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27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Yang, Boyu Lv, Jidong Liu, Hongjie Chai, Ming Zhang, Qinglong Tang, Tao Lv, Jiahui National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China School of Civil and Resource Engineering University of Science and Technology Beijing China Beijing Jiaotong University The Associate Director of the Rail Traffic Control and Safety State Key Laboratory China

ISBN: (纸本)9798331505929

Operating multiple trains as a group under Train-to-Train communication is an efficient way in sparse railway networks. However, it is a barrier to accurate tracking for follower trains with the uncertain status of the preceding trains under communication delay. Therefore, we proposed a train trajectory prediction approach, aiming to obtain an accurate state of preceeding trains in a long time horizon. Firstly, we established a hybrid prediction model combined Long Short-Term Memory (LSTM) with the Kalman Filter (KF) and using the sliding window mechanism to enhance future prediction accuracy. Secondly, to fusion LSTM prediction data and the Kalman calculation model, we proposed the Hybrid Train Trajectory Prediction algorithm by adopting real-time calculation of the covariance matrix using real data and predicted data. Finally, we apply an experiment considering network characteristics in Western China. The result shows that the Mean Absolute Error (MAE) of series prediction in the longer time domain is 44% of the Recurrent Neural Network (RNN) model and 88% of the traditional LSTM model. © 2024 IEEE.

关键词： Kalman filters

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Uav anti-collision visual detection algorithm 4

Uav anti-collision visual detection algorithm

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4th International Conference on Computer Vision, Image and Deep Learning, CVIDL 2023

作者： Han, Jun Yu Li, Zhe Li, Sheng Hou Zhao, Bo Shen Air Traffic Control and Navigation School Air Force Engineering University Xi'an710038 China Key Laboratory of Meta-Synthesis for Electornic and Information System Xi'an710051 China

ISBN: (纸本)9798350326444

In order to solve the problem of unsafe flight of traditional 'low, slow and small' civil UAVs, and reduce pres sure on air traffic control personnel., an improved YOLOv5m target detection algorithm is proposed for active target detection of UAVs. According to the characteristics of low-altitude UAV detection, an attention mechanism was added to the YO LOv5 feature extraction network, and the original weighted NMS was optimized to SOFT-NMS Finally, the accuracy and real-time performance of the model are verified by constructi ng real UAV conflict target detection data set. The experimen tal results show that the average accuracy, recall rate, accura cy are 2.31 %, 3.66% and 5.59% higher than before the impr ovement, meet the anti-collision detection requirements of civi 1 UAV s in low altitude airspace. © 2023 IEEE.

关键词： Object detection

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Temporal-spatial dynamic characteristics of vehicle emissions on intercity roads in Guangdong Province based on vehicle identity detection data

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Journal of Environmental Sciences 2023年第8期130卷 126-138页

作者： Hui Ding Yongming Zhao Shenhua Miao Tong Chen Yonghong Liu College of Automation&College of Artifical Intelligence Nanjing University of Posts and TelecommunicationsNanjing 210023China School of Intelligent Systems Engineering Sun Yat-Sen UniversityGuangzhou 510275China Guangdong Provincial Key Laboratory of Intelligent Transport System Guangzhou 510275China Guangdong Provincial Engineering Research Center for Traffic Environmental Monitoring and Control Guangzhou 510275China

Estimating intercity vehicle emissions precisely would benefit collaborative control in multiple *** the variability of emissions caused by vehicles,roads,and traffic,the 24-hour change characteristics of air pollutants(CO,HC,NO_(X),PM_(2.5))on the intercity road network of Guangdong Province by vehicle categories and road links were revealed based on vehicle identity detection data in real-life traffic for each hour in July *** results showed that the spatial diversity of emissions caused by the unbalanced economywas *** vehicle emissions in the Pearl River Delta region(PRD)with a higher economic level were approximately 1–2 times those in the non-Pearl RiverDelta region(non-PRD).Provincial roads with high loads became potential sources of high ***,emission control policies must emphasize the PRD and key roads by travel guidance to achieve greater *** passenger cars with a large proportion of traffic dominated morning and evening peaks in the 24-hour period and were the dominant contributors to CO and HC emissions,contributing more than 50%in the daytime(7:00–23:00)and higher than 26%at night(0:00–6:00).Diesel trucks made up 10%of traffic,but were the dominant player at night,contributed 50%–90%to NO_(X) and PM_(2.5) emissions,with amarked 24-hour change rule of more than 80%at night(23:00–5:00)and less than 60%during ***,targeted control measures by time-section should be set up on collaborative *** findings provide time-varying decision support for variable vehicle emission control on a large scale.

关键词： Intercity roads Dynamic vehicle emissions Vehicle identity detection data Diesel trucks

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A Safe Vision Method for Train Positioning 6th

A Safe Vision Method for Train Positioning

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6th International Conference on Electrical engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Sun, Ye Liao, Mushan Chai, Ming Liu, Hongjie Yang, Dong School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China Rail Transportation Operation and Control System Beijing Jiaotong University Beijing100044 China Chengdu Traffic Control and Metro Technology Co. Ltd. Chengdu100044 China

ISBN: (纸本)9789819993185

Train positioning is crucial for safe operation of a train. In this paper, we propose a novel safe vision method to achieve train positioning by recognizing wayside kilometer posts. The proposed method contains three parts: kilometer posts detection, kilometer posts semantic recognition, and runtime safe monitoring. A YOLO v5 model is developed to detect kilometer posts from the wayside while a train is running. A Convolutional Recurrent Neural Network (CRNN) model is used to recognize the information on the kilometer posts indicating an absolute position of the railway line. In addition, a safety monitor is proposed to avoid machine learning-based vision methods resulting incorrect recognition results. The monitor verifies whether the recognition results satisfy rule-based properties at runtime. Following the fail-safe principle, the monitor prevents the recognition results from being used for train positioning whenever a violation is detected. We evaluate our method on several benchmarks on a semi-physical simulation platform. Experiment results show that our models efficiently recognize kilometer posts with 88.32% accuracy. With the safety monitor, the safe positioning rate reaches 99.50%, providing a new idea for train visual positioning. © 2024, Beijing Paike Culture Commu. Co., Ltd.

关键词： Computer vision

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Research on head way control of a guided transport system based on intersection condition evaluation

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Transportation Safety and Environment 2023年第4期5卷 29-35页

作者： Xiao Yu Yuan Cao Yongkui Sun Signal and Communication Research Institute China Academy of Railway Sciences Corporation LimitedBeijing 100081China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing 100044China National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong UniversityBeijing 100044China

ln order to ensure the safety and efficiency of the section tracking operation of a guided transport system,a safety headway control method of section tracking based on intersection conditions is proposed in this *** the difference of signal phase,the evaluation model of road conditions was established based on a fuzzy comprehensive evaluation method,*** on the artificial potential field method,the time-varying hybrid artificial potential field(TH-APF)method was proposed,and the tracking headway control algorithm was designed to realize the dynamic control of the tracking headway of the guide transport *** simulation results verified the effectiveness and applicability of the evaluation model of intersection road conditions;the tracking headway can be maintained at about 120 *** tracking headway control algorithm of guided transport vehicles can respond to the road conditions and avoid the local optimum of the artificial potential field method,thus improving the operating efficiency.

关键词： guided transport system intersection condition evaluation artificial potential field method tracking headway control

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A Model Predictive control Approach for Virtually Coupled Train Set Based on Multi-Phase Trajectory Planning 21

A Model Predictive Control Approach for Virtually Coupled Tr...

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21st International Conference on Networking, Sensing and control, ICNSC 2024

作者： Li, Bosi Liu, Hongjie Lang, Yinghui Jia, Qingdong Zhang, Kun Li, Kaixuan School of Automation and Intelligence Beijing Jiaotong University Beijing100044 China Beijing Jiaotong University National Engineering Research Center of Rail Transportation Operation and Control System Beijing100044 China Traffic Control Technology Co. Ltd. Beijing100070 China

ISBN: (纸本)9798350365221

Virtual coupling (VC) is an emerging technology that enhances railway operations by dynamically and accurately matching line capacity with passenger demand. However, challenges arise in coordinating the virtually coupled train set (VCTS) during inter-station operations and maintaining accurate control of the VCTS. To address this issue, we propose a multi-phase trajectory planning control approach to generate the reference trajectories for VCTS to enhance the synchronicity of interstation operations. However, during speed-varying inter-station operations, it remains challenging to control VCTS accurately under disturbances while adhering to safety constraints. The control layer employs a model predictive control (MPC) approach to ensure precise reference tracking, based on the optimized reference trajectories for all train units. The effectiveness of this approach is validated through experimental results. © 2024 IEEE.

关键词： Predictive control systems

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Effect of Wheel-Rail Interface Friction Coefficient on Wheel Wear Evolution of Heavy Haul Locomotive 2nd

Effect of Wheel-Rail Interface Friction Coefficient on Wheel...

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2nd International Conference of Mechanical system Dynamics, ICMSD 2023

作者： Kai, Hao Pengfei, Liu Chen, Wang bo, Liu Zhaoxin, Ma School of Mechanical Engineering Shijiazhuang Tiedao University Shijiazhuang050043 China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang050043 China Key Laboratory of Mechanical Behavior Evolution and Control of Traffic Engineering Structures in Hebei Shijiazhuang Tiedao University Shijiazhuang050043 China School of Mechanical Engineering Hebei University of Architecture Zhangjiakou075000 China

ISBN: (纸本)9789819980475

Aiming at the serious problem of wheel wear of six-axle heavy haul locomotive, the wheel-rail interface friction theory is introduced to study the influence of different friction coefficients on wheel wear. The heavy haul locomotive-track coupling dynamic model and wheel wear model are established by UM software, and the rail top/rail side lubrication simulation conditions are set to analyze the evolution law of wheel profile and the change of wear amount. The results show that: The higher the friction coefficient of the rail top will reduce the tread wear of the first and third wheelset, but increase the flange wear rate. Under the friction coefficient of 0.40 at the rail top, the wear rates of the flanges of the first-to-third wheelset are 0.72, 0.41, and 0.52 mm/10,000 km, respectively. When the friction coefficient of the rail top is 0.40, the wear reduction rates of the flanges of the first-to-third wheelset are 16.88%, 9.97% and 9.11%, respectively, but the wear reduction of the flanges of the second wheelset is 0.20 mm under the friction coefficient of the rail top of 0.20. The research results provide a reference for wheel wear reduction of heavy haul locomotives, and provide a new idea for the research of locomotive wheel-rail interface friction management. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Flanges

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An Optimal control Based Trajectory Planning Method for Cooperative Merging Maneuvers 3

An Optimal Control Based Trajectory Planning Method for Coop...

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3rd International Symposium on Intelligent Robotics and systems, ISoIRS 2023

作者： Wang, Qi Ge, Hao Duan, Xuting Zhou, Jianshan School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control State Key Laboratory of Air Traffic Management System and Technology Beijing China Nanjing Research Institute of Electronic Engineering State Key Laboratory of Air Traffic Management System and Technology Nanjing China School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China

ISBN: (纸本)9798350339963

Due to the prediction errors and diverse driving styles of surrounding vehicles, traffic congestion and even accidents can occur in the traffic bottleneck area where vehicles merge into the main road. To ensure that connected and automated vehicles (CAVs) can quickly and efficiently merge into the main road, this paper proposes a cooperative trajectory planning method based on optimal control for vehicle cut-in scenarios. A optimal control model is constructed, and a quintic polynomial is used to generate the initial solution of the optimal control problem to accelerate the solution process and improve the success rate. Finally, The obtained merging trajectory is then synchronized with the movement of vehicles on the main road to optimize their actions and ensure a safe merging process. Joint simulation with Robot Operating system (ROS) and RVIZ is utilized, and the results show that the proposed algorithm can quickly obtain cooperative results, the locally successful merging trajectory meets the requirements of smoothness and safety, and if the solution does not allow merging, the merging vehicle is instructed to terminate the execution. © 2023 IEEE.

关键词： Trajectories

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TICNet: Three-Branch Real-Time Semantic Segmentation Network with Intensive Compensation of Railway Track Scenes 5

TICNet: Three-Branch Real-Time Semantic Segmentation Network...

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5th International Conference on Machine Learning and Computer Application, ICMLCA 2024

作者： Bai, Yiwen Yang, Lu Zhang, Lei Song, Yajing School of Transportation Science and Engineering Beihang University Beijing102206 China School of Mechanical Engineering Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Tianjin300384 China Traffic Control Technology Co. Ltd. Beijing China

ISBN: (纸本)9798331530334

With the rapid development of railway traffic system, real-time semantic segmentation plays a crucial role in railway track scene monitoring. However, most of the existing methods use lightweight convolution to reduce the computational complexity, which results in reduced accuracy. To solve this problem, this paper proposes a real-time semantic segmentation network called TICNet, which is specifically used for accurate segmentation of railway track scenes. TICNet uses a novel three-branch structure designed for efficient feature extraction and accurate segmentation. Results on the RailSem19 dataset show that TICNet has a segmentation accuracy of 62.36% mIoU with an inference speed of 81.2 FPS, which is significantly better than many existing methods. © 2024 IEEE.

关键词： Semantic Segmentation

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Research on the logic monitoring method for the cloud computing based safety computer

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Transportation Safety and Environment 2023年第2期5卷 79-87页

作者： Yaran Yang Lianchuan Ma Tao Tang Huan Ding Zhen Liu School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong UniversityBeijing 100044China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing 100044China CRSC Research&Design Institute Group Co.Ltd. Beijing 100070China

With the development of railway construction in China,the computing demand of the train control system is increasing day by *** application of cloud computing technology on the rail transit signal system has become a research hotspot in recent *** to improve the safety and availability of the safety computer platform in the cloud computing environment is the key problem when applying cloud computing to the train operation control *** the cloud platform is in an open network environment,fac-ing many security vulnerabilities and malicious network attacks,it is necessary to monitor the operation of computer programmes through edge safety ***,this paper encrypts the logical monitoring method,and then proposes a secure computer de fence model based on the dynamic heterogeneous redundancy *** the continuous time Markov chain(CTMC)is used to quantitatively solve the stable probability of the system,and the influence of different logical monitoring methods on the anti-attack performance of the system is ***,the experiment proves that the dynamic heterogeneous redundancy structure composed of encryption logic monitoring can guarantee the safe and stable operation of the safety computer more effectively.

关键词： safety computer logical monitoring method continuous time Markov modelling(CTMC) cloud computing anti-aggression analysis

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