin M et al (2025) Investigating the impacts of auditory and visual feedback in advanced driver assistance systems: a pilot study on driver behavior and emotional response. Front Comput Sci 6:1499165","journal-title":"Front Comput Sci"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10462-025-11467-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-025-11467-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-025-11467-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T05:46:07Z","timestamp":1771479967000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10462-025-11467-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,5]]},"references-count":240,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["11467"],"URL":"https:\/\/doi.org\/10.1007\/s10462-025-11467-5","relation":{},"ISSN":["1573-7462"],"issn-type":[{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,5]]},"assertion":[{"value":"27 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"75"}}