IEEE Transactions on Intelligent Transportation Systems最新文献

IEEE Intelligent Transportation Systems Society Information IEEE智能交通系统学会信息

IF 8.4 1区工程技术

IEEE Transactions on Intelligent Transportation Systems Pub Date : 2025-09-24 DOI: 10.1109/TITS.2025.3604346

引用次数: 0

IEEE INTELLIGENT TRANSPORTATION SYSTEMS SOCIETY Ieee智能交通系统学会

IF 7.9 1区工程技术

IEEE Transactions on Intelligent Transportation Systems Pub Date : 2025-07-02 DOI: 10.1109/TITS.2025.3579658

引用次数: 0

IEEE Intelligent Transportation Systems Society Information IEEE智能交通系统学会信息

IF 7.9 1区工程技术

IEEE Transactions on Intelligent Transportation Systems Pub Date : 2025-07-02 DOI: 10.1109/TITS.2025.3579612

引用次数: 0

Scanning the Issue 扫描问题

IF 7.9 1区工程技术

IEEE Transactions on Intelligent Transportation Systems Pub Date : 2025-07-02 DOI: 10.1109/TITS.2025.3580163

Simona Sacone

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Intelligent Connected Vehicle Data Privacy and Security Transaction Sharing System Based on Blockchain 基于区块链的智能网联汽车数据隐私与安全事务共享系统

IF 8.4 1区工程技术

IEEE Transactions on Intelligent Transportation Systems Pub Date : 2025-06-26 DOI: 10.1109/TITS.2025.3578015

Jiwei Zhang;Yufei Tu;Ziang Sun;Tianqi Song;Shaozhang Niu

{"title":"Intelligent Connected Vehicle Data Privacy and Security Transaction Sharing System Based on Blockchain","authors":"Jiwei Zhang;Yufei Tu;Ziang Sun;Tianqi Song;Shaozhang Niu","doi":"10.1109/TITS.2025.3578015","DOIUrl":"https://doi.org/10.1109/TITS.2025.3578015","url":null,"abstract":"With the widespread application of Transportation Cyber Physical Systems (T-CPS), increasingly intelligent and interconnected vehicles are conducting extensive transportation activities. Compared with traditional transportation equipment, they integrate advanced information functions such as data collection, terminal communication, real-time computing, and remote coordination, which can generate and collect a large amount of real traffic data. The enormous value of these traffic data can be released through market-oriented transactions. Blockchain technology can support the transmission and collaborative control of information T-CPS, while protecting the privacy and data security of intelligent connected vehicles. This article proposes a blockchain based data trading system aimed at simplifying the transaction flow of traffic data for intelligent connected vehicle owners, while maintaining fairness, privacy, and sustainable market development. Our work introduces two key innovations: a two-stage availability verification process that reduces transaction costs while enhancing data reliability, and an efficient encryption confirmation mechanism that ensures privacy and security for data providers and buyers throughout the entire transaction lifecycle. Finally, we demonstrate the feasibility and overall performance of our system through comprehensive analysis including security and reliability assessment, market behavior analysis, and computational complexity modeling, as well as practical experiments based on the Ethereum blockchain network. The evaluation results indicate that this scheme can provide privacy and security data transaction services at lower transaction costs.","PeriodicalId":13416,"journal":{"name":"IEEE Transactions on Intelligent Transportation Systems","volume":"26 9","pages":"14192-14204"},"PeriodicalIF":8.4,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Responsibility-Based Socially Compatible Driving Behavior Modeling Verified by Hierarchical Multi-Agent Inverse Reinforcement Learning 基于责任的社会相容驾驶行为分层多智能体逆强化学习模型

IF 8.4 1区工程技术

IEEE Transactions on Intelligent Transportation Systems Pub Date : 2025-06-24 DOI: 10.1109/TITS.2025.3577660

Tingjun Li;Nan Xu;Shuo Feng;Hassan Askari;Bruno Henrique Groenner Barbosa;Konghui Guo

{"title":"Responsibility-Based Socially Compatible Driving Behavior Modeling Verified by Hierarchical Multi-Agent Inverse Reinforcement Learning","authors":"Tingjun Li;Nan Xu;Shuo Feng;Hassan Askari;Bruno Henrique Groenner Barbosa;Konghui Guo","doi":"10.1109/TITS.2025.3577660","DOIUrl":"https://doi.org/10.1109/TITS.2025.3577660","url":null,"abstract":"Autonomous vehicles (AVs) offer a promising glimpse into a future where transportation is smarter, safer, and more streamlined. Nevertheless, as AVs continue to interact with conventional vehicles (CVs), the potential for increased complexities and challenges cannot be overlooked, such as the frozen robot problem. This study proposes a regret-based model for motion planning responsibilities, encompassing self-respect and courtesy for conflicting personal interests. By incorporating these reciprocal responsibilities, socially compatible driving behaviors are promoted, and uncertainties in behavior are also reduced. A Self-Respect-Courtesy (SR-C) plane is further introduced, illustrating the interaction intensity and tendency. To navigate the trade-offs of responsibilities in varying situations, the concept of environmental niche is provided. Niches help to characterize the outcomes of specific actions with the resulting conditions to fulfill responsibilities. Finally, a hierarchical multi-agent inverse reinforcement learning algorithm is designed to calibrate the proposed model with NGSIM highway lane-changing cases. We found that the proposed model can significantly improve the calibration results and reduce the predictions error of mandatory lane changes by up to 20%. Moreover, the cross-entropy error also significantly decreases in a stable stage, indicating that responsible actions can safely reduce the behavior uncertainties of interactions. Our research revealed that drivers prioritize courtesy responsibility in discretionary lane changes with more consistency, whereas their self-respect preferences are stronger but show more variability in mandatory lane changes. These findings provide valuable insights into the underlying mechanism of interactions.","PeriodicalId":13416,"journal":{"name":"IEEE Transactions on Intelligent Transportation Systems","volume":"26 9","pages":"14353-14370"},"PeriodicalIF":8.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Traffic Flow Crystallization Method for Trajectory Approximation and Lane Change Inference 交通流结晶法的轨迹逼近与变道推理

IF 7.9 1区工程技术

IEEE Transactions on Intelligent Transportation Systems Pub Date : 2025-06-13 DOI: 10.1109/TITS.2025.3572623

Mohammad Ali Arman;Chris M. J. Tampère

{"title":"Traffic Flow Crystallization Method for Trajectory Approximation and Lane Change Inference","authors":"Mohammad Ali Arman;Chris M. J. Tampère","doi":"10.1109/TITS.2025.3572623","DOIUrl":"https://doi.org/10.1109/TITS.2025.3572623","url":null,"abstract":"Whereas on many motorways, traffic operations are permanently monitored, and long historical logs of such data exist, they are not directly usable for lane change studies, as they only register local passages and speeds. This study proposes a novel method to transform discrete vehicle passage records of individual vehicle data (IVD) into approximations of vehicle trajectories and inference of lane change maneuvers (LCMs), such that large-scale LCM dataset can be retrieved from existing infrastructures where IVD is recorded at sufficiently close spacings (~600 meters). The method’s core is a probabilistic re-identification of individual vehicles in successive, lane-specific loop detectors. Dubbed Traffic Flow Crystallization (TFC), the methodology enhances traffic monitoring by providing vast and diverse LCM datasets. It consists of two key re-identification (ReID) modules: a lane-restricted module that matches vehicles strictly within the same lane and a non-lane-restricted module that recursively identifies lane-changing vehicles using boundary conditions imposed by previously matched vehicles. This recursive process resembles crystal growth, inspiring the method’s name. The ReID methodology is based on a weighted likelihood function consisting of Bayesian probability estimators that integrate three similarity measures: vehicle length, passage time, and passage speed. A lane-change feasibility filter ensures that re-identified vehicles satisfy plausible spatiotemporal constraints. The final module resolves inconsistencies and infers LCMs. The proposed method is trained and validated using CCTV footage, where visually-identified vehicles serve as ground truth. Validation results demonstrate a vehicle ReID success rate exceeding 96% and an inferred LCM rate with only a 2% underestimation compared to ground truth.","PeriodicalId":13416,"journal":{"name":"IEEE Transactions on Intelligent Transportation Systems","volume":"26 7","pages":"9305-9325"},"PeriodicalIF":7.9,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vehicle Cooperative Positioning With Tightly Coupled GNSS/INS/UWB Integration Based on Improved Multiple Fading Factors and Adaptive Cost Function 基于改进多重衰落因子和自适应成本函数的GNSS/INS/UWB紧密耦合集成车辆协同定位

IF 7.9 1区工程技术

IEEE Transactions on Intelligent Transportation Systems Pub Date : 2025-06-13 DOI: 10.1109/TITS.2025.3575812

Jingang Zhao;Wei Sun;Wei Ding;Yadan Li;Pengxiang Sun;Peilun Sun

{"title":"Vehicle Cooperative Positioning With Tightly Coupled GNSS/INS/UWB Integration Based on Improved Multiple Fading Factors and Adaptive Cost Function","authors":"Jingang Zhao;Wei Sun;Wei Ding;Yadan Li;Pengxiang Sun;Peilun Sun","doi":"10.1109/TITS.2025.3575812","DOIUrl":"https://doi.org/10.1109/TITS.2025.3575812","url":null,"abstract":"Cooperative positioning technology based on multi-vehicle information fusion is essential for advanced applications in intelligent transportation systems (ITS). The integration of global navigation satellite systems (GNSS), inertial navigation system (INS), and ultra-wideband (UWB) technology holds significant promise for enhancing the continuity and reliability of vehicle cooperative positioning. In tightly coupled GNSS/INS/UWB integration, the tolerance against measurement outliers and state model perturbations is pivotal for fulfilling the specific requirements of critical ITS applications. To optimize the comprehensive performance of vehicle cooperative positioning under uncertain sensor observation environments, this paper proposes a robust multiple fading factors unscented Kalman filtering (RMFUKF) algorithm based on adaptive cost function. The proposed solution incorporates Huber M-estimation with an adaptive tuning strategy to perform measurement-specific outliers processing. Furthermore, the improved multiple fading factors based on an exponential weighting method are implemented to mitigate the effects of dynamic model mismatches. Experimental results from vehicular field experiments demonstrate that the proposed RMFUKF scheme significantly improves the robustness and adaptive performance of vehicle cooperative positioning under unpredictable, real-world operating conditions.","PeriodicalId":13416,"journal":{"name":"IEEE Transactions on Intelligent Transportation Systems","volume":"26 7","pages":"9740-9754"},"PeriodicalIF":7.9,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Practical Distributed Control for Cooperative VTOL UAVs Within a 3-D Roundabout 三维回旋处协同垂直起降无人机的实用分布式控制

IF 7.9 1区工程技术

IEEE Transactions on Intelligent Transportation Systems Pub Date : 2025-06-13 DOI: 10.1109/TITS.2025.3570005

Rao Fu;Pengda Mao;Yangqi Lei;Kai-Yuan Cai;Quan Quan

{"title":"Practical Distributed Control for Cooperative VTOL UAVs Within a 3-D Roundabout","authors":"Rao Fu;Pengda Mao;Yangqi Lei;Kai-Yuan Cai;Quan Quan","doi":"10.1109/TITS.2025.3570005","DOIUrl":"https://doi.org/10.1109/TITS.2025.3570005","url":null,"abstract":"With the rapid development of uncrewed aerial vehicle (UAV) technology in recent years, research on large-scale low-altitude UAV air traffic management (ATM) has gained attention. Unlike the traditional ATM, the number of small UAVs in the airspace may be in the millions, making air traffic management challenging. In an ATM, airspace is composed of airways, intersections, and nodes. In this paper, a three-dimensional (3-D) roundabout model is utilized as an airspace structure for air traffic intersections of known traffic network models, which is decomposed into a central island, several ramps, and buffer zones. In this paper, for simplicity, the distributed coordination of the motions of Vertical TakeOff and Landing (VTOL) UAVs to pass through a 3-D roundabout is focused on, which is formulated as a 3-D roundabout passing-through problem. The corresponding control objectives include inter-agent conflict-free, keeping within the 3-D curved virtual tube, and avoiding local minima. Lyapunov-like functions are designed elaborately, and formal analysis is made to show that all UAVs can pass through the 3-D roundabout without getting trapped. Taking the kinematic model of VTOL UAVs into consideration, the horizontal control and attitude control channels are decoupled, which is more reasonable for practical applications. Numerical simulation and real experiment are given to show the effectiveness of the proposed method.","PeriodicalId":13416,"journal":{"name":"IEEE Transactions on Intelligent Transportation Systems","volume":"26 7","pages":"9341-9357"},"PeriodicalIF":7.9,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling Multi-Granularity Context Information Flow for Pavement Crack Detection 面向路面裂缝检测的多粒度上下文信息流建模

IF 7.9 1区工程技术

IEEE Transactions on Intelligent Transportation Systems Pub Date : 2025-06-12 DOI: 10.1109/TITS.2024.3438883

Junbiao Pang;Baocheng Xiong;Jiaqi Wu;Qingming Huang

{"title":"Modeling Multi-Granularity Context Information Flow for Pavement Crack Detection","authors":"Junbiao Pang;Baocheng Xiong;Jiaqi Wu;Qingming Huang","doi":"10.1109/TITS.2024.3438883","DOIUrl":"https://doi.org/10.1109/TITS.2024.3438883","url":null,"abstract":"Pavement cracks have a highly complex spatial structure, a low contrasting background and a weak spatial continuity, posing a significant challenge to an effective crack detection method. To precisely localize crack from an image, it is critical to effectively extract and aggregate multi-granularity context, including the fine-grained local context around the cracks (in spatial-level) and the coarse-grained semantics (in semantic-level). In this paper, we apply the dilated convolution as the backbone feature extractor to model local context, then we build a context guidance module to leverage semantic context to guide local feature extraction at multiple stages. To handle label alignment between stages, we apply the Multiple Instance Learning (MIL) strategy to align the feature between two stages. In addition, to our best knowledge, we have released the largest, most complex and most challenging Bitumen Pavement Crack (BPC) dataset. The experimental results on the three crack datasets demonstrate that the proposed method performs well and outperforms the current state-of-the-art methods. On BPC, the proposed model achieved AP 88.32% with the 16.89 M parameters under the 45.36 GFlops runing speed. Datset and code are publicly available at: <uri>https://github.com/pangjunbiao/BPC-Crack-Dataset</uri>.","PeriodicalId":13416,"journal":{"name":"IEEE Transactions on Intelligent Transportation Systems","volume":"26 7","pages":"9165-9174"},"PeriodicalIF":7.9,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0