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Digital Twins and Parallel intelligence (DTPI), IEEE International Conference on

作者： Fan Liu Jing Xun Min Zhou Shibo He Hairong Dong State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China State Key Laboratory of Industrail Control Technology Beijing Jiaotong University Hangzhou China School of Electronic Information Engineering Beihang University Beijing China

ISBN: (数字)9781665492270

ISBN: (纸本)9781665492287

With the development of high-speed railway automatic train operation(ATO) systems, the automatic operation system gradually replaces the work and responsibilities of traditional drivers. Under the parallel intelligent method, a real-time rescheduling model combined ATO driving strategy is proposed to restore the train operation from the delay caused by disturbance. The objective of the proposed model is to minimize the total delay when disturbance occurs. We use a commercial solver to solve our model. Finally, two numerical cases are carried out to verify the effectiveness of the proposed model.

关键词： Alarm systems Real-time systems rail transportation Dispatching Numerical models Delays Digital twins

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Dynamic Safe Area Detection Method for Autonomous Vehicles in Hub Airport 40

Dynamic Safe Area Detection Method for Autonomous Vehicles i...

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40th Chinese control Conference, CCC 2021

作者： Pang, Xiaoyu Shangguan, Wei Cao, Yue Chai, Linguo Qiu, Weizhi Beijing Jiaotong University School of Electronic and Information Engineering Beijing100044 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Key Laboratory of Intelligent Operation of Civil Aviation Airport Cluster Beijing100621 China

ISBN: (纸本)9789881563804

The application of autonomous driving technology will improve the level of airport autonomy and intelligent operation. In order to improve safety, autonomous vehicles need to accurately detect what portion of area inside the lane is free from obstacles. This paper proposes a safe area detection method, which uses a safe threshold to combine the lane detection model and the SSD object detection model to mark the safe area for airport autonomous vehicles. Finally, in the built airport simulation platform, we mainly compare the proposed method with the FCN area detection method. The simulation results show the proposed method improves accuracy rate by 7.91%, and speed by 17.90%, which can meet the requirements of real-time detection in hub airport. © 2021 Technical Committee on control Theory, Chinese Association of automation.

关键词： Autonomous vehicles

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Digital twin-based automatic train regulation for integration of dispatching and control 1

Digital twin-based automatic train regulation for integratio...

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1st IEEE International Conference on Digital Twins and Parallel intelligence, DTPI 2021

作者： Zhou, Min Hou, Zhuopu Liu, Jun Reborts, Clive Dong, Hairong Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety China CRSC Research Design Institute Group Co. Ltd. School of Electronic Electrical and Systems Engineering University of Birmingham United Kingdom

ISBN: (纸本)9781665433372

This paper proposes a framework of digital twin-based integration of train regulation and control for metro systems. We study the integration of train regulation and train control by using deep learning and hybrid search methods. Specifically, a well-trained convolutional neural network is adopted to fit the nonlinear function mapping relationship between the input set (the line conditions and running time of the train in each section) and the output set (the energy consumption of the optimal speed profile and the switching points), which greatly reduces the calculation time of the optimal recommended speed profile in the process of train regulation. An integrated optimization model is proposed with the aim to minimize the total train delay and energy consumption, a hybrid search algorithm based on particle swarm optimization and a genetic algorithm was developed to solve the problem. The effectiveness of the proposed method is verified based on the actual operating data of a Beijing subway line. © 2021 IEEE.

关键词： Energy utilization

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Beyond-line-of-sight Perception Enhancement via Information Interaction in Connected Autonomous Driving Environment

Beyond-line-of-sight Perception Enhancement via Information ...

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Chinese automation Congress (CAC)

作者： Yuanyuan Zha Wei Shangguan School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Electronic and Information Engineering State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

On account of occlusion and limited visual range, the independent perception of the single vehicle is restricted, which cannot meet the requirements of high-level autonomous driving. In view of the characteristics of information interaction in connected environment, a vehicle-vehicle based beyond-line-of-sight fusion perception framework is proposed. Effective data fusion of multi-source heterogeneous sensor is realized based on D-S evidence theory. Precise object detection and recognition is achieved based on lightweight object detection Faster R-CNN algorithm with backbone used MobileNetV2. Finally, the beyond-line-of-sight perception enhancement method in typical scenes is verified and analyzed on Prescan. Results show that the presented method helps autonomous vehicles make full use of sensory data effectively, expand perception scope, avoid blind fields, which plays a supporting role in the safe and efficient operation of autonomous vehicles.

关键词： Visualization automation Evidence theory Decision making Data integration Object detection Autonomous vehicles

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Discrete-time Linear Tracking control Based on Parallel System Theory

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Applied Mathematics and Nonlinear Sciences 2024年第1期9卷

作者： Gao, Junjie Chen, Mingliang Wei, Qinglai The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment China Nuclear Power Engineering Co. Ltd Guangdong Shenzhen518172 China

Inspired by parallel system theory, a novel parallel tracking controller is presented for discrete-time linear systems in this paper. The core point is to model the time derivative of system control, which makes the control system and the control law completely equivalent in mathematical form. First, the architecture of discrete-time linear parallel tracking control is introduced. Then, in the sight of the reachability of control systems, the pole assignment theorems are given. The merits of this presented method comparing with traditional feedback control are analyzed. Eventually, the efficiency of this method is proved through numerical results. © 2024 Gao, J., Chen, M. & Wei, Q.

关键词： Discrete time control systems

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Optimization of Heavy Haul Train Speed Profiles Under Discrete Notches and Nonlinear Braking Forces

Optimization of Heavy Haul Train Speed Profiles Under Discre...

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International Conference on Intelligent Transportation

作者： Zhiyuan Zhang Hongwei Wang Xi Wang Jun Jin Zhipeng Ying Pengfei Ning School of Automation and Intelligence Beijing Jiaotong University Beijing China China State Railway Group Co. Ltd. Beijing China Signals and Communication Research Institute China Academy of Railway Sciences Beijing China State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing P. R. China Collaborative Innovation Center of Railway Traffic Safety Beijing Jiaotong University Beijing China

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Due to the large mass of heavy haul trains, operating on downhill sections poses significant challenges on train control. Drivers must perform air braking and releasing at the appropriate times to prevent the movement of heavy hual train from decoupling and derailment. To promote the smooth operation of the heavy haul train, this research investigates the optimization problem of heavy haul train speed profiles under discrete notches and nolinear braking forces. An optimization model is first established considering constraints such as speed and air-refilling time to maximize the running distance and minimize the air braking time of a train on downhill sections. This model takes into account discrete notches of electric braking force, each with a nonlinear braking profile. To linearize the model, piecewise approximation (PWA) function and auxiliary variables are introduced, transforming the original problem into a mixed integer linear programming (MILP) problem. The proposed MILP problem is then solved using a solver. Simulations using actual data from the Shuohuang railway illustrate the effectiveness of the proposed methods.

关键词： Atmospheric modeling railway accidents Optimization models Force Linear programming rail transportation Data models Mixed integer linear programming Optimization Intelligent transportation systems

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Parallel intelligence method for timetable rescheduling of high-speed railways under disturbances 1

Parallel intelligence method for timetable rescheduling of h...

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1st IEEE International Conference on Digital Twins and Parallel intelligence, DTPI 2021

作者： Liu, Xuan Zhou, Min Song, Haifeng Gao, Shigen Jin, Chenkun Dong, Hairong Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing100044 China School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Institute of Computing Technology Academy of Railway Sciences Beijing100081 China

ISBN: (纸本)9781665433372

This paper focuses on solving the real-time timetable rescheduling problem for dispatching systems of high-speed railway systems (HSRs) in case of temporary speed restriction by utilizing the parallel intelligence method. We construct a parallel intelligent system framework, which combines the actual and artificial dispatching systems through computational experiments and parallel execution. Then a rescheduling model includes retiming, recording and rerouting, and a solution method based on rolling horizon optimization are both proposed. Finally, a timetable of Beijing-Shanghai HSR within the jurisdiction of the Beijing railway Bureau based case study indicates that the proposed parallel intelligence method can effectively decrease the total delay. © 2021 IEEE.

关键词： Intelligent systems

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Delay propagation for a High-speed railway Network with the Consideration of Primary Delay Derivation

Delay propagation for a High-speed Railway Network with the ...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Wenbo Lian Xingtang Wu Min Zhou Qinpei Duan Hairong Dong the State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China the School of Automation Science and Electrical Engineering Beihang University Beijing China Department of Dispatch China Railway Beijing Bureau Group Co. Ltd Beijing China

ISBN: (数字)9781665484855

ISBN: (纸本)9781665484862

China’s High-Speed railway (HSR) has entered the era of networked operation. Unpredictable emergencies may disrupt the normal operation of the railway, resulting in train delays. The delays may even cause cascading delays due to the track constraint. This paper proposed a delay propagation model by max-plus algebra, considering the constraint of the HSR network, to predict the spatial-temporal range of cascading delays under emergencies. Moreover, the operation strategy re-management in sections and the re-timing strategy due to the station capacity constraint are studied under emergencies, forming a chain model of emergencies, primary delays, and secondary delays. Simulation results show that the proposed model could accurately predict the secondary delay under different emergencies.

关键词： Algebra Computational modeling Simulation Power system protection Predictive models Prediction algorithms rail transportation

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Dynamic Passenger Demands Oriented Optimization of Virtually Coupled Train Formation Scheduling

Dynamic Passenger Demands Oriented Optimization of Virtually...

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Chinese automation Congress (CAC)

作者： Haobei Zhang Tao Tang Hongjie Liu Yinghui Lang School of Electronics and Information Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China

The research on virtual coupling technology in metros is a hot topic recently. Intelligent automatic train units can flexibly form virtually coupled train formations (VCTFs) when needed, so that the train capacity would be able to adapt to passenger demands, which are changing dynamically with time and space. However, matching the capacity of trains with passenger demands is a difficult decision-making optimization problem. In this work, we propose a collaborative control problem to decide when and how to create a VCTF to meet the dynamic passenger demands in a metro system. A mathematical model is formulated which can simultaneously optimize the number of related train units in a VCTF, the train dwelling time at a station and the running time in a section. Performance indicators such as train load factor and number of stranded passengers are adopted to measure the satisfaction of the operators and passengers. Then, a multi-objective genetic algorithm is adopted to obtain the Pareto optimum solutions. Finally, simulation experiments are conducted, and the relationship between line efficiency and passenger demand in different discrete time periods is analyzed to verify the correctness and feasibility of the model. Compared with the traditional timetabling method, adopting the virtual coupling technology can better adapt the train capacity to meet the time changing passenger demands, which is welcomed by both metro operators and passengers in reality.

关键词： Couplings Road transportation rails Adaptation models Analytical models Dynamic scheduling Vehicle dynamics

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Kalman Based Data Fusion Algorithm for High Accuracy Train Positioning

Kalman Based Data Fusion Algorithm for High Accuracy Train P...

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2021 China automation Congress, CAC 2021

作者： Li, Lulu Song, Haifeng Sun, Pengju Liu, Xiaoxi Zhou, Min Dong, Hairong School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Institute of Transportation and Economics China Academy of Railway Sciences Group Co. Ltd Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

ISBN: (纸本)9781665426473

The track circuit can automatically and continuously detect the train position occupancy in the track section. Most of the existing train positioning systems are limited to determine which block is occupied, but can not obtain the accurate position of the train in the block section. Global Navigation Satellite System (GNSS) has the advantages of high precision and real-time positioning, and it can provide an absolute position data. However, in dense areas of tracks, such as stations, it is impossible to accurately determine where the train is located due to GNSS positioning errors. In this paper, an algorithm is proposed to combine GNSS positioning technology with the track circuit positioning method to obtain continuous train position information in the block areas. The position information of the track circuit can also correct the error of GNSS positioning data, and effectively improve train positioning accuracy. What is more, a train positioning simulation platform is developed and applied to verify the proposed method. © 2021 IEEE

关键词： Data fusion

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