{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T09:56:45Z","timestamp":1774691805949,"version":"3.50.1"},"reference-count":57,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,12,21]],"date-time":"2025-12-21T00:00:00Z","timestamp":1766275200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52432010"],"award-info":[{"award-number":["52432010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Road traffic significantly contributes to fuel consumption and emissions. Fortunately, the advent of cooperative adaptive cruise control (CACC), facilitated by vehicle-to-vehicle (V2V) communication, reduces energy consumption and improves efficiency in transportation systems. Nevertheless, V2V communication performance (V2VCP) is highly vulnerable to degradation due to various factors. Limited comprehension exists regarding the generalized modeling of subpar V2V communication performance (SV2VCP), coupled with limited exploration of its resulting impacts on environmental sustainability. To bridge these gaps, this study presents the first attempt to assess the impact of SV2VCP on fuel consumption and exhaust emissions within the CACC framework. More specifically, we adopt the multi-predecessor following (MPF) topology and model SV2VCP scenarios, along with proposing five vehicle state update methods (VSUMs). Subsequently, by simulating various SV2VCP and driving scenarios, we comprehensively understand the effects of different VSUMs, SV2VCP, and abnormal vehicle positions on the safety, emissions, and energy consumption of the platoon. The results reveal that SV2VCP substantially impacts the fuel efficiency and emission performance of the CACC platoon, with fuel consumption during deceleration exceeding that of acceleration by approximately 14% when all vehicles are subject to SV2VCP. Furthermore, our study provides critical recommendations for optimal strategy selection, aiming to foster energy conservation and emission reductions, thereby promoting sustainable transport systems.<\/jats:p>","DOI":"10.3390\/systems14010008","type":"journal-article","created":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T14:27:51Z","timestamp":1766586471000},"page":"8","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Developing Vehicular Response Strategies for Subpar Communication: Systemic Impact on Fuel Consumption and Emissions"],"prefix":"10.3390","volume":"14","author":[{"given":"Xuedong","family":"Hua","sequence":"first","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"},{"name":"Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9525-3865","authenticated-orcid":false,"given":"Yangzhen","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"},{"name":"Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weijie","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"},{"name":"Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6962-1577","authenticated-orcid":false,"given":"Wenxie","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"},{"name":"Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qihao","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"},{"name":"Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"},{"name":"Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"112875","DOI":"10.1016\/j.knosys.2024.112875","article-title":"MGCN: Mamba-integrated spatiotemporal graph convolutional network for long-term traffic forecasting","volume":"309","author":"Lin","year":"2025","journal-title":"Knowl.-Based Syst."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Lin, W., Zhang, Z., Zhao, Y., Zhang, J., and Ren, G. 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