{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T23:53:05Z","timestamp":1772236385887,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T00:00:00Z","timestamp":1768348800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100018542","name":"Natural Science Foundation of Sichuan Province","doi-asserted-by":"publisher","award":["2025NSFSC2000"],"award-info":[{"award-number":["2025NSFSC2000"]}],"id":[{"id":"10.13039\/501100018542","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Intelligent Policing Key Laboratory of Sichuan Province","award":["ZNJW2024KFQN010"],"award-info":[{"award-number":["ZNJW2024KFQN010"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The increasing proliferation of new energy vehicles and autonomous vehicles has led to the formation of mixed traffic flows characterized by diverse driving behaviors, posing new challenges for intersection signal control. To address this issue, this study proposes a multi-class customer feedback queuing network (MCFFQN) model that incorporates state-dependent road capacity and congestion propagation mechanisms to accurately capture the stochastic and dynamic nature of mixed traffic flows. An evaluation framework for intersection performance is established based on key indicators such as vehicle delay, the energy consumption of new energy vehicles, and the fuel consumption and emissions of conventional vehicles. A recursive solution algorithm is developed and validated through simulations under various traffic demand scenarios. Building on this model, a signal timing optimization model aimed at minimizing total costs\u2014including delay and environmental impacts\u2014is formulated and solved using the Mesh Adaptive Direct Search (MADS) algorithm. A case study demonstrates that the optimized signal timing scheme significantly enhances intersection performance, reducing vehicle delay, energy consumption, fuel consumption, and emissions by over 20%. The proposed methodology provides a theoretical foundation for sustainable traffic management under mixed traffic conditions.<\/jats:p>","DOI":"10.3390\/a19010071","type":"journal-article","created":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T15:12:04Z","timestamp":1768403524000},"page":"71","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Signal Timing Optimization Method for Intersections Under Mixed Traffic Conditions"],"prefix":"10.3390","volume":"19","author":[{"given":"Hongwu","family":"Li","sequence":"first","affiliation":[{"name":"School of Transportation and Logistics, Southwest Jiaotong University, Pidu District, Chengdu 611756, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yangsheng","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Transportation and Logistics, Southwest Jiaotong University, Pidu District, Chengdu 611756, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3871-225X","authenticated-orcid":false,"given":"Bin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Sichuan Vocational and Technical College of Communications, Wenjiang District, Chengdu 610039, China"},{"name":"Intelligent Policing Key Laboratory of Sichuan Province, Luzhou 646000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhang, H., Xu, X., Huang, J., and Rashed, G.I.R. 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