IET Intelligent Transport Systems最新文献

{"title":"Trajectory Pattern Recognition in a Multi-Airport Systems Based on a New 3D Multi-Feature Trajectory Compression","authors":"Ligang Yuan,&nbsp;Wenlu Chen,&nbsp;Haiyan Chen,&nbsp;Bin Wang,&nbsp;Xinding Zhou","doi":"10.1049/itr2.70097","DOIUrl":"https://doi.org/10.1049/itr2.70097","url":null,"abstract":"<p>With the rapid development of the global aviation industry, multi-airport systems have emerged as a critical component of large urban clusters and regional aviation networks. However, the complexity and uncertainty of air traffic flows in such systems are significantly increased by factors such as weather conditions, emergencies and the intricate interplay of arrival and departure routes across multiple airports, compounded by the complex structure of airspace. To address the challenges posed by the complex and dynamic air traffic flows within multi-airport systems, in this paper, we have introduced a trajectory recognition method based on a new 3D multi-feature trajectory compression (3D-MFTC) representation and clustering. First, a grid sparsity-based approach is proposed to detect and remove abnormal trajectories in multi-airport systems. Then, a novel 3D-MFTC is developed, which employs normalised Euclidean distance to compress 3D trajectory data and adjusts trajectory feature points based on a normal distribution. Then the fast-DTW algorithm is applied to calculate the trajectory similarity of the compressed data. Finally, DBSCAN is utilised to cluster the trajectory within the multi-airport system, with the optimal parameter combinations determined through K-distance graph analysis and grid search. Experimental results demonstrate that the proposed method significantly enhances the accuracy of trajectory similarity computation, enables fine-grained identification of trajectory patterns in multi-airport systems and outperforms traditional clustering algorithms in terms of both clustering performance and visualisation quality.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70097","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271959","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 Decentralised Braking Force Distribution Strategy for High-Speed Trains","authors":"Jiuhe Wang,&nbsp;Zhiyong Chen,&nbsp;Zhiwen Chen,&nbsp;Weihua Gui","doi":"10.1049/itr2.70100","DOIUrl":"https://doi.org/10.1049/itr2.70100","url":null,"abstract":"<p>Braking force distribution (BFD) among motor and trailer carriages is essential for guaranteeing braking performance and safety in high-speed trains. A centralised BFD strategy is widely used in modern rail transportation, relying on real-time data transmission among carriages over a communication network. This paper presents a decentralised BFD strategy that eliminates the reliance on communication, thereby reducing the associated costs and complexity, while maintaining the same braking performance with more flexibility. The new strategy is built on two novel ideas: each carriage locally estimates its required braking force using coupler force measurements, and distribution of the calculated braking forces obeying a priority rule is realised by delayed implementation in different levels. The proposed scheme is validated on a hardware-in-the-loop platform and tested under both normal and abnormal scenarios. Results show that the decentralised implementation of the two new ideas achieves electric braking utilisation rates above 99.3% across all cases. Without inter-vehicle communication, the decentralised scheme incurs only a modest tracking error increase (maximum 0.88 km/h), while adhesion utilisation stays within a 3% margin. This means that the proposed method effectively balances performance, communication cost and force prioritisation, thereby offering a robust and practical alternative to centralised framework.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70100","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271965","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 Comparative Study of Non-Linear Car Following Models in Real-Driving Scenarios","authors":"Ranganatha Belagumba Ramachandra,&nbsp;Bidisha Ghosh,&nbsp;Vikram Pakrashi,&nbsp;Salissou Moutari,&nbsp;Timilehin Opeyemi Alakoya","doi":"10.1049/itr2.70098","DOIUrl":"https://doi.org/10.1049/itr2.70098","url":null,"abstract":"<p>Car following models (CFMs) are the most prominent microscopic traffic flow models that capture the follower behaviour through detailed representation of leader–follower interactions. Models vary in their interaction logic, but it is generally assumed that all established models can produce realistic vehicle responses under real-world driving conditions. In this study, the efficacy of three well-established CFMs—nonlinear Newell model, the Optimal Velocity Model (OVM), and the intelligent driver model is evaluated in real driving conditions represented by Worldwide harmonized light vehicle testing cycles (WLTC). The choice of leader vehicle profile such as WLTC, captures speed variations corresponding to driving conditions such as rural, urban and highway. The model responses to WLTC were investigated for extreme behaviour analysis, characterized by high acceleration or jerk values. Model robustness is compared using nominal range sensitivity analysis and the response surface method, yielding insights into reducing model complexity during calibration exercises. The results reveal OVM to be the least robust model of the three. The findings highlight unphysical and unrealistic model outputs, offering critical insights to inform model selection and guide improvements for more accurate and reliable microscopic traffic simulations.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70098","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271958","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":"Optimisation of Demand-Oriented Train Timetabling With Integrated Skip-Stopping and Passenger Routing Considering Multi-Speed Types","authors":"Hui Liang,&nbsp;Yun Jing,&nbsp;Ziwen Jiang","doi":"10.1049/itr2.70092","DOIUrl":"https://doi.org/10.1049/itr2.70092","url":null,"abstract":"<p>Designing train timetables that meet passenger demand is of significant importance to railway operators. Considering the coupled relationship between train timetable, train stop planning and passenger routing, this paper investigates the integrated optimisation problem of the three under demand-driven conditions. Specifically, we firstly consider two speed types of trains, design a multi-layer space-time network with train and passenger layers and construct an integer linear programming (ILP) model aimed at minimising the total passenger travel cost. Based on the characteristics of the model, Lagrangian relaxation (LR) is applied to decompose the train safety constraints and train capacity constraints. Finally, the effectiveness of the model and algorithm was validated through an experiment on the Wuhan-Guangzhou South High-Speed Railway (HSR) in China, and the impact of ticket price on passenger routing was analysed.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145224321","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 Dynamic Emergency Lane Clearing Method for Urban Roads Considering Vehicle Turning Information in a Connected Vehicle Environment","authors":"Tingting Zhu,&nbsp;Zhengwu Wang,&nbsp;Kejun Long","doi":"10.1049/itr2.70096","DOIUrl":"https://doi.org/10.1049/itr2.70096","url":null,"abstract":"<p>In complex urban traffic environments, the timely passage of emergency vehicles (EVs) is a significant challenge, often hindered by traffic congestion and insufficient coordination among road users. Enhancing emergency response capabilities is crucial for safeguarding lives and property. With advances in automated driving technologies, connected vehicles (CVs) are expected to cooperate to reduce congestion and ensure prioritized EV passage on urban roads. This study proposes a real-time dynamic emergency lane clearing method for CV environments. A bi-level optimization model is developed for segmented road sections. The lower-level model employs an improved A* algorithm that incorporates vehicle turning information to generate optimal lane-changing trajectories for normal vehicles in the shortest possible time, aiming to minimize their lane-changing costs. The upper-level model is formulated as a mixed-integer nonlinear programming (MINP) problem to determine the optimal trigger points for segmented clearance. By triggering lane clearance in a stepwise manner, the model aims to minimize EV interference and maintain its desired speed. Numerical experiments show that the proposed method significantly reduces deceleration delay by 50% and the number of affected vehicles by 45% compared to traditional strategies. Sensitivity analyses further demonstrate its adaptability to varying road saturation levels and segment lengths, highlighting its potential for real-world deployment in CV-enabled urban environments.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70096","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146531","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":"Performance Criteria Assessment of Marine Radionavigation Systems Reliability Under Degradation Factors","authors":"Oleksiy Melnyk,&nbsp;Svitlana Onyshchenko,&nbsp;Iryna Savieleva,&nbsp;Kostyantin Koryakin,&nbsp;Aditya Rio Prabowo,&nbsp;Martin Jurkovič,&nbsp;Vyacheslav Sapiha","doi":"10.1049/itr2.70094","DOIUrl":"https://doi.org/10.1049/itr2.70094","url":null,"abstract":"<p>The article examines the assessment of the reliability of shipboard radio navigation systems under the influence of degradation factors, with a focus on the impact of both gradual and sudden failures on the continuity of navigation equipment. A classification of failures is presented, environmental and operational factors affecting the efficiency of systems are identified, and the risk of failure is quantified using mathematical modelling. A combined approach to reliability assessment is proposed, which takes into account the probability of failures due to ageing (gradual failures) and external influences (sudden failures), based on an exponential distribution model. An analysis of the mean time between failures (MTBF) of key radio navigation systems was carried out, the probability of failure of at least one element during an operational period of up to 350 days was estimated, and a conceptual model for optimising maintenance was formed. Methodologically, the study is based on the development of a two-factor model that combines the assessment of gradual and sudden failures of shipboard radio navigation systems. To quantify the intensity of failures, an exponential distribution law is used with the integration of correction factors that take into account the influence of the environment and the human factor. The MTBF is calculated taking into account both types of failures, which ensures the complexity of the assessment. The results are supported by tables, graphs and theoretical generalisations that form a reliable basis for improving the fault tolerance of modern marine navigation systems.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146558","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":"China-Europe Railway Express Freight Volume Forecasting With a Novel SARIMAX-BNN Model","authors":"Rong Zhang,&nbsp;Minshan Zhao","doi":"10.1049/itr2.70095","DOIUrl":"10.1049/itr2.70095","url":null,"abstract":"<p>This study proposes a hybrid SARIMAX-BNN model to forecast China-Europe Railway Express (CR Express) freight volume, addressing challenges such as nonlinearity, temporal dependence, and high volatility. Spearman rank correlation is used to select key influencing factors to optimise SARIMAX inputs. The SARIMAX model captures trend and residuals, while the BNN learns nonlinear residual patterns. Final predictions are obtained by combining both models. Using annual and monthly freight data from Xi'an CR Express, the proposed model achieves an MAE of 0.16 (10k tonnes) and a MAPE of 0.90% on the annual dataset and an MAE of 14.53 TEU with a MAPE of 0.05% on the monthly dataset, outperforming all baseline methods. This approach improves forecasting accuracy and supports better operational decisions.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70095","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129359","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":"Understanding User Behaviour and Predicting Charging Costs: A Machine Learning Approach to Support Electric Vehicle Adoption Decisions","authors":"Muhammed Cavus,&nbsp;Huseyin Ayan,&nbsp;Margaret Bell,&nbsp;Dilum Dissanayake","doi":"10.1049/itr2.70088","DOIUrl":"10.1049/itr2.70088","url":null,"abstract":"<p>The increasing adoption of electric vehicles (EVs) necessitates a comprehensive understanding of charging patterns and user behaviour to enable future transportation infrastructure to be planned and designed to meet user needs. This study uses machine learning to predict the costs of EV charging sessions and analyse user behaviour to support strategic planning and decision-making. We examined data that included factors such as total energy consumption and charging duration, and compared three models: linear regression, random forest, and gradient boosting. The gradient boosting model performed the best, with a mean squared error of 0.041 and an <span></span><math>\u0000 <semantics>\u0000 <mi>R</mi>\u0000 <annotation>$R$</annotation>\u0000 </semantics></math>-squared (<span></span><math>\u0000 <semantics>\u0000 <msup>\u0000 <mi>R</mi>\u0000 <mn>2</mn>\u0000 </msup>\u0000 <annotation>$R^2$</annotation>\u0000 </semantics></math>) of 0.91. Additionally, the analysis of user behaviour revealed peak charging times between 6:00 PM (18:00) and 9:00 PM (21:00), with the majority of sessions occurring on weekdays, particularly Wednesdays. Most users preferred charging infrastructures within a 10-mile radius. These insights not only enhance the understanding of current EV charging behaviours but also provide valuable information for local authorities and decision-makers in transportation planning and infrastructure development. By integrating predictive modelling and behavioural analysis, this research offers a novel and robust framework for designing EV charging networks, addressing user needs, and advancing the sustainability of urban transportation systems. This approach not only supports the efficient deployment of charging infrastructures but also introduces the concept of charging comfort by aligning infrastructure development with real user needs. Unlike traditional methods that overlook user preferences and waiting times, our model integrates behavioural analysis to improve the overall user experience. By quantifying when, where, and how users prefer to charge their vehicles, this framework supports not only infrastructure optimisation but also enhances user satisfaction, a key factor in accelerating EV adoption and reducing the environmental burden of urban mobility.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70088","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101671","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":"An Optimal Energy-Saving Coordination Control System for Sail-Propeller of Wind-Assisted Ships","authors":"Jian Song,&nbsp;Yinchao Tan,&nbsp;Lanyong Zhang,&nbsp;Sheng Liu","doi":"10.1049/itr2.70090","DOIUrl":"10.1049/itr2.70090","url":null,"abstract":"<p>Wind-assisted ship propulsion technology has been regarded as a promising sustainable development solution. Wind-assisted ships generate navigation thrust by driving sails and propellers. This study proposes an optimal energy-saving control system for coordinating sail thrust and propeller thrust, achieved by regulating sail azimuth and propeller speed. A coordination control algorithm based on the model predictive control-adaptive Pontryagin minimum principle (MPC-APMP) is proposed. This algorithm transforms the optimal control problem for enhancing sail and propeller energy efficiency into a rolling optimisation problem of MPC framework. Firstly, considering the system's delay relative to time-varying environment and speed requirements, a wind direction/wind speed/ship speed prediction model based on a long short-term memory neural network is designed. According to the sail aerodynamics and the propeller hydrodynamics, a dynamic model of sail-propeller combined propulsion is established and used to evaluate potential wind energy and the overall thrust demand. The reference trajectory of battery power is determined using the established energy consumption model. Finally, the PMP algorithm is applied to derive the optimal control sequence. A co-state variable adaptive law is designed to address model parameter uncertainties. The energy-saving efficiency and stability of the proposed method are validated through simulations and a principle prototype.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70090","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101672","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":"The Joint Impact of Traffic Signal Control and Automated Vehicles on Traffic Efficiency, Safety and Emissions: A Deep Reinforcement Learning Approach","authors":"Amir Hossein Karbasi,&nbsp;Hao Yang","doi":"10.1049/itr2.70087","DOIUrl":"10.1049/itr2.70087","url":null,"abstract":"<p>Recent developments in intelligent transportation systems underscore the promise of combining deep reinforcement learning (DRL)-based traffic signal control (TSC) with automated vehicles (AVs) to improve intersection management. This study analyses how integrating DRL-based TSC systems with AVs affects traffic efficiency, safety and emissions under varying demand levels. By simulating realistic driving behaviours and using sophisticated statistical methods, the research finds that DRL-based TSC significantly outperforms traditional fixed-time and actuated systems, effectively reducing congestion, emissions and conflicts. Queue length analyses reveal that DRL-based TSC provides substantial efficiency gains, further enhanced by AVs, which reduce congestion through improved driving automation. Notably, the short-term benefits of DRL-based TSC at low AV market penetration rates resemble the long-term effects of conventional systems at high AV adoption. While fuel consumption improvements under low demand are modest compared to other adaptive systems, high-demand scenarios show significant advantages of DRL-based TSC, with AV integration further optimising flow and reducing stop-and-go patterns. Safety analysis indicates that DRL-based TSC improves intersection safety, particularly at low AV penetration, with AVs dramatically reducing conflicts. Overall, combining DRL-based TSC with AV technology holds considerable potential for advancing traffic management, safety and environmental outcomes in urban settings.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102020","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}