Journal of Advanced Transportation最新文献

{"title":"Optimization of Port-Rail Intermodal Transshipment Operations Considering Shipment Reallocation in the Railway Network","authors":"Weite Pan,&nbsp;Xiaoning Zhu","doi":"10.1155/atr/6352112","DOIUrl":"https://doi.org/10.1155/atr/6352112","url":null,"abstract":"<p>As research on intermodal transport continues to grow, studies have increasingly moved beyond focusing on single transport modes. Researchers are paying more attention to how port operations align with train operations, yet systematic coordination across different transport modes remains limited. This study incorporates both the handling of intermodal containers within the port and their transportation through the railway network. It extends existing research by considering the reallocation of capacity in the hinterland railway network when intermodal containers are dispatched from the port. To achieve this, a mathematical model is formulated to coordinate ship schedule, container handling operation, and railway transportation plan, with the objective of minimizing the system delay while ensuring smooth intermodal transfers between the port and railway network. A branch-and-Benders-cut algorithm is proposed to efficiently solve the large-scale optimization problem. The framework enables the provision of scientific guidance for integrated port-railway operation management and the evaluation of system performance under various port infrastructure settings. Overall, this study addressed an important gap in the literature on port-railway coordination and provides valuable decision support for optimizing intermodal transport systems.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/6352112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148095355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Six-Stage Serial ResNet for Decomposed Prediction of Individual Daily Trip Chains Using Multisource Data","authors":"Jun Chen,&nbsp;Tingyu Wu,&nbsp;Yuanxin Chen,&nbsp;Yifei Zhuang,&nbsp;Xiaowei Li,&nbsp;Zhengyu Duan","doi":"10.1155/atr/7715359","DOIUrl":"https://doi.org/10.1155/atr/7715359","url":null,"abstract":"<p>Predicting individual daily trip chain (IDTC) provides an important basis for information recommendation and transportation organization. This paper decomposes IDTC into six subproblems: whether to travel (P1), number of trips (P2), origin of travel (P3), departure time (P4), destination of travel (P5), and arrival time (P6). Using residual networks (ResNet), six submodels (M1–M6) are designed to predict these problems sequentially, which are then integrated into a full IDTC model. The method was applied to public transportation data from Weinan City, China. Input features from transit, weather, and POI data over 8 weeks were selected via random forest. Using 49 days of data, IDTC was predicted for the following 7 days. Results show the serial ResNet model predicts IDTC effectively. Key influences include weather on P1, travel time on P2, POI on P3 and P5, arrival time on P4, and departure time on P6.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/7715359","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148092733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Quantity and Scarcity of Tourist Attractions: A Multidimensional Analysis of Tourism Highway Accessibility in Shanxi Province, China","authors":"Qiong Wu,&nbsp;Diana Binti Mohamad,&nbsp;Siyang Liu","doi":"10.1155/atr/3903250","DOIUrl":"https://doi.org/10.1155/atr/3903250","url":null,"abstract":"<p>Tourism accessibility is critical for regional development, yet traditional research overlooks the heterogeneity of attractions, resulting in resource misallocation and suboptimal tourist experiences. This study addresses this gap by integrating the term frequency–inverse document frequency algorithm into measuring tourism highway accessibility (distance, time, and cost) using point of interest (POI) data in Shanxi Province, China. The analysis of the proposed tourism highway accessibility metrics reveals that urban cores exhibit high POI-weighted accessibility but low scarcity value, and peripheral regions with unique attractions face significant accessibility penalties due to inadequate infrastructure and spatial marginalization. Although the increase in POI quantity can enhance accessibility, the effectiveness was limited when considering the scarcity. Per capita GDP and the proportion of the tertiary industry are important in influencing accessibility. The findings support prioritizing transportation infrastructure development in regions with scarce attractions to enhance accessibility, while promoting differentiated attraction development in areas saturated with homogeneous ones.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/3903250","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148092737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Driving Toward Sustainability: Understanding Consumer Behavior Toward Electric Vehicles","authors":"Duy Hoang Nguyen,&nbsp;Thy Giang Ngo","doi":"10.1155/atr/8337218","DOIUrl":"https://doi.org/10.1155/atr/8337218","url":null,"abstract":"<p>In line with the Sustainable Development Goals and the need to reduce carbon dioxide emissions, this study investigates the key determinants of Vietnamese consumers’ intention to adopt electric vehicles (EVs) in Ho Chi Minh City. Using data collected from 330 respondents and analyzed through partial least squares structural equation modeling (PLS-SEM), the study finds that monetary incentives are the strongest predictor of adoption intention, followed by subjective norm, price value, and attitude. Environmental concern, however, does not have a significant effect on adoption intention. The multigroup analysis also reveals meaningful differences across demographic segments: older and higher-income consumers are influenced more strongly by personal attitudes and incentives, whereas younger consumers are more influenced by social pressure. These findings provide useful implications for policymakers and automotive managers in designing targeted strategies to promote sustainable transportation. The study also contributes to the theoretical understanding of EV adoption in developing-country contexts and offers policy and managerial insights to support the acceleration of EV adoption in Vietnam.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/8337218","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148092734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Extending the Technology Acceptance Model: Integrating Innovation Attributes and Cognitive Styles in User Acceptance of Autonomous Delivery Vehicles","authors":"Zhuoxi Yu","doi":"10.1155/atr/8405905","DOIUrl":"https://doi.org/10.1155/atr/8405905","url":null,"abstract":"<p>The successful implementation of autonomous delivery vehicles (ADVs) hinges on user acceptance. To address existing theoretical ambiguities, this study develops and validates a comprehensive model integrating the technology acceptance model (TAM), diffusion of innovation (DOI) theory, and Kirton’s adaption–innovation theory. Data were collected from 388 experienced early adopters in China via an online survey, and the model was analyzed using partial least squares structural equation modeling (PLS-SEM). The results confirm that relative advantage and compatibility positively influence attitude (ATT), which in turn predicts usage intention. However, by using a collected cross-sectional sample, both perceived risk and complexity were found to have a significant positive influence on ATT in this specific context. Furthermore, Kirton’s cognitive styles exerted a direct positive effect on usage intention rather than a moderating one. A multigroup analysis revealed distinct acceptance pathways: men’s ATTs were driven by utilitarian factors (e.g., compatibility) while women’s were driven by experiential factors (risk and complexity), with women also demonstrating a stronger intention to recommend the service. This study contributes to the literature by challenging the conventionally negative roles of risk and complexity for experienced users and proposing a new integrated framework. The findings offer practical insights for developing phase-based and gender-differentiated marketing strategies and inform human–computer interface design for ADVs.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/8405905","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148086710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Investigation on the Bearing Capacity Estimation of the High-Step Dumping Site Foundation in Open-Pit Coal Mines","authors":"Haoran Li,&nbsp;Kun Ni,&nbsp;Chuang Liu,&nbsp;Jing Zhang,&nbsp;Lingfeng Li,&nbsp;Yiming Zhang","doi":"10.1155/atr/9485040","DOIUrl":"https://doi.org/10.1155/atr/9485040","url":null,"abstract":"<p>One important determinant of the safety and load-bearing ability of the disposal area at an open-pit coal mine’s external dumping site is the foundation’s bearing capacity. For open-pit coal mines to operate effectively, this capacity must be calculated precisely. The Terzaghi’s bearing capacity theory is frequently employed for these computations because there is currently no recognized, trustworthy technique for figuring out the foundation’s ultimate bearing capacity at the disposal site. This gap can be filled by developing a new method that takes into account the inclination limit of the inclined strip and the various parameters of the dumping site. The inclined strip method, derived from the sloping strip approach proposed by Donald and Chen within the upper bound limit analysis framework, is employed to consider the effect of foundation inclination. The Black Mountain open-pit mine in Xinjiang was used as a case study for this approach. The findings show that, in comparison to the study’s methodology, the Terzaghi’s bearing capacity theory predicts the upper limit of the inclined strip with a more conservative estimate. The reliability of this method was also confirmed using FLAC3D, a software for finite difference analysis. The final bearing capacity estimates agreed with the P–S curves derived from monitoring sites, and numerical simulations of the critical slip surface and foundation stability produced findings in line with the inclined strip upper limit approach. These results demonstrate how changes in the top slope length (L) affect the foundation’s final bearing capacity and validate the viability of the suggested approach.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/9485040","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148086370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Driving Behavior Dynamics Following C-ITS Adoption: A Multiyear Analysis From South Korea","authors":"Junhee Kang,&nbsp;Sehyun Tak,&nbsp;Sungjin Park","doi":"10.1155/atr/8810507","DOIUrl":"https://doi.org/10.1155/atr/8810507","url":null,"abstract":"<p>The Cooperative Intelligent Transport System (C-ITS) provides an innovative platform for real-time interaction among vehicles, infrastructure, and road users, promoting a safer and more efficient transportation environment. This study aims to evaluate the impact of C-ITS services on driving behavior, with a particular focus on safety. To assess changes in the driving behavior of C-ITS users, a two-step analysis was conducted using Probe Vehicle Data (PVD) collected over 4 years following the launch of the Daejeon–Sejong C-ITS pilot project in South Korea. In the first phase, C-ITS service users were categorized based on their monthly usage patterns through self-organizing map (SOM) clustering. This analysis identified two groups of adopters who continued using the C-ITS service through the fourth year and two groups of abandoners who gradually disengaged. In the second phase, the driving behavior of these groups was compared using the Mann–Kendall Trend (MKT) test to examine potential differences in four driving-related indicators: average speed, hard braking rate, speeding rate, and excessive speeding rate. The results reveal that C-ITS adopters generally maintain lower average speeds, hard braking rates, speeding rates, and excessive speeding rates compared to abandoners. These findings suggest that assuming other factors are constant, regular and active engagement with the C-ITS service may lead to safer driving behavior. The MKT tests further highlight statistically significant differences in trends between the short term (1 year) and medium term (4 years), indicating that C-ITS users may gradually adapt to risk warnings, stabilizing their driving behavior into safer patterns over time.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/8810507","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148084487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Rethinking Railway Station Design: A Hybrid Simulation–Optimization Approach to Planning Service Point Layouts","authors":"Seyed Mohsen Mahmoudi,&nbsp;Navid Khademi,&nbsp;Arian Behmanesh,&nbsp;Morteza Bagheri","doi":"10.1155/atr/9606161","DOIUrl":"https://doi.org/10.1155/atr/9606161","url":null,"abstract":"<p>The strategic layout of service points in railway stations plays a crucial role in minimizing interstation travel time, improving passenger convenience, and enhancing overall operational efficiency. Despite valuable prior research, existing studies often assume uniform service point dimensions and rigid facility locations, leading to suboptimal space utilization. Additionally, most research relies on static user flow assumptions derived from limited observational data, failing to capture the complexity and unpredictability of passenger movement in high-traffic environments. This study addresses these gaps by introducing a flexible service point layout optimization model tailored for railway stations. The proposed model incorporates a block-based layout system, enabling dynamic allocation of facilities of varying sizes and an advanced simulation framework that analyzes passenger flows. These advancements provide a more comprehensive and accurate understanding of passenger behavior, allowing for more effective layout decisions. A hybrid simulation–optimization approach was employed, integrating real-world passenger behavior data from Tehran Railway Station with PTV Viswalk pedestrian simulation software. Data were collected over 33 days from 39 CCTV cameras, analyzing 2219 passenger movements during a peak hour. Two simulation approaches were utilized: same-as-observation and rule-based modeling, with optimization conducted using genetic algorithm and ant colony optimization. Results indicate that the optimized layout reduces interstation travel time by 18% and decreases flow rates between station sections by 15%, significantly improving accessibility and station efficiency. The findings demonstrate the model’s applicability for optimizing public transit hubs though regular data updates are necessary for maintaining accuracy. Future research should incorporate broader data sources, account for dynamic passenger behaviors, and develop multiobjective optimization frameworks to enhance the applicability of the proposed model.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/9606161","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148082096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"CITMR: Contrastive Image–Text–Motion Retrieval for Autonomous Driving Critical Scenarios Extraction","authors":"Kun Peng,&nbsp;Shanke Li,&nbsp;Fei Hui,&nbsp;Xiyao Liu","doi":"10.1155/atr/4985228","DOIUrl":"https://doi.org/10.1155/atr/4985228","url":null,"abstract":"<p>Extracting critical scenarios from the vast and complex driving environments is a crucial step in the iterative upgrade process of autonomous driving systems. Existing image–text-based retrieval methods provide a good understanding of the environment but overlook the critical information regarding the impact of the environment on the self-vehicle. To address these issues, we propose a contrastive image–text–motion retrieval (CITMR) cross-modal learning framework that uses descriptive text as input to retrieve critical scenarios. The framework employs image, text, and motion encoders to extract features from different modalities and uses contrastive loss to enable cross-modal information comparison and interaction. Finally, the vehicle’s motion and its textual description are supplemented in the collected autonomous driving dataset, and a scenario dataset containing image–text–motion pairs is constructed for model validation. Experimental results show that CITMR achieves retrieval performance for text-critical scenarios of 0.8684 and 0.8557 on two test datasets, outperforming the baseline methods.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/4985228","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148076257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Machine Learning Approach for Forecasting Rail Degradation in Railway Systems","authors":"Gledson Fábio Cotrim Rocha,&nbsp;Rodrigo de Alvarenga Rosa,&nbsp;Hendrigo Venes,&nbsp;Bruna dos Santos Neves","doi":"10.1155/atr/1649467","DOIUrl":"https://doi.org/10.1155/atr/1649467","url":null,"abstract":"<p>In railway systems, the contact between rolling stock wheels and rails causes continuous wear, requiring periodic rail replacement to ensure operational safety and reliability. Traditional methods to estimate rail lifetime often fail to account for the specific conditions of each railway, leading to inaccurate forecasts. This paper proposes a method based on machine-learning algorithms to estimate the remaining lifetime of rails using historical data from the railway itself. The proposed approach was applied to the Vitória-Minas Railway (EFVM), in Brazil, using a dataset collected over 6 years and 8 months, totaling 1,275,034 records. Two algorithms were evaluated: artificial neural networks (ANN), with 54 configurations tested, and K-nearest neighbors (k-NN), with 12 configurations. The models were trained and validated with 1,100,000 records and tested with 175,034 records. Four categories were defined for rail lifetime estimation: month, quarter, semester, and year. Results showed that k-NN outperformed ANN in all tested configurations, reaching Accuracy and F1-score values up to 0.97427 and 0.97329, respectively. These findings confirm the potential of data-driven models for supporting maintenance planning in railways.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/1649467","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148076261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}