{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T04:46:10Z","timestamp":1791780370515,"version":"4.3.4"},"reference-count":47,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>While advancements in autonomous vehicle (AV) technology heavily favor urban environments, rural and tribal regions remain severely underprepared for automated deployment due to physical infrastructure deficiencies and communication limitations. To address this disparity, this paper formulates a scalable, low-cost multimodal framework designed to systematically evaluate rural infrastructure readiness across three critical operational domains: communication connectivity, lane marking detectability, and road surface kinematics. First, cellular network reliability is mapped via mobile telemetry to isolate connectivity-deficient risk zones. Second, a vision-based perception module leverages deep learning models on GPS-tagged video footage to quantify lane marking detectability. Third, an onboard road surface assessment pipeline captures inertial measurement unit (IMU) and GPS data to calculate safety-critical geometry metrics\u2014including rollover risk and composite acceleration\u2014while introducing a rapid estimation using the Analytic Hierarchy Process (AHP) of the roadway International Roughness Index (IRI). These sub-indicators are weighted and synthesized into a unified Autonomous Vehicle Readiness Index (ARI) to map to the spatial readiness of AV-critical infrastructure systems. Validated across underserved rural corridors, this framework provides transportation agencies with an objective, data-driven decision engine to prioritize localized infrastructure remediation and accelerate safe, equitable AV deployment.<\/jats:p>","DOI":"10.3390\/s26196067","type":"journal-article","created":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T16:29:53Z","timestamp":1790267393000},"page":"6067","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Infrastructure Preparedness for Autonomous Vehicles in Rural Areas"],"prefix":"10.3390","volume":"26","author":[{"given":"Joshua X. S.","family":"Li","sequence":"first","affiliation":[{"name":"Oklahoma School of Science and Mathematics (OSSM), Oklahoma City, OK 74074, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin X. Y.","family":"Li","sequence":"additional","affiliation":[{"name":"Stillwater High School, Stillwater, OK 74075, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8601-8230","authenticated-orcid":false,"given":"Yiming","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Oklahoma State University, Stillwater, OK 74078, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9462-2208","authenticated-orcid":false,"given":"Junlong","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Oklahoma State University, Stillwater, OK 74078, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2632-7808","authenticated-orcid":false,"given":"Joshua Q.","family":"Li","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Oklahoma State University, Stillwater, OK 74078, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4222-7273","authenticated-orcid":false,"given":"Anirudh","family":"Paranjothi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Oklahoma State University, Stillwater, OK 74078, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ansarinejad, M., Ansarinejad, K., Lu, P., Huang, Y., and Tolliver, D. (2025). Autonomous Vehicles in Rural Areas: A Review of Challenges, Opportunities, and Solutions. Appl. Sci., 15.","DOI":"10.3390\/app15084195"},{"key":"ref_2","unstructured":"Gopalakrishna, D., Carlson, P.J., Sweatman, P., Raghunathan, D., Brown, L., and Serulle, N.U. (2021). Impacts of Automated Vehicles on Highway Infrastructure, Federal Highway Administration. Technical Report."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Sadaf, M., Iqbal, Z., Javed, A.R., Saba, I., Krichen, M., Majeed, S., and Raza, A. (2023). Connected and Automated Vehicles: Infrastructure, Applications, Security, Critical Challenges, and Future Aspects. Technologies, 11.","DOI":"10.3390\/technologies11050117"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"100045","DOI":"10.1016\/j.array.2020.100045","article-title":"Vehicular LTE connectivity analysis in urban and rural environments using USRP measurements","volume":"8","author":"Vasudeva","year":"2020","journal-title":"Array"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"117593","DOI":"10.1109\/ACCESS.2020.3004779","article-title":"A Survey of 5G Technology Evolution, Standards, and Infrastructure Associated with Vehicle-to-Everything Communications by Internet of Vehicles","volume":"8","author":"Storck","year":"2020","journal-title":"IEEE Access"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3729","DOI":"10.1109\/ACCESS.2023.3234442","article-title":"Lane Detection in Autonomous Vehicles: A Systematic Review","volume":"11","author":"Zakaria","year":"2023","journal-title":"IEEE Access"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1109\/TIV.2016.2578706","article-title":"A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles","volume":"1","author":"Paden","year":"2016","journal-title":"IEEE Trans. Intell. Veh."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Asadi, Y. (2026). Paving the Future of Intelligent Pavement Defect Detection with Machine Learning: A Comprehensive Survey of Techniques and Applications. Int. J. Pavement Res. Technol., in press.","DOI":"10.1007\/s42947-026-00711-y"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1016\/j.jreng.2025.10.001","article-title":"A critical review on pavement distress detection using images and point clouds from visual features to geometric modeling","volume":"5","author":"Jing","year":"2025","journal-title":"J. Road Eng."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Mahmoudzadeh, A., Yeganeh, S.F., Arezoumand, S., and Golroo, A. (2019). 3D Pavement Surface Reconstruction Using an RGB-D Sensor. Proceedings, 42.","DOI":"10.3390\/ecsa-6-06641"},{"key":"ref_11","unstructured":"Carreras, O., Da Silva, J., Soria, I., Garcia, J., and Zimanyi, E. (2018, January 16\u201319). Road Infrastructure Support Levels for Automated Driving (ISAD). Proceedings of the 7th Transport Research Arena (TRA), Vienna, Austria."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Haas, R., Hudson, W.R., and Zaniewski, J. (2015). Modern Pavement Management, Krieger Publishing Company.","DOI":"10.1002\/9781119038849"},{"key":"ref_13","unstructured":"(2021). Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles (Standard No. SAE J3016_202104)."},{"key":"ref_14","unstructured":"KPMG International (2020). 2020 Autonomous Vehicles Readiness Index: Assessing the Preparedness of 30 Countries and Jurisdictions, KPMG International Cooperative. Research Report."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Khan, J.A., Wang, L., Jacobs, E., Talebian, A., Mishra, S., Santo, C.A., Golias, M., and Astorne-Figari, C. (2019). Smart Cities Connected and Autonomous Vehicles Readiness Index. Proceedings of the ACM\/EIGSCC Symposium on Smart Cities and Communities (SCC \u201919), ACM.","DOI":"10.1145\/3357492.3358631"},{"key":"ref_16","unstructured":"Saeed, T.U. (2019). Road Infrastructure Readiness for Autonomous Vehicles. [Ph.D. Thesis, Purdue University]."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"103820","DOI":"10.1016\/j.autcon.2021.103820","article-title":"Automated assessment of infrastructure preparedness for autonomous vehicles","volume":"129","author":"Gouda","year":"2021","journal-title":"Autom. Constr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.tranpol.2022.09.012","article-title":"City readiness for connected and autonomous vehicles: A multi-stakeholder and multi-criteria analysis through analytic hierarchy process","volume":"128","author":"Jiang","year":"2022","journal-title":"Transp. Policy"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.trf.2023.02.001","article-title":"Technology readiness and intentions to use conditionally automated vehicles","volume":"94","year":"2023","journal-title":"Transp. Res. Part F Traffic Psychol. Behav."},{"key":"ref_20","first-page":"383","article-title":"Autonomous Vehicle Technology and Technology Acceptance: The Role of Technological Readiness on Consumers\u2019 Attitudes Towards Driverless Cars and Intention to Use in the Future","volume":"36","year":"2024","journal-title":"Future"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"922","DOI":"10.15196\/RS140505","article-title":"Statistical analysis of Hungarian cities\u2019 autonomous vehicle preparedness: Correlations, ranking and neural network","volume":"14","author":"Lukovics","year":"2024","journal-title":"Reg. Stat."},{"key":"ref_22","unstructured":"Toth, C., Perry, F., and Keshmiri, A. (2025). Connected and Autonomous Vehicle Readiness Action Plan, Tennessee Department of Transportation. Technical Report."},{"key":"ref_23","unstructured":"(2025). Developing a Guideline and Feasibility Tool for Highway Infrastructure Readiness for Autonomous Vehicles. [Ph.D. Thesis, Eastern Michigan University]."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Kiattikomol, V., Nuangrod, L., Rung-in, A., and Chuathong, V. (2025). Assessing Infrastructure Readiness of Controlled-Access Roads in West Bangkok for Autonomous Vehicle Deployment. Infrastructures, 10.","DOI":"10.3390\/infrastructures10100270"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1177\/03611981251378138","article-title":"Investigating Automated Shuttle Readiness for Rural Areas: North Carolina Case Study","volume":"2680","author":"Alaka","year":"2026","journal-title":"Transp. Res. Rec."},{"key":"ref_26","unstructured":"Italiano, L., Marino, F., Brambilla, M., Megna, G., Carambia, B., and Nicoli, M. (2026). Highway Readiness Assessment for SAE Levels of Automation and V2X Notification. arXiv."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Babi\u0107, D., Babi\u0107, D., Fioli\u0107, M., Eichberger, A., and Magosi, Z.F. (2022). Impact of road marking retroreflectivity on machine vision in dry conditions: On-road test. Sensors, 22.","DOI":"10.3390\/s22041303"},{"key":"ref_28","unstructured":"Pike, A., Shirinzad, M., Nayak, A., and Rathinam, S. (2024). Assessing Pavement Markings for Automated Vehicle Readiness, Minnesota Department of Transportation. Report No. MN 2024-16."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1007\/s00138-011-0404-2","article-title":"Recent progress in road and lane detection: A survey","volume":"25","author":"Lerner","year":"2014","journal-title":"Mach. Vis. Appl."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s12544-015-0156-6","article-title":"Review of remote sensing methodologies for pavement management and assessment","volume":"7","author":"Schnebele","year":"2015","journal-title":"Eur. Transp. Res. Rev."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Lebaku, P.K.R., Gao, L., Lu, P., and Sun, J. (2024). Deep learning for pavement condition evaluation using satellite imagery. Infrastructures, 9.","DOI":"10.3390\/infrastructures9090155"},{"key":"ref_32","first-page":"15108","article-title":"GSENet: Global Semantic Enhancement Network for Lane Detection","volume":"38","author":"Su","year":"2024","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Liu, J., Li, J.Q., Du, X., and Golalipour, A. (2026). Lane Marking Segmentation Based on Conditional Diffusion Model. 2026 IEEE Intelligent Vehicles Symposium (IV), IEEE.","DOI":"10.1109\/IV66570.2026.11624100"},{"key":"ref_34","unstructured":"(2026, August 11). TuSimple Lane Detection Benchmark. Available online: https:\/\/github.com\/TuSimple\/tusimple-benchmark."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Feng, Z., Guo, S., Tan, X., Xu, K., Wang, M., and Ma, L. (2022). Rethinking efficient lane detection via curve modeling. 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE.","DOI":"10.1109\/CVPR52688.2022.01655"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wang, J., Ma, Y., Huang, S., Hui, T., Wang, F., Qian, C., and Zhang, T. (2022). A keypoint-based global association network for lane detection. 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE.","DOI":"10.1109\/CVPR52688.2022.00145"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Qin, Z., Wang, H., and Li, X. (2020). Ultra fast structure-aware deep lane detection. European Conference on Computer Vision, Springer.","DOI":"10.1007\/978-3-030-58586-0_17"},{"key":"ref_38","unstructured":"(1978). Manual on Uniform Traffic Control Devices, U.S.N.A.C. Manual on Uniform Traffic Control Devices for Streets and Highways, U.S. Department of Transportation, Federal Highway Administration."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1016\/j.aap.2004.03.002","article-title":"Crash reduction following installation of centerline rumble strips on rural two-lane roads","volume":"36","author":"Persaud","year":"2004","journal-title":"Accid. Anal. Prev."},{"key":"ref_40","unstructured":"Texas Department of Transportation (2021). Test Procedure for Operating Inertial Profilers and Evaluating Pavement Profiles (Tex-1001-S), Texas Department of Transportation. Txdot Manual."},{"key":"ref_41","first-page":"708","article-title":"Road roughness and whole body vibration: Evaluation tools and comfort limits","volume":"19","author":"Cantisani","year":"2010","journal-title":"Autom. Constr."},{"key":"ref_42","unstructured":"Saaty, T.L. (1982). Decision Making for Leaders: The Analytical Hierarchy Process for Decisions in a Complex World, Lifetime Learning Publications."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/0022-2496(77)90033-5","article-title":"A scaling method for priorities in hierarchical structures","volume":"15","author":"Saaty","year":"1977","journal-title":"J. Math. Psychol."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Saaty, T.L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, McGraw-Hill.","DOI":"10.21236\/ADA214804"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/0022-2496(83)90028-7","article-title":"Procedures for synthesizing ratio judgements","volume":"27","author":"Saaty","year":"1983","journal-title":"J. Math. Psychol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1287\/opre.49.4.469.11231","article-title":"The analytic hierarchy process\u2014An exposition","volume":"49","author":"Forman","year":"2001","journal-title":"Oper. Res."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Zeki, \u00d6., G\u00fcner, P., Zeki, M., and Ozkaynak, M. (2025). Prioritizing delirium risk factors in nursing: A cross-sectional study using the analytic hierarchy process. BMC Nurs., 24.","DOI":"10.1186\/s12912-025-03454-6"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/19\/6067\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T04:10:19Z","timestamp":1791778219000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/19\/6067"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,24]]},"references-count":47,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2026,10]]}},"alternative-id":["s26196067"],"URL":"https:\/\/doi.org\/10.3390\/s26196067","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,24]]}}}