{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T22:47:00Z","timestamp":1767912420426,"version":"3.49.0"},"reference-count":20,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T00:00:00Z","timestamp":1735776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["U20A20330"],"award-info":[{"award-number":["U20A20330"]}]},{"name":"National Natural Science Foundation of China","award":["52131203"],"award-info":[{"award-number":["52131203"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>The impact of disturbances on a transportation network varies depending on the location and characteristics of the affected highway segments. Given limited resources, it is crucial to prioritize the protection and repair of highway segments based on their importance to maintaining overall network performance during disruptions. This paper proposes a novel method for ranking the importance of highway segments, leveraging a novel local\u2013transit percolation and clustering-based method. Initially, the highway network is constructed by Graph theory, and the k-means clustering method is applied considering each segment\u2019s transit and local traffic flows. Subsequently, a local\u2013transit percolation model is constructed to generate an initial ranking of segments based on the size of the second-largest clusters during the percolation phase transition. A secondary ranking is performed by refining the results from the clustering phase. Results of a control experiment show that, compared to baselines, the proposed ranking approach demonstrates a significantly improved ability to sustain network demand and connectivity when high-ranked segments are moved. The model uncertainty analysis was conducted by adding noise to the gantry records, and the experiments demonstrated that the model exhibits robustness under noisy conditions. These findings highlight the effectiveness and superiority of the proposed method.<\/jats:p>","DOI":"10.3390\/systems13010028","type":"journal-article","created":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T10:32:26Z","timestamp":1735813946000},"page":"28","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Local\u2013Transit Percolation and Clustering-Based Method for Highway Segment Importance Ranking"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-1118-0683","authenticated-orcid":false,"given":"Huizhe","family":"Lyu","sequence":"first","affiliation":[{"name":"School of Transportation, Southeast University, No. 2 Southeast University Road, Nanjing 211189, China"},{"name":"Key Laboratory of Transport Industry of Comprehensive Transportation Theory (Nanjing Modern Multimodal Transportation Laboratory), Ministry of Transport, No. 56 Baoshan Temple Road, Nanjing 211135, China"},{"name":"National Demonstration Center for Experimental Road and Traffic Engineering Education, Southeast University, No. 2 Southeast University Road, Nanjing 211189, China"}]},{"given":"Yang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, No. 2 Southeast University Road, Nanjing 211189, China"},{"name":"Key Laboratory of Transport Industry of Comprehensive Transportation Theory (Nanjing Modern Multimodal Transportation Laboratory), Ministry of Transport, No. 56 Baoshan Temple Road, Nanjing 211135, China"}]},{"given":"Chenxu","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, No. 2 Southeast University Road, Nanjing 211189, China"},{"name":"Key Laboratory of Transport Industry of Comprehensive Transportation Theory (Nanjing Modern Multimodal Transportation Laboratory), Ministry of Transport, No. 56 Baoshan Temple Road, Nanjing 211135, China"}]},{"given":"Zhonghao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, No. 2 Southeast University Road, Nanjing 211189, China"},{"name":"National Demonstration Center for Experimental Road and Traffic Engineering Education, Southeast University, No. 2 Southeast University Road, Nanjing 211189, China"}]},{"given":"Lin","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, No. 2 Southeast University Road, Nanjing 211189, China"},{"name":"National Demonstration Center for Experimental Road and Traffic Engineering Education, Southeast University, No. 2 Southeast University Road, Nanjing 211189, China"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, No. 2 Southeast University Road, Nanjing 211189, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2360-3712","authenticated-orcid":false,"given":"Jun","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, No. 2 Southeast University Road, Nanjing 211189, China"},{"name":"Key Laboratory of Transport Industry of Comprehensive Transportation Theory (Nanjing Modern Multimodal Transportation Laboratory), Ministry of Transport, No. 56 Baoshan Temple Road, Nanjing 211135, China"},{"name":"Hangzhou International Urbanology Research Center, No. 2318 Yu Hang Tang Lu, Hangzhou 311121, China"},{"name":"Zhejiang Urban Governance Studies Center, No. 2318 Yu Hang Tang Lu, Hangzhou 311121, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1007\/s11067-006-9284-9","article-title":"Application of accessibility based methods for vulnerability analysis of strategic road networks","volume":"6","author":"Taylor","year":"2006","journal-title":"Networks Spat. Econ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"104490","DOI":"10.1016\/j.trc.2024.104490","article-title":"A hybrid approach of traffic simulation and machine learning techniques for enhancing real-time traffic prediction","volume":"160","author":"Kim","year":"2024","journal-title":"Transp. Res. Part Emerg. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1109\/TITS.2017.2700080","article-title":"Critical Link Analysis for Urban Transportation Systems","volume":"19","author":"Zhou","year":"2018","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"107458","DOI":"10.1016\/j.ress.2021.107458","article-title":"A computationally efficient metric for identification of critical links in large transportation networks","volume":"209","author":"Almotahari","year":"2021","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1016\/j.cstp.2019.07.006","article-title":"Multi-criteria based approach to identify critical links in a transportation network","volume":"7","author":"Kumar","year":"2019","journal-title":"Case Stud. Transp. Policy"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"103022","DOI":"10.1016\/j.tre.2023.103022","article-title":"Practice-based post-disaster road network connectivity analysis using a data-driven percolation theory-based method","volume":"171","author":"Chang","year":"2023","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"129639","DOI":"10.1016\/j.physa.2024.129639","article-title":"Resilience analysis of highway network under rainfall using a data-driven percolation theory-based method","volume":"638","author":"Li","year":"2024","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.cja.2019.09.020","article-title":"Percolation transition in temporal airport network","volume":"33","author":"Liu","year":"2020","journal-title":"Chin. J. Aeronaut."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"13230","DOI":"10.1109\/TITS.2021.3122459","article-title":"Modeling stochastic behavior of road networks with disruptions using percolation theory","volume":"23","author":"Zhou","year":"2021","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"105492","DOI":"10.1016\/j.cnsns.2020.105492","article-title":"Percolation in multilayer complex networks with connectivity and interdependency topological structures","volume":"92","author":"Cao","year":"2021","journal-title":"Commun. Nonlinear Sci. Numer. Simul."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"020301","DOI":"10.1103\/PhysRevE.100.020301","article-title":"Enhancing the robustness of a multiplex network leads to multiple discontinuous percolation transitions","volume":"100","author":"Kryven","year":"2019","journal-title":"Phys. Rev. E"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.physa.2016.01.001","article-title":"Explosive percolation in thresholded networks","volume":"451","author":"Hayasaka","year":"2016","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Song, Z., Cai, J., and Yang, Q. (2024). Taxi travel distance clustering method based on exponential fitting and k-means using data from the US and China. Systems, 12.","DOI":"10.3390\/systems12080282"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3567","DOI":"10.1109\/TITS.2020.2995856","article-title":"Vehicle trajectory clustering based on dynamic representation learning of internet of vehicles","volume":"22","author":"Wang","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1807","DOI":"10.1109\/TITS.2020.3008884","article-title":"Big data analysis technology for electric vehicle networks in smart cities","volume":"22","author":"Lv","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Song, Q., Hu, J., Zhang, R., and Zhang, Z. (2019, January 6\u20138). An urban topological map generation method for traffic flow prediction based on road segment clustering with floating vehicle trajectory dataset. Proceedings of the 19th Cota International Conference of Transportation Professio (CICTP 2019), Nanjing, China.","DOI":"10.1061\/9780784482292.203"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ko\u0161anin, I., Gnjatovi\u0107, M., Ma\u010dek, N., and Joksimovi\u0107, D. (2023). A clustering-based approach to detecting critical traffic road segments in urban areas. Axioms, 12.","DOI":"10.3390\/axioms12060509"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"104264","DOI":"10.1016\/j.trc.2023.104264","article-title":"Dependency cluster analysis of urban road network based on percolation","volume":"154","author":"Deng","year":"2023","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"105575","DOI":"10.1016\/j.ssci.2021.105575","article-title":"Urban road network vulnerability and resilience to large-scale attacks","volume":"147","author":"Vivek","year":"2022","journal-title":"Saf. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"L012301","DOI":"10.1103\/PhysRevE.104.L012301","article-title":"Stability of traffic breakup patterns in urban networks","volume":"104","author":"Cogoni","year":"2021","journal-title":"Phys. Rev. E"}],"container-title":["Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-8954\/13\/1\/28\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T10:22:04Z","timestamp":1759918924000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-8954\/13\/1\/28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,2]]},"references-count":20,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,1]]}},"alternative-id":["systems13010028"],"URL":"https:\/\/doi.org\/10.3390\/systems13010028","relation":{},"ISSN":["2079-8954"],"issn-type":[{"value":"2079-8954","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,2]]}}}