{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T13:20:31Z","timestamp":1777382431345,"version":"3.51.4"},"reference-count":68,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T00:00:00Z","timestamp":1774310400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100017170","name":"Thailand Science Research and Innovation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100017170","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Array"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.array.2026.100784","type":"journal-article","created":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T15:23:37Z","timestamp":1775316217000},"page":"100784","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Enhancing autonomous vehicle resilience: Roadside sensor networks for robust perception and decision-making in challenging environments"],"prefix":"10.1016","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5873-6254","authenticated-orcid":false,"given":"Badri Raj","family":"Lamichhane","sequence":"first","affiliation":[]},{"given":"Aueaphum","family":"Aueawatthanaphisut","sequence":"additional","affiliation":[]},{"given":"Gun","family":"Srijuntongsiri","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3452-8845","authenticated-orcid":false,"given":"Teerayut","family":"Horanont","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.array.2026.100784_b1","doi-asserted-by":"crossref","first-page":"736","DOI":"10.1016\/j.procs.2021.12.315","article-title":"An overview of sensors in autonomous vehicles","volume":"198","author":"Ignatious","year":"2022","journal-title":"Procedia Comput Sci"},{"key":"10.1016\/j.array.2026.100784_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.cose.2020.102150","article-title":"Cybersecurity for autonomous vehicles: Review of attacks and defense","volume":"103","author":"Kim","year":"2021","journal-title":"Comput Secur"},{"key":"10.1016\/j.array.2026.100784_b3","doi-asserted-by":"crossref","first-page":"42334","DOI":"10.1109\/ACCESS.2022.3168320","article-title":"Future trends in connected and autonomous vehicles: Enabling communications and processing technologies","volume":"10","author":"Damaj","year":"2022","journal-title":"IEEE Access"},{"issue":"2","key":"10.1016\/j.array.2026.100784_b4","doi-asserted-by":"crossref","DOI":"10.1002\/aisy.202100122","article-title":"Intelligent in-vehicle interaction technologies","volume":"4","author":"Murali","year":"2022","journal-title":"Adv Intell Syst"},{"key":"10.1016\/j.array.2026.100784_b5","first-page":"75","article-title":"A survey on architecture of autonomous vehicles","author":"Ramyavarshini","year":"2024","journal-title":"Artif Intell Auton Veh"},{"issue":"5","key":"10.1016\/j.array.2026.100784_b6","doi-asserted-by":"crossref","first-page":"117","DOI":"10.3390\/technologies11050117","article-title":"Connected and automated vehicles: Infrastructure, applications, security, critical challenges, and future aspects","volume":"11","author":"Sadaf","year":"2023","journal-title":"Technologies"},{"key":"10.1016\/j.array.2026.100784_b7","series-title":"2024 IEEE international conference on advanced systems and emergent technologies","first-page":"1","article-title":"Evaluation and optimization of adaptive cruise control in autonomous vehicles using the CARLA simulator: A study on performance under wet and dry weather conditions","author":"Al-Hindawi","year":"2024"},{"key":"10.1016\/j.array.2026.100784_b8","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1109\/OJITS.2022.3181510","article-title":"Autonomous vehicles on the edge: A survey on autonomous vehicle racing","volume":"3","author":"Betz","year":"2022","journal-title":"IEEE Open J Intell Transp Syst"},{"issue":"2","key":"10.1016\/j.array.2026.100784_b9","doi-asserted-by":"crossref","first-page":"110","DOI":"10.63995\/NSTN6884","article-title":"Autonomous vehicles and robust decision-making in dynamic environments","volume":"1","author":"James","year":"2020","journal-title":"Fusion Multidiscip Res Int J"},{"key":"10.1016\/j.array.2026.100784_b10","doi-asserted-by":"crossref","first-page":"177804","DOI":"10.1109\/ACCESS.2020.3022755","article-title":"Decision-making strategy on highway for autonomous vehicles using deep reinforcement learning","volume":"8","author":"Liao","year":"2020","journal-title":"IEEE Access"},{"issue":"4","key":"10.1016\/j.array.2026.100784_b11","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1109\/TIV.2022.3188662","article-title":"Prediction-uncertainty-aware decision-making for autonomous vehicles","volume":"7","author":"Tang","year":"2022","journal-title":"IEEE Trans Intell Veh"},{"issue":"6","key":"10.1016\/j.array.2026.100784_b12","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"},{"issue":"1","key":"10.1016\/j.array.2026.100784_b13","article-title":"Autonomous vehicles and intelligent automation: Applications, challenges, and opportunities","volume":"2022","author":"Bathla","year":"2022","journal-title":"Mob Inf Syst"},{"issue":"4","key":"10.1016\/j.array.2026.100784_b14","doi-asserted-by":"crossref","first-page":"1861","DOI":"10.1007\/s40996-023-01291-8","article-title":"Efficiency and safety of traffic networks under the effect of autonomous vehicles","volume":"48","author":"Hosseinian","year":"2024","journal-title":"Iran J Sci Technol Trans Civ Eng"},{"key":"10.1016\/j.array.2026.100784_b15","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.isprsjprs.2022.12.021","article-title":"Perception and sensing for autonomous vehicles under adverse weather conditions: A survey","volume":"196","author":"Zhang","year":"2023","journal-title":"ISPRS J Photogramm Remote Sens"},{"issue":"7","key":"10.1016\/j.array.2026.100784_b16","doi-asserted-by":"crossref","first-page":"3871","DOI":"10.1109\/TIV.2023.3271624","article-title":"Multi-modal sensor fusion and object tracking for autonomous racing","volume":"8","author":"Karle","year":"2023","journal-title":"IEEE Trans Intell Veh"},{"key":"10.1016\/j.array.2026.100784_b17","series-title":"An introduction to the Kalman filter. \u2026","author":"Welch","year":"1995"},{"issue":"7","key":"10.1016\/j.array.2026.100784_b18","doi-asserted-by":"crossref","first-page":"908","DOI":"10.1049\/itr2.12185","article-title":"Quantifying the performance and optimizing the placement of roadside sensors for cooperative vehicle-infrastructure systems","volume":"16","author":"Du","year":"2022","journal-title":"IET Intell Transp Syst"},{"key":"10.1016\/j.array.2026.100784_b19","doi-asserted-by":"crossref","unstructured":"Li Y, Yu AW, Meng T, Caine B, Ngiam J, Peng D, Shen J, Lu Y, Zhou D, Le QV, et al. Deepfusion: Lidar-camera deep fusion for multi-modal 3d object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 2022, p. 17182\u201391.","DOI":"10.1109\/CVPR52688.2022.01667"},{"issue":"5","key":"10.1016\/j.array.2026.100784_b20","doi-asserted-by":"crossref","first-page":"5668","DOI":"10.1109\/JSEN.2020.3041615","article-title":"Multi-object detection and tracking, based on DNN, for autonomous vehicles: A review","volume":"21","author":"Ravindran","year":"2020","journal-title":"IEEE Sensors J"},{"key":"10.1016\/j.array.2026.100784_b21","doi-asserted-by":"crossref","DOI":"10.1016\/j.compeleceng.2022.108030","article-title":"A lifelong framework for data quality monitoring of roadside sensors in cooperative vehicle-infrastructure systems","volume":"100","author":"Du","year":"2022","journal-title":"Comput Electr Eng"},{"key":"10.1016\/j.array.2026.100784_b22","series-title":"European robotics forum","first-page":"280","article-title":"Exploiting roadside sensor data for vehicle manoeuvring assistance","author":"Princiotto","year":"2024"},{"key":"10.1016\/j.array.2026.100784_b23","series-title":"2023 IEEE intelligent vehicles symposium","first-page":"1","article-title":"Safe autonomous driving in adverse weather: Sensor evaluation and performance monitoring","author":"Sezgin","year":"2023"},{"issue":"20","key":"10.1016\/j.array.2026.100784_b24","doi-asserted-by":"crossref","first-page":"25346","DOI":"10.1109\/JSEN.2023.3312911","article-title":"LiDAR-based NDT matching performance evaluation for positioning in adverse weather conditions","volume":"23","author":"Chang","year":"2023","journal-title":"IEEE Sensors J"},{"issue":"1","key":"10.1016\/j.array.2026.100784_b25","doi-asserted-by":"crossref","first-page":"14","DOI":"10.3390\/s24010014","article-title":"Performance verification of autonomous driving LiDAR sensors under rainfall conditions in darkroom","volume":"24","author":"Choe","year":"2023","journal-title":"Sensors"},{"issue":"20","key":"10.1016\/j.array.2026.100784_b26","doi-asserted-by":"crossref","first-page":"8471","DOI":"10.3390\/s23208471","article-title":"Object detection in adverse weather for autonomous driving through data merging and YOLOv8","volume":"23","author":"Kumar","year":"2023","journal-title":"Sensors"},{"key":"10.1016\/j.array.2026.100784_b27","series-title":"2024 IEEE\/RSJ international conference on intelligent robots and systems","first-page":"3218","article-title":"An observability constrained downward-facing optical-flow-aided visual-inertial odometry","author":"Liu","year":"2024"},{"key":"10.1016\/j.array.2026.100784_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.arcontrol.2023.100910","article-title":"Lateral control for autonomous vehicles: A comparative evaluation","volume":"57","author":"Artu\u00f1edo","year":"2024","journal-title":"Annu Rev Control"},{"key":"10.1016\/j.array.2026.100784_b29","series-title":"UAV-based intelligent information systems on winter road safety for autonomous vehicles","author":"Ariram","year":"2024"},{"key":"10.1016\/j.array.2026.100784_b30","series-title":"2010 IEEE international conference on pervasive computing and communications","first-page":"79","article-title":"An integrated network of roadside sensors and vehicles for driving safety: Concept, design and experiments","author":"Qin","year":"2010"},{"key":"10.1016\/j.array.2026.100784_b31","first-page":"283","article-title":"Roadside sensor network deployment based on vehicle-infrastructure cooperative intelligent driving","volume":"4","author":"An","year":"2023","journal-title":"Int J Intell Netw"},{"key":"10.1016\/j.array.2026.100784_b32","series-title":"International conference on smartRail, traffic and transportation engineering","first-page":"305","article-title":"Deployment optimization of roadside sensing units based on NSGA-II for vehicle infrastructure cooperated autonomous driving","author":"Zhao","year":"2023"},{"key":"10.1016\/j.array.2026.100784_b33","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1016\/j.trf.2021.08.018","article-title":"Interaction between pedestrians and automated vehicles: Exploring a motion-based approach for virtual reality experiments","volume":"82","author":"Bindsch\u00e4del","year":"2021","journal-title":"Transp Res Part F: Traffic Psychol Behav"},{"key":"10.1016\/j.array.2026.100784_b34","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121358","article-title":"Potential sources of sensor data anomalies for autonomous vehicles: An overview from road vehicle safety perspective","volume":"236","author":"Zhao","year":"2024","journal-title":"Expert Syst Appl"},{"key":"10.1016\/j.array.2026.100784_b35","doi-asserted-by":"crossref","DOI":"10.1109\/TITS.2023.3307589","article-title":"Crossfuser: Multi-modal feature fusion for end-to-end autonomous driving under unseen weather conditions","author":"Wu","year":"2023","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"3","key":"10.1016\/j.array.2026.100784_b36","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0893-6080(00)00098-8","article-title":"Bayesian approach for neural networks\u2014review and case studies","volume":"14","author":"Lampinen","year":"2001","journal-title":"Neural Netw"},{"key":"10.1016\/j.array.2026.100784_b37","article-title":"Survey: Time-series data preprocessing: A survey and an empirical analysis","author":"Tawakuli","year":"2024","journal-title":"J Eng Res"},{"issue":"2","key":"10.1016\/j.array.2026.100784_b38","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1177\/03611981231172949","article-title":"Roadside LiDAR sensor configuration assessment and optimization methods for vehicle detection and tracking in connected and automated vehicle applications","volume":"2678","author":"Ge","year":"2024","journal-title":"Transp Res Rec"},{"key":"10.1016\/j.array.2026.100784_b39","article-title":"Roadside visual sensor deployment in urban networks considering vehicle control boundary","author":"Xu","year":"2025","journal-title":"IEEE Sensors J"},{"key":"10.1016\/j.array.2026.100784_b40","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2019.135237","article-title":"Connected & autonomous vehicles\u2013environmental impacts\u2013A review","volume":"712","author":"Kopelias","year":"2020","journal-title":"Sci Total Environ"},{"key":"10.1016\/j.array.2026.100784_b41","series-title":"2022 IEEE 95th vehicular technology conference:(VTC2022-spring)","first-page":"1","article-title":"Simulating realistic rain, snow, and fog variations for comprehensive performance characterization of lidar perception","author":"Teufel","year":"2022"},{"issue":"16","key":"10.1016\/j.array.2026.100784_b42","doi-asserted-by":"crossref","first-page":"5397","DOI":"10.3390\/s21165397","article-title":"An overview of autonomous vehicles sensors and their vulnerability to weather conditions","volume":"21","author":"Vargas","year":"2021","journal-title":"Sensors"},{"issue":"10","key":"10.1016\/j.array.2026.100784_b43","doi-asserted-by":"crossref","first-page":"7572","DOI":"10.1109\/JIOT.2021.3130054","article-title":"Autonomous driving security: State of the art and challenges","volume":"9","author":"Gao","year":"2021","journal-title":"IEEE Internet Things J"},{"issue":"3","key":"10.1016\/j.array.2026.100784_b44","doi-asserted-by":"crossref","first-page":"706","DOI":"10.3390\/s21030706","article-title":"A survey of autonomous vehicles: Enabling communication technologies and challenges","volume":"21","author":"Ahangar","year":"2021","journal-title":"Sensors"},{"key":"10.1016\/j.array.2026.100784_b45","doi-asserted-by":"crossref","unstructured":"Garcia J, Feng J, Almanee S, Xia YC, Qi A. A comprehensive study of autonomous vehicle bugs. In: Proceedings of the ACM\/IEEE 42nd international conference on software engineering. 2020, p. 385\u201396.","DOI":"10.1145\/3377811.3380397"},{"key":"10.1016\/j.array.2026.100784_b46","article-title":"Vehicle-to-everything (V2X) in the autonomous vehicles domain\u2013A technical review of communication, sensor, and AI technologies for road user safety","volume":"23","author":"Yusuf","year":"2024","journal-title":"Transp Res Interdiscip Perspect"},{"key":"10.1016\/j.array.2026.100784_b47","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.trc.2016.03.008","article-title":"Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication in a heterogeneous wireless network\u2013Performance evaluation","volume":"68","author":"Dey","year":"2016","journal-title":"Transp Res Part C: Emerg Technol"},{"key":"10.1016\/j.array.2026.100784_b48","series-title":"Towards vehicle-to-everything autonomous driving: A survey on collaborative perception","author":"Liu","year":"2023"},{"key":"10.1016\/j.array.2026.100784_b49","doi-asserted-by":"crossref","DOI":"10.1109\/MWC.014.2300277","article-title":"5G perspective of connected autonomous vehicles: Current landscape and challenges toward 6G","author":"Kakkavas","year":"2024","journal-title":"IEEE Wirel Commun"},{"key":"10.1016\/j.array.2026.100784_b50","series-title":"2020 3rd international conference on engineering technology and its applications","first-page":"159","article-title":"A review on vehicle-to-infrastructure communication system: Requirement and applications","author":"Malik","year":"2020"},{"key":"10.1016\/j.array.2026.100784_b51","article-title":"A simulation framework for prototyping intelligent vehicle-to-infrastructure applications: A case study on RSU-based intersection movement assist for connected autonomous vehicles","author":"Wu","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.array.2026.100784_b52","series-title":"On the opportunities and risks of foundation models","author":"Bommasani","year":"2021"},{"key":"10.1016\/j.array.2026.100784_b53","doi-asserted-by":"crossref","unstructured":"Cui C, Ma Y, Cao X, Ye W, Zhou Y, Liang K, Chen J, Lu J, Yang Z, Liao KD, et al. A survey on multimodal large language models for autonomous driving. In: Proceedings of the IEEE\/CVF winter conference on applications of computer vision. 2024, p. 958\u201379.","DOI":"10.1109\/WACVW60836.2024.00106"},{"key":"10.1016\/j.array.2026.100784_b54","doi-asserted-by":"crossref","unstructured":"Fu D, Li X, Wen L, Dou M, Cai P, Shi B, Qiao Y. Drive like a human: Rethinking autonomous driving with large language models. In: Proceedings of the IEEE\/CVF winter conference on applications of computer vision. 2024, p. 910\u20139.","DOI":"10.1109\/WACVW60836.2024.00102"},{"issue":"10","key":"10.1016\/j.array.2026.100784_b55","doi-asserted-by":"crossref","first-page":"4287","DOI":"10.1109\/TIV.2023.3326636","article-title":"Foundation vehicles: From foundation intelligence to foundation transportation for future mobility","volume":"8","author":"Wang","year":"2023","journal-title":"IEEE Trans Intell Veh"},{"key":"10.1016\/j.array.2026.100784_b56","doi-asserted-by":"crossref","DOI":"10.1109\/TIV.2024.3396450","article-title":"VistaRAG: Toward safe and trustworthy autonomous driving through retrieval-augmented generation","author":"Dai","year":"2024","journal-title":"IEEE Trans Intell Veh"},{"key":"10.1016\/j.array.2026.100784_b57","doi-asserted-by":"crossref","DOI":"10.1109\/LRA.2024.3440097","article-title":"Drivegpt4: Interpretable end-to-end autonomous driving via large language model","author":"Xu","year":"2024","journal-title":"IEEE Robot Autom Lett"},{"key":"10.1016\/j.array.2026.100784_b58","doi-asserted-by":"crossref","unstructured":"Chen X, Zhang T, Wang Y, Wang Y, Zhao H. Futr3d: A unified sensor fusion framework for 3d detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 2023, p. 172\u201381.","DOI":"10.1109\/CVPRW59228.2023.00022"},{"issue":"6","key":"10.1016\/j.array.2026.100784_b59","doi-asserted-by":"crossref","first-page":"3335","DOI":"10.3390\/s23063335","article-title":"Sensor fusion in autonomous vehicle with traffic surveillance camera system: detection, localization, and AI networking","volume":"23","author":"Hasanujjaman","year":"2023","journal-title":"Sensors"},{"key":"10.1016\/j.array.2026.100784_b60","doi-asserted-by":"crossref","unstructured":"Singh A. Transformer-based sensor fusion for autonomous driving: A survey. In: Proceedings of the IEEE\/CVF international conference on computer vision. 2023, p. 3312\u20137.","DOI":"10.1109\/ICCVW60793.2023.00355"},{"key":"10.1016\/j.array.2026.100784_b61","doi-asserted-by":"crossref","unstructured":"Huang Z, Liu H, Lv C. Gameformer: Game-theoretic modeling and learning of transformer-based interactive prediction and planning for autonomous driving. In: Proceedings of the IEEE\/CVF international conference on computer vision. 2023, p. 3903\u201313.","DOI":"10.1109\/ICCV51070.2023.00361"},{"key":"10.1016\/j.array.2026.100784_b62","series-title":"HawkDrive: A transformer-driven visual perception system for autonomous driving in night scene","author":"Guo","year":"2024"},{"issue":"3","key":"10.1016\/j.array.2026.100784_b63","doi-asserted-by":"crossref","first-page":"1972","DOI":"10.1109\/COMST.2021.3057017","article-title":"A tutorial on 5G NR V2X communications","volume":"23","author":"Garcia","year":"2021","journal-title":"IEEE Commun Surv Tutor"},{"key":"10.1016\/j.array.2026.100784_b64","series-title":"2024 IEEE intelligent vehicles symposium","first-page":"1693","article-title":"A comparison of imitation learning pipelines for autonomous driving on the effect of change in ego-vehicle","author":"Ajak","year":"2024"},{"issue":"1","key":"10.1016\/j.array.2026.100784_b65","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1119\/1.4755780","article-title":"Radiometry and the friis transmission equation","volume":"81","author":"Shaw","year":"2013","journal-title":"Am J Phys"},{"issue":"1","key":"10.1016\/j.array.2026.100784_b66","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TIT.1979.1055985","article-title":"On the Shannon capacity of a graph","volume":"25","author":"Lov\u00e1sz","year":"1979","journal-title":"IEEE Trans Inform Theory"},{"issue":"3","key":"10.1016\/j.array.2026.100784_b67","doi-asserted-by":"crossref","DOI":"10.1016\/j.geits.2022.100023","article-title":"A review on cooperative perception and control supported infrastructure-vehicle system","volume":"1","author":"Yu","year":"2022","journal-title":"Green Energy Intell Transp"},{"key":"10.1016\/j.array.2026.100784_b68","series-title":"Proceedings of the 1st annual conference on robot learning","first-page":"1","article-title":"CARLA: An open urban driving simulator","author":"Dosovitskiy","year":"2017"}],"container-title":["Array"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2590005626001074?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2590005626001074?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T09:23:55Z","timestamp":1777368235000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2590005626001074"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":68,"alternative-id":["S2590005626001074"],"URL":"https:\/\/doi.org\/10.1016\/j.array.2026.100784","relation":{},"ISSN":["2590-0056"],"issn-type":[{"value":"2590-0056","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Enhancing autonomous vehicle resilience: Roadside sensor networks for robust perception and decision-making in challenging environments","name":"articletitle","label":"Article Title"},{"value":"Array","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.array.2026.100784","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"100784"}}