Journal of Traffic and Transportation Engineering-English Edition最新文献

{"title":"Decoding the safety matrix: A conceptualisation of safety indicator-based variables for highway prediction models","authors":"Loretta Bortey,&nbsp;David J. Edwards,&nbsp;Chris Roberts,&nbsp;Iain Mark Rillie","doi":"10.1016/j.jtte.2025.04.004","DOIUrl":"10.1016/j.jtte.2025.04.004","url":null,"abstract":"<div><div>Despite the success of machine learning (ML) in safety risk prediction across various industries, there is scant evidence to prove that variables used are reliable indicators of safety performance. This study provides a conceptual framework for identifying safety indicators and formulating variables from these indicators that will optimise the quality of data used for risk modelling for Highways Traffic Officers (HTOs). This aligns with Sustainable Development Goal (SDG) 3: Good Health and Well-being, particularly target 3.6, which aims to halve global road traffic deaths and injuries. A mixed philosophical stance was adopted to understand and interpret the literature on safety indicators (SI) from myriad perspectives. A three-phase iterative waterfall approach was adopted which includes: i) PRISMA-based bibliometric search to identify relevant literature; ii) scientometric and cluster analysis to identify significant SIs and key considerations for selecting appropriate indicators for different purposes; iii) grounded theory analysis to synthesise scientific discoveries. Literature on leading and lagging SIs identified pertinent considerations that must be made when selecting SIs for risk modelling (e.g., action and utility). Furthermore, leading and lagging indicators were combined to form resilient indicators that incorporate adaptability into the safety system-thereby increasing safety performance. This paper presents a novel conceptual framework for HTOs which inculcates resilient measures in SI selection for adaptability and recovery purposes; and a robust method of integrating leading and lagging indicators to create resilience. Cumulatively, the research presents the first study to provide detailed guidance on the specific criteria of ML variables significant for risk modelling and prediction.</div></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":"13 3","pages":"Pages 912-937"},"PeriodicalIF":9.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148545720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive review of the utilisation of artificial intelligence in the maintenance of railway infrastructure","authors":"Naveen Venkatesh Sridharan,&nbsp;Ramin Karim,&nbsp;Ravdeep Kour","doi":"10.1016/j.jtte.2025.08.001","DOIUrl":"10.1016/j.jtte.2025.08.001","url":null,"abstract":"<div><div>The evolution of artificial intelligence (AI) technologies has seen an excessive utility across several industrial domains including railways. In general, railway infrastructure is composed of various components like track, overhead electrical systems, signaling system and communication system. The name of these components varies with different countries; for instance, Swedish inference for the railway infrastructure components is named as Bana, El, Signal, Tele (BEST) corresponding to track, electricals, signaling and telecom. The purpose of this paper is to provide a comprehensive review on the AI technologies utilized in the maintenance of railway infrastructure. Thereby highlighting the significance of AI in facilitating the execution of maintenance activities carried out in railway infrastructure. In this study, a total of 99 scientific papers were reviewed that were published between January 2019 and April 2024. The selected papers were reviewed based on the AI techniques used in the maintenance of railway infrastructure and were further categorized into major AI technologies within components in the railway infrastructure. The analysis based on the literature survey states that most of the operation and maintenance activities revolved around the detection of track and catenary defects. Whilst, only limited or no research was found related to AI in the fields of signaling and telecom. However, the adoption and application of AI in maintenance of railway infrastructure are still at the infant stages. A large scope persists in developing a combined application of AI and multitude of techniques such as feature fusion, point cloud data, image analysis, etc., that can be adopted for effective decision-making, enhanced optimisation, ease to handle uncertainties and tackle cybersecurity related issues.</div></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":"13 3","pages":"Pages 811-836"},"PeriodicalIF":9.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148545645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on driving path planning: A review and bibliometric analysis","authors":"Fengxiang Guo,&nbsp;Yiwen Zhou,&nbsp;Jingyang Li,&nbsp;Kailun Zhou,&nbsp;Jing Cai","doi":"10.1016/j.jtte.2025.03.010","DOIUrl":"10.1016/j.jtte.2025.03.010","url":null,"abstract":"<div><div>Driving path planning is of great significance to improve driving safety and traffic efficiency. To comprehensively understand the research progress in the field of driving path planning, based on the core database of Web of Science, 1413 literatures published from 2000 to 2023 (as of October 19, 2023), covering 4674 authors and 1389 keywords, were obtained. Using bibliometric tools VOSviewer and R-Bibliometric, the research progress is systematically analyzed. Firstly, the literature is analyzed from five dimensions: annual distribution, national distribution, research institutions, source journals and core authors. Secondly, research hotspots and trends are analyzed from four perspectives: literature co-citation analysis, keyword co-occurrence analysis, high-impact literature, and development trend. On this basis, the statistical analysis structure chart and corresponding analysis and summary frameworks of research are established to summarize the research status. Results show that research in this field has experienced a period of rapid growth and tends to develop steadily. In the early stage, Italy, Singapore, and the United States accumulated more research results, and then China, Sweden and Greece’s research developed rapidly. Institutions such as the University of California, Berkeley, the Swiss Federal Institute of Technology in Zurich were involved in early research, followed by KTH Royal Institute of Technology, Beijing Institute of Technology, Tongji University. IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Vehicle Technology are the most authoritative journals in this field, and Wang Meiling, Cao Dongpu, and Fu Mengyin are the most core authors. In recent years, the focus of research on driving path planning has mainly focused on autonomous driving, among which, the research on trajectory generation considering environment recognition, method of motion and trajectory planning emphasizing efficiency and stability, planning technology of collision avoidance trajectory emphasizing safety, and the quality of the solution of planning model are the important directions.</div></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":"13 3","pages":"Pages 1006-1032"},"PeriodicalIF":9.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148545382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of high mechanical-electrical performance piezoelectric energy harvester for road applications: Modeling, theory, and experiment","authors":"Huazhi Yuan,&nbsp;Jiawei Ding,&nbsp;Shuai Wang,&nbsp;Qiang Lu,&nbsp;Hongyun Cao,&nbsp;Chaohui Wang","doi":"10.1016/j.jtte.2025.12.002","DOIUrl":"10.1016/j.jtte.2025.12.002","url":null,"abstract":"<div><div>The application of renewable energy contributes to the sustainable development of road infrastructure. Aiming at the inadequate mechanical-electrical performance of the cantilever piezoelectric energy harvester (PEH) which can be used for road electrical facilities, the shape and size of the PEH are optimized under low-frequency roadway conditions. Firstly, models of the PEH with different shapes are constructed using different methods. Then, the electrical and mechanical properties of the PEH are investigated based on the finite element method, and the shape of the PEH is determined. Finally, the electrical theory of the triangular PEH is derived and modified, and its electrical output effect is verified by experimental testing. The results show that reducing the free-end-width and length or increasing the fixed-end-width could improve the electrical performance of the PEH, but reducing the length would significantly increase the maximum stress and reduce the uniformity of stress distribution. Comprehensive analysis of the electrical and mechanical performance recommend the use of the triangular PEH. Meanwhile, the modified electrical theory is in good agreement with finite element and test results, and a single PEH reach an output power of 15.76 mW. The results help to improve the mechanical-electrical performance of PEH, which can provide a basis for the design of self-powered road electrical facilities.</div></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":"13 3","pages":"Pages 696-713"},"PeriodicalIF":9.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148545614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State of the art of railway onboard systems for driver-machine cooperation","authors":"Zaid Cahya,&nbsp;Chouki Sentouh,&nbsp;Estiko Rijanto,&nbsp;Jean-Christophe Popieul,&nbsp;Dito Eka Cahya","doi":"10.1016/j.jtte.2025.03.009","DOIUrl":"10.1016/j.jtte.2025.03.009","url":null,"abstract":"<div><div>This research presents a comprehensive review of existing literature on train driver assistance systems and associated technologies suitable for onboard railway implementation. The primary objective is to systematically identify recent technological advancements, analyze their development patterns and prevalence, and gain a deeper understanding of current research trends in railway onboard systems. To achieve this, articles published since 2015 were retrieved from the Scopus database, resulting in a selection of 179 relevant studies. Each article was manually reviewed to ensure a thorough evaluation of its objectives, methodologies, and reported impacts. The selected studies were categorized into five key domains: train condition monitoring, which focuses on predictive maintenance and system health diagnostics; environment monitoring, addressing external conditions such as weather and track status; object detection, involving obstacle identification and collision avoidance; driver monitoring, which examines human factors such as attention, fatigue, and cognitive state; and brake assistance systems, aimed at improving safety and operational efficiency. This structured classification enabled a clearer comparison of technological maturity and research emphasis across different areas. Furthermore, the review explores opportunities to enhance human-machine cooperation by linking these findings with the latest developments in railway driver advisory systems (R-DAS). Based on this synthesis, four promising future research directions are identified: adaptive trajectory optimization for energy-efficient and context-aware driving, cooperative R-DAS (CR-DAS) enabling collaborative decision-making between human drivers and automation, human-in-the-loop (HITL) shared control strategies to balance authority between operator and system, and robust remote operation with reliable authority transfer mechanisms. These directions highlight the potential for more intelligent, adaptive, and cooperative onboard systems in next-generation railways.</div></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":"13 3","pages":"Pages 780-810"},"PeriodicalIF":9.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148545647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A bibliometric review of research on driver fatigue under conditional automated driving","authors":"Dingan Ni,&nbsp;Hui Zhang,&nbsp;Naikan Ding,&nbsp;Kai Tian,&nbsp;Shaopeng Li,&nbsp;Yifan Sun","doi":"10.1016/j.jtte.2024.12.010","DOIUrl":"10.1016/j.jtte.2024.12.010","url":null,"abstract":"<div><div>In order to comprehend the research hotspots and development trends in the field of driver fatigue on conditional automated driving, from the perspective of driver fatigue state and automated driving function, multiple topic words were combined to retrieve relevant articles from the core collection database of Web of Science. A total of 231 articles were retrieved after the data screening from 2010 to 2023, and the literature analysis was conducted from the perspective of annual distribution, countries and institutions distribution, source publications distribution. Then, the VOSviewer and CiteSpace software were used to analyze the research topic and frontiers of literatures considering literature co-citation, keyword co-occurrence, and keyword burst. The results indicated that the USA, China, and Germany are the top three countries involved in driver fatigue research under conditional automated driving. Technical University of Munich is the institution that published the largest number of articles in this field. Accident Analysis &amp; Prevention, IEEE Transactions on Intelligent Transportation Systems, and Transportation Research Part F: Traffic Psychology and Behaviour are the top three journals that scholars selected to submit articles. The relevant research topics in the field of driver fatigue under conditional automated driving mainly including (a) fatigue detection method, and the effect of automated duration on driver state, (b) the effect of non-driving related tasks (NDRT) on driver behavior and fatigue state, (c) the influential indicators for fatigue from manual driving to conditional automated driving, and (d) the difference of driving behavior and fatigue state between manual driving and conditional automated driving. With the phenomenon of keywords burst, professional drivers, takeover performance, monitoring tasks, and deep learning have become the research frontiers and hotspots. In summary, this study revealed the research topic, frontiers and development trend in the field of driver fatigue under conditional automated driving through bibliometric and structured network analysis. This study hopes to offer valuable insights for future research directions, highlighting the importance of fatigue detection methods, the impact of automated driving duration, the role of non-driving related tasks, and the transition from manual to conditional automated driving condition.</div></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":"13 3","pages":"Pages 837-860"},"PeriodicalIF":9.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148545687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Main components and emission characteristics of environmentally hazardous substances from road asphalt","authors":"Menghao Wang,&nbsp;Chaohui Wang,&nbsp;Zhiwu Zuo,&nbsp;Guangxun E,&nbsp;Yao Tian,&nbsp;Qian Chen","doi":"10.1016/j.jtte.2024.06.007","DOIUrl":"10.1016/j.jtte.2024.06.007","url":null,"abstract":"<div><div>Road asphalt produces hazardous substances that pollute the environment and significantly endanger human health. To clarify complex emission characteristics of these asphalt hazardous substances (AHS), their main components of AHS were comprehensively investigated and summarized. Furthermore, the emission rules of AHS under different testing conditions were systematically studied. To quantify these dynamics, robust regression models between AHS emissions and various experimental variable were successfully established. The analytical results demonstrated that the fundamental components of AHS mainly include volatile organic compounds, inorganic small molecule gases, and solid particles. Regarding thermodynamic variables, AHS emissions exhibit a marked increase as heating temperatures elevate. This specific dynamic conforms accurately to a power function relationship, yielding a strong correlation coefficient of 0.98. Conversely, AHS emissions progressively decrease with increasing heating times; this relationship conforms to an exponential function, demonstrating a correlation coefficient of 0.90. Additionally, the increased multiples of AHS emissions and asphalt qualities conform to a positive linear functional relationship, supported by a correlation coefficient of 0.96. A comparative analysis revealed that AHS emissions originating from rubber powder-modified asphalt are the highest. In stark contrast, AHS emissions from styrene-butadiene-styrene asphalt are notably the lowest when compared directly to the other three types of commonly used road asphalt. The emitted asphalt hazardous gases generate secondary inorganic salts and secondary aerosols, which actively promote the subsequent formation of fine particulate matter within these highly complex aerosol systems.</div></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":"13 3","pages":"Pages 763-779"},"PeriodicalIF":9.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148545646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of the composition, regeneration mechanism, and performance of cold recycled asphalt mixture","authors":"Long Wen,&nbsp;Duyao Liu,&nbsp;Ran Zhang,&nbsp;Xu Yang,&nbsp;Shifa Xu,&nbsp;Chuan Qiu,&nbsp;Jie Ji","doi":"10.1016/j.jtte.2025.06.003","DOIUrl":"10.1016/j.jtte.2025.06.003","url":null,"abstract":"<div><div>This review aims to enhance the mechanical and road performance of cold recycled asphalt mixture, and advocate the application of cold recycling technology, which features lower energy consumption and reduced carbon emissions. The properties of composition materials were initially studied for cold recycled asphalt mixture, meanwhile which regeneration mechanism was subsequently revealed. Additionally, a summary of the impact of complex factors on the mechanical and road performance of cold regenerated mixtures was provided, along with a proposed method for optimizing their performance. This review summarizes the main challenges of current cold recycling technologies and discusses future research directions. From numerous studies, it is found that the composition of cold recycled asphalt mixture significantly impacts its performance. The gradation variability and dosage of reclaimed asphalt pavement (RAP) material are the main factors affecting the performance of cold recycled material. The bonding property of binder has a significant effect on the mechanical properties of the mixture. The cold regeneration mechanism of waste asphalt mixture includes the rejuvenation of aged asphalt, the bonding mechanism of binder and the enhancement impact of additives. There are many factors affecting the performance of cold reclaimed asphalt mixture. Currently, improvements in mechanical and road performance can primarily be achieved through three main avenues: controlling the quality of RAP material, modifying the binders, and incorporating high-performance additives. However, the cold recycled asphalt mixture still faces several challenges, including a low utilization rate of RAP and limited application structure layers. In addition, insufficient early strength delays the opening of traffic. In the future, it is still necessary to propose more reasonable and efficient approaches to optimize the performance of cold reclaimed asphalt mixture, diverging from traditional methods. Moreover, the intelligent monitoring, evaluation, and prediction of performance for cold recycled asphalt pavement is also highly essential.</div></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":"13 3","pages":"Pages 714-736"},"PeriodicalIF":9.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148545651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Providing a safety case for artificial neural network elements in automated driving systems: A review of challenges","authors":"Eric Coolen,&nbsp;Mark Nicholson","doi":"10.1016/j.jtte.2025.07.003","DOIUrl":"10.1016/j.jtte.2025.07.003","url":null,"abstract":"<div><div>Artificial neural networks (ANNs) have rapidly gained popularity since the availability of powerful and economical hardware solutions, opening up applications in sectors such as automotive. Due to the limitations of traditional, deterministic software in the development of autonomous vehicles, the industry is increasingly applying ANNs for tasks such as sensing and understanding the environment of a vehicle equipped with an automated driving system (ADS) to allow it to plan and subsequently execute a safe trajectory in a traffic scenario. There are safety challenges, however, in the deployment of ANNs for environmental perception tasks, and for motion planning and execution. A vehicle equipped with an ADS needs to be safe to gain the public's trust in using and/or owning such vehicles. In automotive safety engineering, the creation of a compelling safety case for the introduction of an ADS is common practice. This paper investigates the challenges in creating a safety case for the use of ANNs in an ADS and presents the status of research through a literature survey. It analyses the applicability of current automotive safety standards. Lastly, it reviews a few frameworks that offer advice on the development of autonomous systems using ANNs and evaluates their suitability for an ADS.</div></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":"13 3","pages":"Pages 861-879"},"PeriodicalIF":9.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148545688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying light penetration in short tunnels: Development and validation of a numerical model","authors":"Tien Yee,&nbsp;Jidong J. Yang,&nbsp;Joachim Joseph James,&nbsp;Shihan Ma,&nbsp;Joseph D. Marsh","doi":"10.1016/j.jtte.2025.04.003","DOIUrl":"10.1016/j.jtte.2025.04.003","url":null,"abstract":"<div><div>Light penetration into a tunnel varies considerably with the site conditions as well as tunnel geometry. Short tunnels, defined as those less than 125 m (410 ft) in length, receive insufficient attention regarding their lighting requirement largely due to the misconception that natural light can penetrate through them, thus eliminating the need for artificial lighting. However, past studies and data reveal that this assumption may not necessarily hold true, with short tunnels experiencing higher crash rates compared to longer ones, partly due to visibility and driver's adaptation to lighting conditions. Field observations further show that certain regions within short tunnels have insufficient lighting, making smaller objects difficult to see. Moreover, there is a notable lack of reliable national guidelines for providing supplemental lighting within short tunnels. This underscores the need to study light penetration conditions in short tunnels. In this paper, a numerical model was developed to address this need. The model is based on the inverse square law of light propagation and the Lambert cosine law of illumination, which serve as the foundation for simulating lighting propagation in this study. Our proposed numerical model can quantitatively determine the spatial variation of light illuminance within a short tunnel. The model's outputs were independently verified and validated using field collected data. Consequently, with more studies and refinements, this model can potentially be further developed into a design and analysis tool in the future to establish lighting requirements and improve driver safety in short tunnels.</div></div>","PeriodicalId":47239,"journal":{"name":"Journal of Traffic and Transportation Engineering-English Edition","volume":"13 3","pages":"Pages 958-973"},"PeriodicalIF":9.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148545721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}