Journal of Advanced Transportation最新文献

{"title":"Dual-Mode Adaptive Control With Entropy-Triggered Reactivation for Heavy-Haul Trains","authors":"Zhao Sheng,&nbsp;Kexing Yan,&nbsp;Zhipeng Zhao,&nbsp;Shigen Gao","doi":"10.1155/atr/5317987","DOIUrl":"https://doi.org/10.1155/atr/5317987","url":null,"abstract":"<p>This paper addresses the tracking control problem for automatic train operation of heavy-haul trains (HHTs) under uncertain operating environments. To mitigate the limitations of conventional simplified modeling and the high computational burden from continuous adaptation, this work presents an integrated control framework with three synergistic advancements. First, a refined longitudinal dynamical model is constructed that differentiates four subunit types, i.e., leading locomotive, inner locomotive, rear locomotive, and inner wagons, with explicit bounded coupler-deformation constraints. By capturing practical compressive–tensile characteristics and locomotive–wagon dynamic interactions, the model delivers more realistic HHT dynamic descriptions and lays a reliable basis for subsequent controller synthesis. Second, a dual-mode adaptive controller is developed to jointly improve adaptability and computational efficiency. Under satisfied triggering conditions, adaptive parameters can be frozen and reused; adaptation is reactivated once performance degradation is perceived, enabling robust and economical operation for varied uncertain scenarios. Third, a sliding-window entropy-triggered reactivation function (ETRF) is proposed to supervise the transitions between stationary and nonstationary adaptive modes. The ETRF comprehensively evaluates speed-tracking errors, mileage errors, and parameter convergence states and embeds a minimum dwell-time constraint to suppress chattering and ensure stable mode transitions. Simulation studies validate the overall effectiveness and practical merits of the proposed integrated scheme for HHT control.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/5317987","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149206003","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":"Design of Multimodal Signal Progression Along an Arterial With Bus Dedicated Lanes","authors":"Hyeonmi Kim,&nbsp;Yao Cheng,&nbsp;Gang-Len Chang,&nbsp;Kyeong-Pyo Kang","doi":"10.1155/atr/2060215","DOIUrl":"https://doi.org/10.1155/atr/2060215","url":null,"abstract":"<p>Despite the increasing deployment of bus dedicated lanes in practice, commonly available programs for arterial signal plans are not designed to provide concurrent progression for such bus flows and general traffic. This study presents a bandwidth maximization model for traffic engineers to design both the phase sequences and offsets over a series of intersections along an arterial with bus dedicated lanes. The proposed model, offering concurrent progression to both modes based on traffic volumes and geometric conditions, has considered the following factors: bus dwelling times, location of bus dedicated lanes, traffic queues, and conflicts between the through bus movements and left-turning traffic. In addition, by weighing the bandwidths with the passenger volumes by mode and by direction, the proposed model offers progression to the mode(s) and the direction(s) for which it is justified from the perspective of maximizing the benefits to all arterial users. The results from numerical analysis with actual arterial and field data have confirmed the effectiveness of the proposed model in producing concurrent progression bands for both modes under various realistic constraints. Given reliable information for key input variables, the proposed model can serve as an effective tool for traffic professionals to do the essential design task.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/2060215","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205592","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":"Autonomous Ride-Hailing Adoption in a Pilot City: A Benefit–Risk Framework With Structural Equation Modeling and Machine Learning","authors":"Ruiwei Li,&nbsp;Ying Huang,&nbsp;Ruibo Xie","doi":"10.1155/atr/1715189","DOIUrl":"https://doi.org/10.1155/atr/1715189","url":null,"abstract":"<p>Autonomous ride-hailing (ARH) is moving from trials to pilot deployments, yet conversion from awareness to actual use remains limited. We surveyed <i>N</i> = 500 aware nonusers in Guangzhou’s Nansha pilot area to examine initial adoption intention under real service availability. An integrated benefit–risk framework combining technology acceptance model (TAM) constructs with risk perception was tested via structural equation modeling (SEM) and evaluated with machine learning (ML) prediction. SEM showed perceived usefulness as the strongest positive driver of attitude (<i>β</i> = 0.514), while risk perception exerted large negative effects on attitude (<i>β</i> = −0.409) and intention (<i>β</i> = −0.339). The model explained 74.9% of the variance in attitude and 76.1% of the variance in initial adoption intention. ML using gradient boosting achieved AUC = 0.874 with balanced precision/recall, supporting practical segmentation of high-potential users. Exploratory piecewise analyses suggested potential thresholds (usefulness &gt; 4.0; risk &gt; 2.2 on 5-point scales), indicating nonlinear acceptance dynamics; these patterns are treated as hypothesis-generating. Findings highlight that successful ARH deployment requires simultaneous benefit enhancement (use-case clarity and service integration) and proactive risk mitigation (safety transparency and privacy assurance).</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/1715189","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146001","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":"Short-Term Traffic Flow Simulation at Adjacent Intersections Under the Influence of Autonomous Vehicles","authors":"Mohammad Iman Sharifi,&nbsp;Hamid Mirzahossein,&nbsp;Amir Abbas Rassafi,&nbsp;Seyed Mohsen Hosseinian","doi":"10.1155/atr/8048267","DOIUrl":"https://doi.org/10.1155/atr/8048267","url":null,"abstract":"<p>With the increasing number of autonomous vehicles (AVs), short-term traffic flow prediction plays a crucial role in reducing road congestion and enhancing traffic management efficiency. In previous studies, the main focus was on modeling traffic flows at intersections and highways. However, limited research has been conducted on the impact of AVs on design speed, lane change, and longitudinal and lateral distances at adjacent intersections, particularly in the context of metropolises, where traffic conditions are complex and heterogeneous. The aim of this research is to control the speed, distances, and overtaking operations of AVs and then simulate the short-term traffic flow at the adjacent smart intersections in Tehran, Iran. For this purpose, first, the AV design speed for each of the intersections was evaluated based on the analytical method and coding in Python software. Then, the maneuver conditions, lane change, and longitudinal and lateral distances of the AV for each of the intersections were examined using the Krauss car-following model. Finally, the results were evaluated using the support vector machine (SVM) method, and the parameters of accuracy, sensitivity, precision, and F1 score were determined. In the results, the AV design speed and the longitudinal and lateral distances for the AV’s maneuver were determined for all intersections. In addition, the results of the SVM method showed that the calculated design speed, longitudinal and lateral distances, and lane change maneuvers of AV for the intersections under study were appropriate. These findings demonstrate the potential of the proposed framework to enhance the modeling of AV behavior at intersections, offering a foundation for more reliable traffic management and safety analysis.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/8048267","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146721","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":"Multiobjective Transit-Oriented Multimodal Network Design Incorporating Parking Fees","authors":"Tygo Nijsten,&nbsp;Jan-Pieter Dorsman,&nbsp;Michel Mandjes,&nbsp;Erwin Walraven,&nbsp;Maaike Snelder","doi":"10.1155/atr/1311015","DOIUrl":"https://doi.org/10.1155/atr/1311015","url":null,"abstract":"<p>High car usage in urban areas leads to congestion, pollution, and other negative externalities. While both “carrot” measures (enhancing more sustainable modes of transport) and “stick” measures (discouraging car use) are recognized as essential for sustainable mobility, their combined optimization remains underexplored. This study introduces the Transit Network Design, Frequency, and Parking Setting Problem (TNDFPSP), a novel multiobjective framework that jointly optimizes transit routes, service frequencies, and parking fees in a bimodal context. The optimization problem targets three objectives: minimizing generalized user costs, car usage, and operator deficit, enabling a systematic analysis of trade-offs between user, environmental, and operational goals. We propose an evolutionary algorithm tailored to this problem and evaluate candidate solutions using a multimodal traffic assignment model that explicitly captures car–transit interactions, including parking fees and search times. Experiments on Mandl’s benchmark network show that incorporating parking fees alongside frequencies not only improves all objectives but also enables better trade-off analysis for policy design. As an illustrative estimate based on modal passenger-kilometers, the resulting solutions are associated with an approximately 3.4% lower CO₂ footprint compared to the baseline TNDP, whereas optimizing transit routes and frequencies alone yields only marginal changes. These findings highlight the potential added value of integrated carrot-and-stick strategies for sustainable urban transport planning.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/1311015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146763","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":"Tourist Route Planning in Urban Road Networks: A Systematic Review of Optimisation Models and Data Integration","authors":"Phan Gia Bao Le,&nbsp;Sara Moridpour,&nbsp;Minh Ngoc Dinh","doi":"10.1155/atr/8706872","DOIUrl":"https://doi.org/10.1155/atr/8706872","url":null,"abstract":"<p>Tourist route optimisation in dense urban environments presents a complex multiobjective challenge that requires balancing logistical efficiency with experiential satisfaction. This paper presents a systematic review of model-based approaches for urban tourist route planning, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (<i>n</i> = 81). The study develops a novel engineering-oriented taxonomy categorising optimisation methodologies into mathematical programming, metaheuristics, and machine learning. Unlike existing reviews that primarily adopt a management or recommender-system perspective, this taxonomy highlights a paradigm shift toward hybrid frameworks designed for dynamic adaptability. The review also systematically analyses the integration of heterogeneous data sources from explicit tourist preferences to implicit spatiotemporal traces and Geographic Information System (GIS) infrastructure, highlighting their critical role in parameterising objective functions. A comparative evaluation identifies the distinct conflicting objectives including maximising attractiveness (utility), ensuring feasibility (cost/time) and enhancing resilience (safety). Despite theoretical advancements, results indicate a critical gap between simulation and real-world deployment, with limited experimental validation in dynamic settings. The paper concludes by providing actionable managerial implications and outlining a future research agenda, such as urban digital twin integration, Pareto-based multiobjective decision support and adaptive routing systems that remain robust under stochastic urban conditions.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/8706872","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048206","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":"Individual Movement Prediction Using Long-Term Smart Card Data: A Bayesian Method Considering Spatiotemporal Correlation","authors":"Qiong Chen,&nbsp;Tong Zhang,&nbsp;Qi Dai,&nbsp;Dawei Li,&nbsp;Xiaomeng Shi","doi":"10.1155/atr/6258858","DOIUrl":"https://doi.org/10.1155/atr/6258858","url":null,"abstract":"<p>Individual mobility prediction is essential for understanding human travel patterns and optimizing transportation resource allocation. However, most methods focus on single-dimensional spatial prediction or short-term next-step tasks, struggling to sufficiently account for spatiotemporal correlations or provide the flexibility needed for long-term planning on arbitrary future dates. To address these limitations, this paper proposes a peak-hour individual mobility prediction framework integrating a passenger segmentation model with Bayesian methods. Using 1-year long-term smart card data from Kunshan City, the framework first identifies a core group of high-frequency and stable users through clustering, which mitigates random noise and enhances prediction robustness. Subsequently, probabilistic models (including bigram, trigram, and Bayesian networks) are developed to accurately capture the probabilistic dependencies among travel dates, departure times, transit lines, and stations. Experimental results demonstrate that the Bayesian network model significantly outperforms traditional machine learning models and other Bayesian variants in both temporal and spatial dimensions. Notably, the proposed model does not require the prediction day to be adjacent to the historical sequences, and no external features are required. This research not only provides personalized travel recommendations at the microlevel but also offers decision-making support for the macrolevel spatiotemporal management of public transit networks, such as predicting congestion periods and passenger flow distribution at stations.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/6258858","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048205","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":"Technological Architecture of Aerial Mobility Innovation: A Patent-Based Network, Text-Mining, and Multicriteria Evaluation Approach","authors":"Mohammad Sabet,&nbsp;Adel Aazami,&nbsp;Sebastian Kummer,&nbsp;Navid Mohammadi","doi":"10.1155/atr/1415764","DOIUrl":"https://doi.org/10.1155/atr/1415764","url":null,"abstract":"<p>This study presents an integrated assessment of technological development in the aerial mobility innovation ecosystem, combining network analysis, patent clustering, and a multicriteria strategic evaluation model. The empirical corpus centers on unmanned aerial vehicle (UAV) logistics, unmanned aircraft system (UAS) applications, urban air mobility (UAM) platforms, and the avionics, sensing, communication, and materials technologies that enable supply-chain-oriented aerial operations, rather than commercial passenger air transport. Patent data sourced from Lens.org were analyzed using Gephi, revealing a highly modular applicant collaboration network shaped by five dominant communities centered around Huawei, Apple, Qualcomm, NVIDIA, and UATC. These applicant communities form structurally cohesive ecosystems that anchor major technological directions within the field. To uncover the thematic organization of innovation, text clustering of patent abstracts identified five coherent technological clusters: data and sensing layer, platform design and manufacturing, network infrastructure and communication, agrotech applications, and materials and component innovation. Together, these clusters represent the core thematic architecture of aerial mobility, capturing the interplay between perception technologies, engineering design, communication infrastructures, domain-specific applications, and advancements in materials and components. A subsequent TOPSIS-based strategic evaluation reveals that the data and sensing layer, materials and component innovation, and network infrastructure and communication clusters possess the highest strategic potential based on their citation influence, cross-domain relevance, and integration across applicant communities. Overall, the findings show that aerial mobility innovation emerges through the interaction of five structurally dominant applicant collaboration communities and five thematically distinct technological clusters, offering a comprehensive understanding of how technological trajectories evolve. The proposed integrated framework offers a replicable patent-based prioritization signal that can inform preliminary research scanning, monitoring, and agenda-setting in this rapidly progressing technological domain, without substituting for market, regulatory, or operational assessment.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/1415764","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149047994","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":"Correction to “Waiting Behavior and Arousal in Different Levels of Crowd Density: A Psychological Experiment with a “Tiny Box””","authors":"","doi":"10.1155/atr/9875126","DOIUrl":"https://doi.org/10.1155/atr/9875126","url":null,"abstract":"<p>M. Beerman and A. Sieben, “Waiting Behavior and Arousal in Different Levels of Crowd Density: A Psychological Experiment with a “Tiny Box”,” <i>Journal of Advanced Transportation</i>, vol. 2022 (2022). https://doi.org/10.1155/2022/7245301.</p><p>In the article titled “Waiting Behavior and Arousal in Different Levels of Crowd Density: A Psychological Experiment with a “Tiny Box”,” there was an error in Table 2. Specifically, the columns representing the mean scores of the participants in the two rightmost columns were inadvertently swapped. The error was introduced by the authors during manuscript preparation, and Table 2 should be corrected as follows:</p><p>We apologize for these errors.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/9875126","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149047952","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":"Decision on Booking Requests in Ticket-Unavailable Sections: A Ticket Allocation Optimization Approach Considering Stochastic Demand in High-Speed Railway","authors":"Yu Wang,&nbsp;Lingyun Meng,&nbsp;Lingjiangfei Wu,&nbsp;Jiafa Zhu","doi":"10.1155/atr/7054589","DOIUrl":"https://doi.org/10.1155/atr/7054589","url":null,"abstract":"<p>China Railway captures the excess demand through an intelligent online ticketing system where passengers could submit ticket booking requests in ticket-unavailable sections and decides to provide available tickets to fulfill the booking requests through splitting long distance tickets. As a result, a sequential ticket allocation optimization approach is proposed based on the booking-order-driven model to maximize the expected revenue. This approach integrates the access of passengers to the ticketing website based on Pascal probability distribution with multinomial-logit-based (MNL-based) passenger choices to support the company’s data-driven decision. Passengers choose trains according to the MNL model based on the random utility maximization, thereby distributing the passenger flow among different trains between the same OD section. Finally, a multidimensional 0–1 integer programming model is established to ensure dynamic revenue optimization at any given time point during presale period. A numerical study on the Beijing–Jinan high-speed railway corridor is performed to validate the effectiveness of the approach in meeting the excess demand and improving the revenue in the large-scale operational scenarios of multiple trains with multiple stops.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/7054589","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148994275","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}