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2. Embodied Footprints: A Safety-guaranteed Collision Avoidance Model for Numerical Optimization-based Trajectory Planning

Author

Li, Bai, Zhang, Youmin, Zhang, Tantan, Acarman, Tankut, Ouyang, Yakun, Li, Li, Dong, Hairong, and Cao, Dongpu

Subjects
Computer Science - Robotics, Mathematics - Optimization and Control
Abstract

Optimization-based methods are commonly applied in autonomous driving trajectory planners, which transform the continuous-time trajectory planning problem into a finite nonlinear program with constraints imposed at finite collocation points. However, potential violations between adjacent collocation points can occur. To address this issue thoroughly, we propose a safety-guaranteed collision-avoidance model to mitigate collision risks within optimization-based trajectory planners. This model introduces an embodied footprint, an enlarged representation of the vehicle's nominal footprint. If the embodied footprints do not collide with obstacles at finite collocation points, then the ego vehicle's nominal footprint is guaranteed to be collision-free at any of the infinite moments between adjacent collocation points. According to our theoretical analysis, we define the geometric size of an embodied footprint as a simple function of vehicle velocity and curvature. Particularly, we propose a trajectory optimizer with the embodied footprints that can theoretically set an appropriate number of collocation points prior to the optimization process. We conduct this research to enhance the foundation of optimization-based planners in robotics. Comparative simulations and field tests validate the completeness, solution speed, and solution quality of our proposal., Comment: 15 pages, 16 figures

Published
2023

6. Attention-based Supply-Demand Prediction for Autonomous Vehicles

Author

Zhang, Zikai, Li, Yidong, Dong, Hairong, You, Yizhe, and Zhao, Fengping

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

As one of the important functions of the intelligent transportation system (ITS), supply-demand prediction for autonomous vehicles provides a decision basis for its control. In this paper, we present two prediction models (i.e. ARLP model and Advanced ARLP model) based on two system environments that only the current day's historical data is available or several days' historical data are available. These two models jointly consider the spatial, temporal, and semantic relations. Spatial dependency is captured with residual network and dimension reduction. Short term temporal dependency is captured with LSTM. Long term temporal dependency and temporal shifting are captured with LSTM and attention mechanism. Semantic dependency is captured with multi-attention mechanism and autocorrelation coefficient method. Extensive experiments show that our frameworks provide more accurate and stable prediction results than the existing methods., Comment: 5 page, naive version

Published
2019

11. The rising roles of exosomes in the tumor microenvironment reprogramming and cancer immunotherapy.

Author

Wu, Yu, Han, Wenyan, Dong, Hairong, Liu, Xiaofeng, and Su, Xiulan

Subjects
TUMOR microenvironment, EXOSOMES, CELL communication, IMMUNOTHERAPY, DRUG delivery systems
Abstract

Exosomes are indispensable for intercellular communications. Tumor microenvironment (TME) is the living environment of tumor cells, which is composed of various components, including immune cells. Based on TME, immunotherapy has been recently developed for eradicating cancer cells by reactivating antitumor effect of immune cells. The communications between tumor cells and TME are crucial for tumor development, metastasis, and drug resistance. Exosomes play an important role in mediating these communications and regulating the reprogramming of TME, which affects the sensitivity of immunotherapy. Therefore, it is imperative to investigate the role of exosomes in TME reprogramming and the impact of exosomes on immunotherapy. Here, we review the communication role of exosomes in regulating TME remodeling and the efficacy of immunotherapy, as well as summarize the underlying mechanisms. Furthermore, we also introduce the potential application of the artificially modified exosomes as the delivery systems of antitumor drugs. Further efforts in this field will provide new insights on the roles of exosomes in intercellular communications of TME and cancer progression, thus helping us to uncover effective strategies for cancer treatment. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Exclusive decay of P-wave Bottomonium into double J/\psi

Author

Zhang, Juan, Dong, Hairong, and Feng, Feng

Subjects
High Energy Physics - Phenomenology
Abstract

We calculate the order-v^2 relativistic correction of J/\psi, including electromagnetic correction, to \chi_{bJ}-> J/\psi J/\psi, in the framework of NRQCD factorization formula. The relativistic order-v^2 effect is found to increase the lower-order prediction for the decay width by about 10%, while the electromagnetism contribution is very small about 0.2% for \chi_{b0} and \chi_{b2}. The total branching ratios are predicted to be of order 10^{-5} for \chi_{b0,b2}-> J/\psi J/\psi, but 10^{-11} for \chi_{b1}-> J/\psi J/\psi, since there is only electromagnetism contribution in this channel. We predict it is possible to observe these reactions in LHC. Finally, we estimate the decay width and branch ratio of \chi_{cJ}-> \omega\omega,\phi\phi) in the constituent quark model by our formula at the leading-order of relativistic correction and electromagnetic correction. The obtained branch ratio of \chi_{c0,2}-> \phi\phi is in agreement with the experimental measurement in the order of magnitude., Comment: 16 pages, 2 figures, published version. arXiv admin note: text overlap with arXiv:0912.5498 and arXiv:hep-ph/0611130v2

Published
2011
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22. Deterministic Reinforcement Learning Consensus Control of Nonlinear Multi-Agent Systems via Autonomous Convergence Perception

Author

Gao, Shigen, Xu, Chaoan, and Dong, Hairong

Abstract

This brief addresses an approximate optimal consensus control problem for multi-agent systems (MAS) using an autonomous perception empowered deterministic reinforcement learning scheme. An autonomous perception module is designed to online detect the convergence of NNs and tracking performance, and determine proper time moments that reinforcement learning (RL)-based method can be switched to deterministic RL (DRL) mode with constant NNs weight vectors, saving computing resources and reducing computational amount for devices equipped on MAS. Furthermore, once non-convergence of NNs or consensus errors is detected again, the designed autonomous perception module would switch DRL back to RL mode without chattering in the closed-loop system, though switch behaviour and non-smooth function are involved. Simulation results are finally presented to demonstrate the effectiveness.

Published
2024
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28. CPT Model-Based Prediction of the Temporal and Spatial Distributions of Passenger Flow for Urban Rail Transit under Emergency Conditions

Author

Li, Wei, Zhou, Min, and Dong, Hairong

Subjects
Machine vision -- Analysis, Transportation industry
Abstract

Emergencies have a significant impact on the passenger flow of urban rail transit. It is of great practical significance to accurately predict the urban rail transit passenger flow and carry out research on its temporal and spatial distributions under emergency conditions. Urban rail transit operating units currently use video surveillance information mainly to process emergencies and rarely use computer vision technology to analyze passenger flow information collected. Accordingly, this paper proposes a passenger flow-based temporal and spatial distribution model for urban rail transit emergencies based on the CPT. First, this paper clarifies the categories and classification of urban rail transit emergencies, analyzes the factors affecting passenger route selection, and establishes a generalized travel cost model for passengers under emergencies. Second, this paper establishes a passenger route choice behavior model for urban rail transit based on the cumulative prospect theory. Finally, taking Beijing as an example, this paper analyzes passenger travel behavior under emergencies based on multiple logistic regression models and analyzes the impact of emergencies on rail transit travel behavior. The research results show that the cumulative prospect theory can better describe the route choice behavior of rail transit passengers under emergencies than the existing models, and this model is of great significance for handling urban rail transit emergencies. The model proposed in this paper can provide a theoretical basis for the government and relevant departments to formulate traffic management measures., Author(s): Wei Li [1]; Min Zhou (corresponding author) [1]; Hairong Dong [1] 1. Introduction Urban rail transit, which is intensifying, is characterized by fast speed, large capacity, high efficiency, and [...]

Published
2020
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31. Formation Control for Virtual Coupling Trains With Parametric Uncertainty and Unknown Disturbances

Author

Xi, Wang, Hu, Mingyao, Wang, Hongwei, Dong, Hairong, and Ying, Zhipeng

Abstract

In this brief, a sliding mode control strategy is proposed to achieve the formation control for virtual coupling trains. Different from existing moving block based train control system, the headway between consecutive train sets is dynamically adjusted with respect to the velocity of the preceding train instead of just maintaining a large constant safe margin. By considering the uncertainty of the train model and external disruptions with unknown bound, the established formation control law can drive the position tracking error and the speed tracking error of the virtually coupled train sets to a predesigned sliding surface, and asymptotically converge to the equilibrium point. Meanwhile, estimations of the unknown train parameters and the bound of unknown external disturbances are derived on-line simultaneously. Simulation results are provided to demonstrate the effectiveness of the proposed strategy.

Published
2023
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34. Output tracking control of strict‐feedback non‐linear systems under asymmetrically bilateral and time‐varying full‐state constraints

Author

Bin Ning, Dong Hairong, Lingbin Ning, Shigen Gao, and Sun Yawen

Subjects
0209 industrial biotechnology, Control and Optimization, Adaptive control, Computer science, Control (management), Linear system, Estimator, 02 engineering and technology, Computer Science Applications, Human-Computer Interaction, Nonlinear system, 020901 industrial engineering & automation, Control and Systems Engineering, Control theory, Bounded function, Backstepping, State (computer science), Electrical and Electronic Engineering
Abstract

The state feedback output tracking control problem is investigated for a class of uncertain non-linear strict-feedback system subject to asymmetrically bilateral and time-varying full-state constraints. Non-linear mapping is employed to deal with full-state constraints and the system is transformed into an uncertain pure-feedback system. For the transformed system, an approximation-free backstepping control scheme is proposed by using performance function rather than employing any estimator. It is shown that the proposed control strategy can guarantee that all signals in the closed-loop system are bounded and the tracking errors can be made arbitrarily small by choosing proper control gains. Meanwhile, the states are set within the asymmetrically bilateral and time-varying full-state constraints. At last, two simulation examples are obtained to demonstrate the feasibility and effectiveness of the proposed control algorithm wherein the practical system for metro is considered.

Published
2020

35. Progress of Laser Processing Technology in Ferroelectric Nanocomposites.

Author

Ding, Haijuan, Fan, Yaping, Dong, Hairong, Zhao, Chengtao, and Zhao, Debiao

Subjects
FERROELECTRIC polymers, POLYMERIC nanocomposites, NANOCOMPOSITE materials, OPTICAL control, POLYVINYLIDENE fluoride, COMPOSITE materials
Abstract

Although polymer-based nanocomposites have great application potential in many fields, compared with the application of ferroelectric nanocomposites in functional microscale structures and devices, especially in the field of photonics microdevices fabricated by laser processing, the development of polymer-based nanocomposites is relatively lagging behind. In this study, the polyvinylidene fluoride ferroelectric composite material was taken as the research object, and the preparation method of polymer nanocomposite material suitable for laser microstructure processing was solved by exploring the material functionalization method. The control of the optical properties of polyvinylidene fluoride ferroelectric composites was achieved through material design, control of the size of nanoparticles in the prepared polymer nanocomposites, and characterization of their structures and properties. Two-dimensional and three-dimensional structures of polymer nanocomposites were prepared by laser microstructure processing technology, and the optical properties of the microstructures were evaluated. When the applied stress field was zero, the macroscopic coercive field was larger, and the hystereswas loop was wider, while the butterfly curve changed rapidly near the coercive field, and the strain was negative. From the test results of the scanning electron microscope, it can be concluded that the lowest average power to find ablation traces was 0.06 mw, and the affected area was very small, and there was no damage to the surrounding nanotubes. Therefore, this paper believes that the damage threshold of carbon nanotubes was slightly less than 0.06 mw. This study contributes to the development of nanocomposite preparation methods for laser micromachining. [ABSTRACT FROM AUTHOR]

Published
2022
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38. Sharing Traffic Priorities via Cyber–Physical–Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse

Author

Li, Bai, Cao, Dongpu, Tang, Shiqi, Zhang, Tantan, Dong, Hairong, Wang, Yaonan, and Wang, Fei-Yue

Abstract

Replacing traffic signals with roadside vehicle-to-infrastructure systems in the era of connected and autonomous vehicles (CAVs) is promising. Managing CAVs in a signal-free intersection, known as autonomous intersection management (AIM), controls the driving behavior of each intersection-traverse CAV to maximize the throughput. Although AIM improves the gross throughput, the fairness of each individual vehicle in its right of way is not seriously considered. This study sets up an AIM system in the cyber–physical–social space to trade traverse priorities quantitatively and fairly. To that end, one needs an AIM method that is optimal and stable, otherwise no convincing trades of traverse priorities could be made. This study proposes a near-optimal lane-free AIM method based on numerical optimal control, wherein log-exp functions are deployed to convexify nondifferentiable collision-avoidance constraints. Besides that, a parameterized social force model (SFM) is proposed to provide a tunable initial guess for numerical optimal control. By tuning the urgency weights in SFM, one may get cooperative trajectories in different homotopy classes, which are further utilized to decide the amount of virtual currency to reward those CAVs who tend to share their traverse priorities. The overall method improves the traverse throughput with individual fairness respected. In experiencing this system, passengers learn how to behave with politeness when they drive manually. Experiments show the efficiency and robustness of the AIM method and also show the efficacy of the overall priority-sharing system.

Published
2023
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39. Propagation and safety analysis of the train‐to‐train communication system

Author

Eckehard Schnieder, Haifeng Song, Wei Wu, and Dong Hairong

Subjects
Structure (mathematical logic), Carrier signal, Computer science, Carry (arithmetic), 020208 electrical & electronic engineering, Real-time computing, 020206 networking & telecommunications, System safety, 02 engineering and technology, Petri net, Communications system, Task (project management), 0202 electrical engineering, electronic engineering, information engineering, Train, Electrical and Electronic Engineering
Abstract

Smart railway transportation systems aim to make the trains operate in a more intelligent and flexible manner. Reliable train-to-train communication, which can increase the efficiency and safety of the train operation, is getting more concern in recent researches, and different communication solutions can be applied to carry out the data communication. However, its propagation and safety analysis is not systematically put forward. In this work, the structure and working principle of a train-to-train communication system are proposed. In order to have a better performance, multi-communication channels are involved. Three different modems are applied to make sure that the system can implement the communication task in different situations. What is more, the long-range communication modem provides not only long distance communication but also distance measurement between two trains. The propagation analysis based on different carrier waves and application scenarios is discussed. The system safety is evaluated by means of Petri nets, and the analysis procedure can be reused for analysing different system structures.

Published
2019

41. Nonlinear mapping‐based feedback technique of dynamic surface control for the chaotic PMSM using neural approximation and parameter identification

Author

Dong Hairong, Tao Tang, Bin Ning, Yidong Li, and Shigen Gao

Subjects
Lyapunov function, 0209 industrial biotechnology, Approximation theory, Control and Optimization, Artificial neural network, Computer science, Chaotic, 02 engineering and technology, 01 natural sciences, Computer Science Applications, System dynamics, Human-Computer Interaction, Nonlinear system, symbols.namesake, 020901 industrial engineering & automation, Control and Systems Engineering, Control theory, Backstepping, 0103 physical sciences, symbols, Electrical and Electronic Engineering, Synchronous motor, 010301 acoustics
Abstract

This study presents a novel non-linear mapping-based feedback technique for controlling chaotic permanent magnet synchronous motor (PMSM) using dynamic surface control (DSC), neural approximation and parameter identification. Neural networks are utilised to online approximating the unknown system dynamics, adaptive parameter identification is designed to estimate the unknown parameter, and DSC technique circumvents the problem of `explosion of complexity' in the traditional backstepping methodology. The major feature of the non-linear mapping-based feedback technique lies in that the merits of high-gain and low-gain control are synthesised by virtue of a novel non-linear continuous differentiable mapping feedback function, and a novel non-quadratic Lyapunov function is used to analyse the closed-loop system stability caused by the compound function of non-linear feedback. Finally, unprejudiced comparative results are given to demonstrate the effectiveness and advantages of the proposed control scheme.

Published
2018

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