IET Intelligent Transport Systems最新文献

{"title":"A MILP Model and Two-Stage Heuristic Algorithm for Vehicle-Assisted Multi-Drone Inspection Routing Problem","authors":"Yuanqing Xia,&nbsp;He Luo,&nbsp;Rui Dong,&nbsp;Youlong Yin,&nbsp;Shizhong Lin,&nbsp;Guoqiang Wang","doi":"10.1049/itr2.70028","DOIUrl":"10.1049/itr2.70028","url":null,"abstract":"<p>This paper introduces a vehicle-assisted multi-drone inspection routing problem (VAMDIRP), which enables the vehicle to repeatedly traverse roads, thereby reducing task completion time. Firstly, a mixed-integer linear programming (MILP) model is constructed for the problem using a series of decision variables and auxiliary variables. The model can be solved by GUROBI for small-scale instances. Secondly, a two-stage heuristic algorithm is proposed to solve large-scale instances. Experimental results show that this algorithm improves the solution quality by an average of 20.71% and reduces the running time by an average of 60.31% compared to existing algorithms. Finally, a sensitivity analysis is conducted on relevant parameters, revealing that changes in the number and speed of drones significantly affect the solution quality.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143831024","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":"Multimodal Gaidai State-of-the-Art Limit Hypersurface Methodology for Container Vessels With Multiple Failure Modes","authors":"Yan Zhu,&nbsp;Oleg Gaidai,&nbsp;Shicheng He,&nbsp;Jinlu Sheng,&nbsp;Ahmed Alaghbari,&nbsp;Antoine Dembadouno,&nbsp;Tanyaradzwa Kuzvidza","doi":"10.1049/itr2.70029","DOIUrl":"10.1049/itr2.70029","url":null,"abstract":"<p>This case study presents state-of-the-art, multimodal structural reliability and risk evaluation methodology, particularly suitable for naval architecture, transportation and marine engineering applications.</p><p>Existing reliability methods do not easily tackle systems with a number of critical components higher than 2, while the advocated multimodal reliability and risk evaluation methodology has no limitations on the system's number of dimensions, parts or components. The 4400 TEU container vessel's onboard measured deck panel stresses raw data, collected during numerous vessel's trans-Atlantic crossings, was analysed. Risk of ship hull and panel structural damage caused by excessive whipping (slamming and springing) wave loads, representing types of highly nonlinear wave-induced vibrations, are among primary safety concerns for the contemporary marine transportation industry. It is often challenging to accurately forecast excessive vessel's deck panel hot-spot stresses, possessing complex nonlinear, nonstationary properties. The proposed multimodal hypersurface reliability method fully accounts for a large number of structural components, as well as dynamic nonlinearities. Lab testing may often be disputed, as obtained measurements will depend on biased incident wave properties and model scales. As a result, the onboard dataset, obtained from a particular cargo ship, operating in the North Atlantic provides especially valuable insights into an overall dynamic vessel hull system's durability and reliability.</p><p>This investigation aimed at providing generic state-of-the-art reliability methodology, enabling accurate extraction of pertinent information about vessel hull system's dynamics, e.g., deck panel hot-spot stresses, derived from the onboard sensor-recorded time histories. Utilising proposed hypersurface reliability methodology, structural failure, hazard or damage risks may be effectively yet accurately forecasted, based on spatially distributed vessel deck panel stresses. The presented multimodal state-of-the-art reliability methodology may be particularly suitable for the evaluation of structural hazards of large dynamic systems, having virtually unlimited numbers of principal/key components. The presented study made use of the full scale onboard measured dataset, kindly provided by Det Norske Veritas, Oslo, Norway (DNV), which is commercially valuable on its own.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143831211","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":"Simulation-Based Optimization Method for Impact Evaluation to Work Zones in Large-Scale Networks","authors":"Chen Peng,&nbsp;Rongsheng Chen,&nbsp;Enjian Yao,&nbsp;Yang Yang,&nbsp;Yongyi Shang","doi":"10.1049/itr2.70015","DOIUrl":"10.1049/itr2.70015","url":null,"abstract":"<p>Work zones for road maintenance in traffic networks can significantly impact the traffic distribution and route choice behaviour of travellers. This study proposes an approach to evaluate and predict the broad-scale effects of work zones on large-scale traffic networks. For the requirement of the efficient evaluation of the various impacts of work zones on traffic networks, this study defines the road maintenance sensitivity factor (RMSF) to represent the joint impact of work zones. A simulation-based optimization method for calibrating the RMSF is formulated. The original objective function is replaced by an analytical metamodel that builds the approximate relationship between the RMSFs and traffic flow distribution with the effect of work zones. A derivative-free trust-region algorithm is used to obtain the optimal solution. Numerical experiments are conducted on a small test network and a large-scale freeway network. The proposed method shows the accuracy and effectiveness with tight computational resources than the simultaneous perturbation stochastic approximation method in both experiments, giving the RMSF results and map the traffic redistribution of large-scale networks with work zones accurately and efficiently, which can help traffic managers to optimize maintenance plans and traffic management measures with the assistance of the traffic management system.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818713","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":"Nash Bargaining Strategy in Autonomous Decision Making for Multi-Ship Collision Avoidance Based on Route Exchange","authors":"Yang Wang,&nbsp;Qiangsheng Ye,&nbsp;Hoong Chuin Lau,&nbsp;Tengfei Wang,&nbsp;Bing Wu","doi":"10.1049/itr2.70025","DOIUrl":"10.1049/itr2.70025","url":null,"abstract":"<p>A novel scheme is proposed for the distributed multi-ship collision avoidance (CA) problem with consideration of the autonomous, dynamic nature of the real circumstance. All the ships in the envisioned scenarios can share their decisions or intentions through route exchange, allowing them to make subsequent decisions based on the route planning in each iteration. By leveraging route exchange, the multi-ship CA problem involves iterations for negotiation, and is regarded as a staged cooperative game under conditions of complete information. The concept of closest spatio-temporal distance (CSTD) is introduced to more accurately assess collision risk between ships. A coordinated CA mechanism is established when a collision risk is identified, which further incorporates considerations including the stand-on/give-way relationships, negotiation rounds, route re-planning calculation, as well as the cost factor for route evaluation. The Nash bargaining solution (NBS) is elaborated to achieve Pareto-optimal CA routes in the scenarios. In the proposed model, while the individual interest of each ship are maximized, the economic fairness and global optimization of the overall system are also maintained. Simulation results indicate that the NBS shows good flexibility and adaptability, and that when all ships comply with route re-planning solution, the proposed scheme can bring out normal solutions within a limited number of re-planning iterations.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143801406","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 Reinforcement Learning-Based AGV Scheduling for Automated Container Terminals With Resilient Charging Strategies","authors":"Shaorui Zhou,&nbsp;Yeyi Yu,&nbsp;Min Zhao,&nbsp;Xiaopo Zhuo,&nbsp;Zhaotong Lian,&nbsp;Xun Zhou","doi":"10.1049/itr2.70027","DOIUrl":"10.1049/itr2.70027","url":null,"abstract":"<p>Automated guided vehicles (AGVs) serve as pivotal equipment for horizontal transportation in automated container terminals (ACTs), necessitating the optimization of AGV scheduling. The dynamic nature of port operations introduces uncertainties in AGV energy consumption, while battery constraints pose significant operational challenges. However, limited research has integrated charging and discharging behaviors into AGV operations. This study innovatively proposes an AGV scheduling model that incorporates a resilient and adaptive charging strategy, adjusting the balance between vehicle charging and the completion of transportation tasks, enabling AGVs to complete fixed container transportation tasks in the shortest time. Differing from most existing research primarily based on OR-typed algorithms, this study proposes a reinforcement learning-based AGV scheduling method. Finally, a series of numerical experiments, which is based on a real large-scale automated terminal in the Pearl River Delta (PRD) region of Southern China, are conducted to verify the effectiveness and efficiency of the model and the algorithm. Some beneficial management insights are obtained from sensitivity analysis for practitioners. Notably, the paramount observation is that the operational efficacy of AGVs does not necessarily correlate positively with their number. Instead, it follows a “U-shaped” curve trend, indicating an optimal range beyond which performance diminishes.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143801407","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":"Towards a Data-Driven Digital Twin AI-Based Architecture for Self-Driving Vehicles","authors":"Parinaz Babaei,&nbsp;Nosrat Riahinia,&nbsp;Omid Mahdi Ebadati E,&nbsp;Ali Azimi","doi":"10.1049/itr2.70017","DOIUrl":"10.1049/itr2.70017","url":null,"abstract":"<p>Recent advancements on digital technologies, particularly artificial intelligence, have been resulted into remarkable transformations in automobile industry. One of these technologies is artificial intelligence (AI). AI plays a key role in the development of autonomous vehicles. In this paper, the role of AI in autonomous vehicle (AV) platform layers is studied. The focus of this paper is on the indexed papers in Scopus database. The most relevant keywords are selected and searched. 628 articles, between 2014 and 2024 were selected for analysing and reviewing. Articles were analysed based on source type, topics, and AI algorithms. Text mining and content analysis of articles revealed that 233 journals published 628 articles, and the most top 185 are selected to assess. The topics of paper are classified into perception, localization and mapping, planning, decision making, control, communication, security, data management, and general topics. Each of these areas consisted of many roles, or tasks and use AI to realize their tasks. Convolutional neural network in the perception, control, and localization and mapping layers have been more used. Deep reinforcement learning had the most application in planning and decision-making areas. The main result of this paper is recognition of AVs platform layers classification, designing a data-driven digital twin AI-based model of autonomous vehicles architecture, containing physical world, virtual world, and communication space, and mapping of applied AI algorithms each layer, which aid researchers to choose the suitable methods in the field of autonomous vehicles. This study provided a comprehensive map of research projects related to from 1985 to 2022. Finally, some research directions are suggested.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143787139","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":"Energy Efficient Adaptive Bit-Mapping Based Collision-Free MAC Protocol for VANETs","authors":"Manoj Tolani,&nbsp;K Tushar Vikash,&nbsp;Pankaj Kumar","doi":"10.1049/itr2.70026","DOIUrl":"10.1049/itr2.70026","url":null,"abstract":"<p>In the present work, an energy-efficient medium access control (MAC) protocol is proposed for the adaptive data traffic condition in VANET. The proposed adaptive collision free MAC-bit map assisted (ACFM-BMA) protocol represents a significant advancement in vehicular communication systems by integrating strategies focused on electric vehicle (EV) battery levels and buffer status. This protocol optimizes communication efficiency and energy conservation through a holistic approach that considers the dynamic nature of both the vehicles' energy resources and their data buffering capabilities. By incorporating real-time data about EV battery levels, the protocol ensures that communication tasks are scheduled in a manner that conserves energy, extending the operational lifespan of vehicles in the network. Additionally, the protocol takes into account the buffer status of each vehicle, preventing data congestion and loss and enhancing the reliability of data transmission. The integration of battery and buffer status information enables more efficient use of the communication channel, reducing idle times and improving overall throughput. The performance of the proposed method is analyzed based on overall vehicle density, the number of vehicles generating periodic data traffic, and the event occurrence probability of vehicles generating event data traffic. Three different scenarios are considered: low, medium, and high data traffic, corresponding to varying numbers of vehicles. The results demonstrate that the proposed method significantly conserves energy across all scenarios.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143770165","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 a Novel Integrated Control System to Enhance Speed Planning and Control Efficiency for Subway Train","authors":"Jing Shang,&nbsp;Cheng Li,&nbsp;Xiwen Yuan","doi":"10.1049/itr2.70024","DOIUrl":"10.1049/itr2.70024","url":null,"abstract":"<p>The traditional distributed control system of trains faces challenges such as weak functional coordination, limited information sharing, significant control response delays, and low speed control accuracy, thereby impeding the efficient and energy-saving operation of trains. This paper proposes a novel integrated control system architecture and approach for trains, facilitating rapid interaction and reuse of control information through the integration of data and computations from onboard signals, traction, braking, and network subsystems. Initially, a sophisticated software architecture for integrated control is developed. Subsequently, leveraging optimal control theory, the paper outlines a strategy for optimising the train's manipulation curve and employs the LQR control algorithm for speed tracking control. Finally, the effectiveness of the proposed integrated control method is rigorously validated through experiments. The results demonstrate that the proposed approach effectively reduces the need for frequent train operation condition switching, resulting in a 16.1% energy-saving rate in speed curve optimisation and maintaining a speed control error of less than 0.2 km/h, thus substantially enhancing energy efficiency and passenger comfort during train operations.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749323","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":"Integrated Line Planning and Timetable Scheduling for Railways Considering the Dynamics and Uncertainty of Passenger Demand","authors":"Zhaocha Huang,&nbsp;Han Zheng","doi":"10.1049/itr2.70019","DOIUrl":"10.1049/itr2.70019","url":null,"abstract":"<p>Scheduling plans catering to dynamic and complex passenger demands have drawn recent attention. Given dynamic demand, there is an urgent need to explore methods for extracting valid data from vast amounts of information and achieving flexible, robust parametric control of scheduling to boost transportation resource utilization efficiency. This paper proposes a deep learning technique to construct uncertainty sets using first- and second-order moment information of passenger demand. Based on previous research under deterministic demands, a distributional robust optimization model for integrated line plan and timetable scheduling is established. Unlike other robust optimization models, the distributional robust one can better utilize the information in uncertain data. To handle the ensuing mixed integer semidefinite programming problem, a generalized benders decomposition algorithm post-linearization is presented, which decomposes the model for iterative solving. Notably, the proposed model attains an average demand satisfaction rate 10.19% higher than the deterministic demand model, reduces train usage by 9, and lifts the average full load rate by 19.05% compared to the strongly robust model. It can flexibly select parameters for diverse demand scenarios and decision-making objectives, offering theoretical support for planning under uncertain passenger demands.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143741153","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":"STCDM: Spatio-Temporal Conditional Diffusion Model for Traffic Data Filling","authors":"Jiayi Wu,&nbsp;Xinglin Piao,&nbsp;Xiulan Wei,&nbsp;Yong Zhang","doi":"10.1049/itr2.70016","DOIUrl":"10.1049/itr2.70016","url":null,"abstract":"<p>While the utilization of transportation systems is on the rise, significant data quality concerns persist, including data loss and noise arising from network transmission delays and detector malfunctions. Various methods for data imputation exist, among which diffusion-based approaches have demonstrated competitive outcomes. Nonetheless, diffusion models, primarily employed in matrix-structured data like images, fail to fully exploit the inherent graph structure of traffic data. To enhance the quality of data filling, we propose a novel method that combines spatio-temporal transformer and a conditional diffusion model (STCDM). The introduction of the conditional diffusion model involves using observable traffic data as conditional information in the reverse process, allowing it to learn the underlying probability distribution and guide the generation of high-quality data samples. The spatio-temporal transformer module is selected as the basic denoising function, capturing comprehensive spatio-temporal context information of traffic data. Our experimental results, conducted on public transportation datasets with various missing patterns and rates, indicate that STCDM exhibits superior performance by achieving up to a 1.11% improvement over the second-ranked conditional score-based diffusion model across popular performance metrics.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.70016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143717139","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}