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    Sealing Performance of Pressure-Adaptive Seal
    LI Yuanfeng (李元丰), WANG Yiling (王怡灵), ZHANG Wanxin∗ (张万欣), LIU Jinian (刘冀念), MA Jialu (马加炉)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 747-756.   DOI: 10.1007/s12204-022-2510-x
    Abstract395)      PDF (2268KB)(161)      
    A pressure-adaptive seal is developed to meet the demands of quick assembling and disassembling for an individual protection equipment in aerospace. The analysis model, which reflects the main characteristics of the seal structure, is built based on the finite element method and the Roth’s theory of rubber seal, and verified by the prototype test. The influences of precompression ratio, hardness of the sealing ring rubber, and friction coefficient on the sealing performance are investigated by variable parameter method. Results show that the model can describe the essential characteristics of the pressure-adaptive seal structure, which has good follow-up to the cavity pressure to achieve the purpose of pressure self-adaptive. The leakage rate correlates negatively with the precompression ratio of the sealing ring and the hardness of the sealing ring material, while is positively related to the friction coefficient between the sealing ring and the sealing edge. The maximum contact stress on sealing surface has negative correlation with the precompression ratio of the sealing ring, and positive correlation with the hardness of the seal ring material. The damage risk of the sealing ring increases with the increases of the precompression ratio of sealing ring, hardness of sealing ring material, and friction coefficient.
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    Travel Intention of Electric Vehicle Sharing based on Theory of Multiple Motivations
    BAO Lewen (鲍乐雯), MIAO Rui, ∗ (苗 瑞), CHEN Zhihua (陈志华), ZHANG Bo (张 博), GUO Peng (郭 鹏), MA Yuze (马宇泽)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 1-9.   DOI: 10.1007/s12204-023-2563-5
    Abstract268)      PDF (467KB)(107)      
    Determining the travel intention of residents with shared electric vehicles (EVs) is significant for promoting the development of low-carbon transportation, considering that common problems such as high idle rate and lack of attractiveness still exist. To this end, a structural equation model (SEM) based on the theory of multiple motivations is proposed in this paper. First, the influencing motivations for EV sharing are divided into three categories: consumer-driven, program-driven, and enterprise-driven motivations. Then, the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire. Finally, an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention. The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention, compared to program-driven motivations with impact weights from ?0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06. In terms of consumer-driven motivations, the weight of green travel awareness is the highest. The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident, enterprise, and government.
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    Automatic Removal of Multiple Artifacts for Single-Channel Electroencephalography
    ZHANG Chenbei (张晨贝), SABOR Nabil, LUO Junwen (罗竣文), PU Yu (蒲 宇), WANG Guoxing (王国兴), LIAN Yong∗ (连 勇)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 437-451.   DOI: 10.1007/s12204-021-2374-5
    Abstract190)      PDF (2934KB)(98)      
    Removing different types of artifacts from the electroencephalography (EEG) recordings is a critical step in performing EEG signal analysis and diagnosis. Most of the existing algorithms aim for removing single type of artifacts, leading to a complex system if an EEG recording contains different types of artifacts. With the advancement in wearable technologies, it is necessary to develop an energy-efficient algorithm to deal with different types of artifacts for single-channel wearable EEG devices. In this paper, an automatic EEG artifact removal algorithm is proposed that effectively reduces three types of artifacts, i.e., ocular artifact (OA), transmission- line/harmonic-wave artifact (TA/HA), and muscle artifact (MA), from a single-channel EEG recording. The effectiveness of the proposed algorithm is verified on both simulated noisy EEG signals and real EEG from CHB- MIT dataset. The experimental results show that the proposed algorithm effectively suppresses OA, MA and TA/HA from a single-channel EEG recording as well as physical movement artifact.
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    Physical Characterization of Ionic Liquid-Modified Polyvinyl Alcohol and Sodium Thiocyanate Polymer Electrolytes for Electrochemical Double-Layer Capacitor Application
    AZEMTSOP Manfo Theodore , MEHRA Ram Mohan , KUMAR Yogesh , GUPTA Meenal
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 161-171.   DOI: 10.1007/s12204-021-2397-y
    Abstract235)      PDF (1140KB)(94)      
    Novel gel polymer electrolytes (GPEs) composed of polyvinyl alcohol (PVA) and sodium thiocyanate were developed via a solution casting technique. An ionic liquid (IL), 1-ethyl-3-methyl-imidazolium tricyanomethanide ([EMIM][TCM]), was doped into a polymer–salt complex system (PVA + NaSCN) to further enhance the conductivity. IL-doped polymer electrolyte (ILDPE) films were characterized using X-ray diffraction (XRD), polarized optical microscopy (POM), Fourier-transform infrared (FTIR) spectroscopy, and conductivity measurements. XRD was performed to check the degree of crystallinity and amorphicity of the ILDPE films, and the amorphicity of GPEs increased with the increase of the IL content. POM was employed to evaluate the changes in the surface morphology due to the inclusion of salt and IL in the PVA. The compositional nature of the GPE films was examined via FTIR studies. The electrical and electrochemical properties were characterized by cyclic voltammetry and electrochemical impedance spectroscopy. The maximum conductivity for the GPE film was estimated to be 1.10 × 10-5 S/cm for 6% (mass fraction) of IL in the polymer–salt complex. The ionic transference number was approximately 0.97. An electrochemical double-layer capacitor (EDLC) was built from optimized GPE films and reduced graphene oxide-based electrodes. The specific capacitance calculated from the cyclic voltammograms of the EDLC cells was 3 F/g.
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    Adaptive Human-Robot Collaboration Control Based on Optimal Admittance Parameters
    YU Xinyi (禹鑫燚), WU Jiaxin (吴加鑫), XU Chengjun (许成军), LUO Huizhen (罗惠珍), OU Linlin∗ (欧林林)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 589-601.   DOI: 10.1007/s12204-022-2460-3
    Abstract224)      PDF (1674KB)(91)      
    In order to help the operator perform the human-robot collaboration task and optimize the task performance, an adaptive control method based on optimal admittance parameters is proposed. The overall control structure with the inner loop and outer loop is first established. The tasks of the inner loop and outer loop are robot control and task optimization, respectively. Then an inner-loop robot controller integrated with barrier Lyapunov function and radial basis function neural networks is proposed, which makes the robot with unknown dynamics securely behave like a prescribed robot admittance model sensed by the operator. Subsequently, the optimal parameters of the robot admittance model are obtained in the outer loop to minimize the task tracking error and interaction force. The optimization problem of the robot admittance model is transformed into a linear quadratic regulator problem by constructing the human-robot collaboration system model. The model includes the unknown dynamics of the operator and the task performance details. For relaxing the requirement of the system model, the integral reinforcement learning is employed to solve the linear quadratic regulator problem. Besides, an auxiliary force is designed to help the operator complete the specific task better. Compared with the traditional control scheme, the security performance and interaction performance of the human-robot collaboration system are improved. The effectiveness of the proposed method is verified through two numerical simulations. In addition, a practical human-robot collaboration experiment is carried out to demonstrate the performance of the proposed method.
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    Further Result on the Observer Design for One-Sided Lipschitz Systems
    YANG Ming1 (杨 明), HUANG Jun1∗ (黄 俊), ZHANG Wei2 (章 伟)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 817-822.   DOI: 10.1007/s12204-020-2252-6
    Abstract142)      PDF (328KB)(80)      
    This paper investigates the problem of observer design for a class of control systems. Different from current works, the nonlinear functions in the system only satisfy the property of the one-sided Lipschitz (OSL) condition but not quadratic inner-boundedness (QIB). Moreover, the case where the OSL constant is negative is specially investigated. Firstly, a full-order observer is constructed for the original system. Then, a reduced-order observer is also designed by using the decomposition method. The advantage and effectiveness of the proposed design scheme are shown in a numerical simulation.
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    Ant Colony Algorithm Path Planning Based on Grid Feature Point Extraction
    LI Erchao∗ (李二超), QI Kuankuan (齐款款)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 86-99.   DOI: 10.1007/s12204-023-2572-4
    Abstract134)      PDF (1196KB)(77)      
    Aimed at the problems of a traditional ant colony algorithm, such as the path search direction and field of view, an inability to find the shortest path, a propensity toward deadlock and an unsmooth path, an ant colony algorithm for use in a new environment is proposed. First, the feature points of an obstacle are extracted to preprocess the grid map environment, which can avoid entering a trap and solve the deadlock problem. Second, these feature points are used as pathfinding access nodes to reduce the node access, with more moving directions to be selected, and the locations of the feature points to be selected determine the range of the pathfinding field of view. Then, based on the feature points, an unequal distribution of pheromones and a two-way parallel path search are used to improve the construction efficiency of the solution, an improved heuristic function is used to enhance the guiding role of the path search, and the pheromone volatilization coefficient is dynamically adjusted to avoid a premature convergence of the algorithm. Third, a Bezier curve is used to smooth the shortest path obtained. Finally, using grid maps with a different complexity and different scales, a simulation comparing the results of the proposed algorithm with those of traditional and other improved ant colony algorithms verifies its feasibility and superiority.
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    Airframe Damage Region Division Method Based on Structure Tensor Dynamic Operator
    CAI Shuyu∗ (蔡舒妤), SHI Lizhong (师利中)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 757-767.   DOI: 10.1007/s12204-022-2498-2
    Abstract191)      PDF (1607KB)(76)      
    In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region, the airframe damage region division method based on the structure tensor dynamic operator is proposed in this paper. The structure tensor feature space is established to represent the local features of damage images. It makes different damage images have the same feature distribution, and transform varied damage region division into consistent process of feature space division. On this basis, the structure tensor dynamic operator generation method is designed. It integrates with bacteria foraging optimization algorithm improved by defining double fitness function and chemotaxis rules, in order to calculate the parameters of dynamic operator generation method and realize the structure tensor feature space division. And then the airframe damage region division is realized. The experimental results on different airframe structure damage images show that compared with traditional threshold division method, the proposed method can improve the division quality. The interference of damage adjacent region is eliminated. The information loss caused by over-segmentation is avoided. And it is efficient in operation, and consistent in process. It also has the applicability to different types of structural damage.
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    Construction on Aerodynamic Surrogate Model of Stratospheric Airship
    QIN Pengfei (秦鹏飞), WANG Xiaoliang∗ (王晓亮)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 768-779.   DOI: 10.1007/s12204-022-2494-6
    Abstract167)      PDF (3866KB)(54)      
    Stratospheric airship can stay at an altitude of 20 km for a long time and carry various loads to achieve long-term stable applications. Conventional stratospheric airship configuration mainly includes a low-resistance streamline hull and inflatable “X”-layout fins that realize the self-stabilization. A fast aerodynamic predictive method is needed in the optimization design of airship configuration and the flight performance analysis. In this paper, a predictive surrogate model of aerodynamic parameters is constructed for the stratospheric airship with “X” fins based on the neural network. First, a geometric shape parameterized model, and a flow field parameterized model were established, and the aerodynamic coefficients of airships with different shapes used as the training and test samples were calculated based on computational fluid dynamics (SA turbulence model). The improved Bayesian regularized neural network was used as the surrogate model, and 20 types of airships with different shapes were used to test the effectiveness of network. It showed that the correlation coefficients of Cx, Cy, Cz, CM,x, CM,y, CM,z were 0.928 7, 0.991 7, 0.991 9, 0.958 2, 0.986 1, 0.984 2, respectively. The aerodynamic coefficient distribution contour at different angles of attack and sideslip angles is used to verify the reliability of the method. The method can provide an effective way for a rapid estimation of aerodynamic coefficients in the airship design.
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    Multi-UAV Route Re-Generation Method Based on Trajectory Data
    YUAN Dongdong (袁冬冬), WANG Yankai∗ (王彦恺), BAI Jiaqi (白嘉琪)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 806-816.   DOI: 10.1007/s12204-021-2332-2
    Abstract116)      PDF (1409KB)(47)      
    A large quantity of unmanned aerial vehicle (UAV) trajectory data related to air traffic information has important value in engineering fields. However, the cost of data and trajectory processing limits the applications, and as the number of UAVs increases rapidly, future UAVs’ path data will be very large. Therefore, this paper designs a multi-UAV route re-generation method based on trajectory data, which can realize the UAVs’ path data compression, de-aggregation, and regeneration tasks. Based on the trajectory data, the three-dimensional Douglas-Peucker algorithm is used to compress the trajectory data to reduce the storage space. The improved B-spline path smoothing algorithm based on the reversing control point is used to depolymerize and smooth the path. Simulation experiments show that the above multi-UAV route re-generation algorithm can obtain a more optimized path while maintaining the important characteristics of the original path.
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    Reliability Evaluation of Two-Phase Degradation Process with a Fuzzy Change-Point
    LIU Kai1 (刘 凯), DANG Wei1 (党 炜), ZOU Tianji1,2∗ (邹田骥), LÜ Congmin1 (吕从民), LI Peng1,2 (李 鹏), ZHANG Haitao1 (张海涛)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 867-872.   DOI: 10.1007/s12204-021-2323-3
    Abstract139)      PDF (484KB)(47)      
    For some products, degradation mechanisms change during testing, and therefore, their degradation patterns vary at different points in time; these points are called change-points. Owing to the limitation of measurement costs, time intervals for degradation measurements are usually very long, and thus, the value of change-points cannot be determined. Conventionally, a certain degradation measurement is selected as the change-point in a two-phase degradation process. According to the tendency of the two-phase degradation process, the change-point is probably located in the interval between two neighboring degradation measurements, and it is a fuzzy variable. The imprecision of the change-point may lead to the incorrect product’s reliability evaluation results. In this paper, based on the fuzzy theory, a two-phase degradation model with a fuzzy change-point and a statistical analysis method are proposed. First, a two-phase Wiener degradation model is developed according to the membership function of the change-point. Second, the reliability evaluation is carried out using maximum likelihood estimation and a fuzzy simulation approach. Finally, the proposed methodology is verified via a case study. The results of the study show that the proposed methodology can achieve more believable reliability evaluation results compared with those of the conventional approach.
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    Action-aware Encoder-Decoder Network for Pedestrian Trajectory Prediction
    FU Jiawei∗ (傅家威), ZHAO Xu (赵 旭)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 20-27.   DOI: 10.1007/s12204-023-2565-3
    Abstract150)      PDF (775KB)(46)      
    Accurate pedestrian trajectory predictions are critical in self-driving systems, as they are fundamental to the response- and decision-making of ego vehicles. In this study, we focus on the problem of predicting the future trajectory of pedestrians from a first-person perspective. Most existing trajectory prediction methods from the first-person view copy the bird’s-eye view, neglecting the differences between the two. To this end, we clarify the differences between the two views and highlight the importance of action-aware trajectory prediction in the first-person view. We propose a new action-aware network based on an encoder-decoder framework with an action prediction and a goal estimation branch at the end of the encoder. In the decoder part, bidirectional long short-term memory (Bi-LSTM) blocks are adopted to generate the ultimate prediction of pedestrians’ future trajectories. Our method was evaluated on a public dataset and achieved a competitive performance, compared with other approaches. An ablation study demonstrates the effectiveness of the action prediction branch.
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    Strength-Toughness Improvement of 15-5PH Stainless Steel by Double Aging Treatment
    TE Rigele (特日格乐), ZHANG Yutuo, ∗ (张玉妥)
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 270-279.   DOI: 10.1007/s12204-021-2390-5
    Abstract149)      PDF (3166KB)(46)      
    To obtain better strength-toughness balance of 15-5PH stainless steel, a double aging treatment is proposed to investigate the mechanical properties and microstructure evolution. In this study, Cu precipitates and reversed austenite played a determining role to improve strength-toughness combination. The microstructure was observed using electron backscattered diffraction, transmission electron microscopy and scanning transmission electron microscopy. The volume fractions of Cu precipitates and reversed austenite were calculated with Thermo-Calc software and measured by X-ray diffraction. The results showed that the reversed austenite is formed at the martensitic lath boundaries and its volume fraction also increases with the increase of the aging temperature. At the same time, the size of the Cu precipitates gradually increases. Compared with the traditional single aging and double aging treatment, double aging treatment of 15-5PH stainless steel can increase the toughness while retaining the necessary strength. During double aging of 550 ℃ × 4 h + 580 ℃ × 1 h, 15-5PH stainless steel has the best strength and low-temperature (- 40 ℃) toughness match. Its yield strength, ultimate tensile strength and the Charpy impact energy are 1.037 GPa, 1.086 GPa and 179 J, respectively.
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    Low Voltage Indium-Oxide-Zinc Thin Film Transistor Gated by KH550 Solid Electrolyte
    DONG Qian (董 钱), GUO Liqiang(郭立强), WANG Weilin (王伟琳), CHENG Guanggui (程广贵)
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 186-191.   DOI: 10.1007/s12204-022-2421-x
    Abstract93)      PDF (763KB)(46)      
    With the development of integrate circuit and artificial intelligence, many kinds of transistors have been invented. In recent years, wide attention has been paid to the oxide thin film transistors due to its ease preparation, low cost, and suitability for mass production. Traditionally used gate dielectric film (such as silicon dioxide film) in oxide thin film transistor owns low dielectric constant, which leads to weak capacitive coupling between the gate dielectric layer and the channel layer. As a result, high voltage (10 V or more) needs to be applied on the gate electrode in order to achieve the purpose of regulating the current of channel layer. Therefore, new oxide thin film needs to be developed. In this work, silane coupling agents (3-triethoxysilypropyla-mine) KH550 solid electrolyte film was obtained by spin coating-process. The KH550 solid electrolyte was used as gate dielectric layer to fabricate low-voltage indium zinc oxide thin film transistor. The surface topography and thickness of KH550 solid electrolyte film were characterized by atomic force microscope and field emission scanning electron microscope, respectively. The capacitance-frequency curve of the sample was measured by impedance analyzer (Soloartron 1260A), and the electrical characteristics of the sample were analyzed by a semiconductor parameter analyzer (Keithley 4200 SCS). A maximum specific capacitance of about 7.3 μF/cm2 is obtained at 1 Hz. The transistor shows a good stability of pulse operation and negative bias voltage, the operation voltage is only 2 V, the current on/off ratio is about 1.24 × 106, and the subthreshold swing is 169.2 mV/dec. The development of KH550 solid electrolyte gate dielectric provides a novel way for the research of oxide thin film transistor.
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    Generation Approach of Human-Robot Cooperative Assembly Strategy Based on Transfer Learning
    LÜ Qibing (吕其兵), LIU Tianyuan (刘天元), ZHANG Rong (张荣), JIANG Yanan (江亚南), XIAO Lei (肖雷), BAO Jingsong∗ (鲍劲松)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 602-613.   DOI: 10.1007/s12204-022-2493-7
    Abstract167)      PDF (3845KB)(45)      
    In current small batch and customized production mode, the products change rapidly and the personal demand increases sharply. Human-robot cooperation combining the advantages of human and robot is an effective way to solve the complex assembly. However, the poor reusability of historical assembly knowledge reduces the adaptability of assembly system to different tasks. For cross-domain strategy transfer, we propose a human-robot cooperative assembly (HRCA) framework which consists of three main modules: expression of HRCA strategy, transferring of HRCA strategy, and adaptive planning of motion path. Based on the analysis of subject capability and component properties, the HRCA strategy suitable for specific tasks is designed. Then the reinforcement learning is established to optimize the parameters of target encoder for feature extraction. After classification and segmentation, the actor-critic model is built to realize the adaptive path planning with progressive neural network. Finally, the proposed framework is verified to adapt to the multi-variety environment, for example, power lithium batteries.
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    Fabrication and Characterization of Graphene-Enhanced Hollow Microlattice Materials
    BAO Haisheng (鲍海生), LIU Longquan∗ (刘龙权)
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 192-196.   DOI: 10.1007/s12204-021-2339-8
    Abstract83)      PDF (662KB)(44)      
    A method was developed and proposed to fabricate graphene-enhanced hollow microlattice materials, which include the three-dimensional (3D) printing, nanocomposite electroless plating, and polymer etching technologies. The surface morphology and uniformity of as-deposited coatings were systematically characterized and analyzed. Moreover, the mechanical properties of the microlattices were investigated through quasi-static compression tests. The results demonstrated that a uniform Nickel-phossphorous-graphene (Ni-P-G) coating was obtained successfully, and the specific modulus and strength were increased by adding graphene into the microlattice materials. The optimal mass concentration of graphene nanoplatelets was obtained after comparing the specific modulus and strength of the materials with different densities of graphene, and the strength mechanism was discussed.
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    Path Planning and Optimization of Humanoid Manipulator in Cartesian Space
    LI Shiqi (李世其), LI Xiao∗ (李肖), HAN Ke (韩可), XIONG Youjun (熊友军), XIE Zheng (谢铮), CHEN Jinliang (陈金亮)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 614-620.   DOI: 10.1007/s12204-022-2416-7
    Abstract214)      PDF (1591KB)(41)      
    To solve the problems of low efficiency and multi-solvability of humanoid manipulator Cartesian space path planning in physical human-robot interaction, an improved bi-directional rapidly-exploring random tree algorithm based on greedy growth strategy in 3D space is proposed. The workspace of manipulator established based on Monte Carlo method is used as the sampling space of the rapidly-exploring random tree, and the opposite expanding greedy growth strategy is added in the random tree expansion process to improve the path planning efficiency. Then the generated path is reversely optimized to shorten the length of the planned path, and the optimized path is interpolated and pose searched in Cartesian space to form a collision-free optimized path suitable for humanoid manipulator motion. Finally, the validity and reliability of the algorithm are verified in an intelligent elderly care service scenario based on Walker2, a large humanoid service robot.
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    Semantic Segmentation-Based Road Marking Detection Using Around View Monitoring System
    XU Hanqing (徐汉卿), YANG Ming∗ (杨 明), DENG Liuyuan (邓琉元), LI Hao (李 颢), WANG Chunxiang, (王春香), HAN Weibin (韩伟斌), YU Yuelong (于跃龙)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 833-843.   DOI: 10.1007/s12204-021-2401-6
    Abstract126)      PDF (1134KB)(41)      
    Road marking detection is an important branch in autonomous driving, understanding the road information. In recent years, deep-learning-based semantic segmentation methods for road marking detection have been arising since they can generalize detection result well under complicated environments and hold rich pixel-level semantic information. Nevertheless, the previous methods mostly study the training process of the segmentation network, while omitting the time cost of manually annotating pixel-level data. Besides, the pixel-level semantic segmentation results need to be fitted into more reliable and compact models so that geometrical information of road markings can be explicitly obtained. In order to tackle the above problems, this paper describes a semantic segmentation-based road marking detection method using around view monitoring system. A semiautomatic semantic annotation platform is developed, which exploits an auxiliary segmentation graph to speed up the annotation process while guaranteeing the annotation accuracy. A segmentation-based detection module is also described, which models the semantic segmentation results for the more robust and compact analysis. The proposed detection module is composed of three parts: vote-based segmentation fusion filtering, graph-based road marking clustering, and road-marking fitting. Experiments under various scenarios show that the semantic segmentation-based detection method can achieve accurate, robust, and real-time detection performance.
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    Air Combat Assignment Problem Based on Bayesian Optimization Algorithm
    FU Lia (傅 莉), LONG Xia∗ (龙 洗), HE Wenbinb (何文斌)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 799-805.   DOI: 10.1007/s12204-021-2270-z
    Abstract123)      PDF (519KB)(40)      
    In order to adapt to the changing battlefield situation and improve the combat effectiveness of air combat, the problem of air battle allocation based on Bayesian optimization algorithm (BOA) is studied. First, we discuss the number of fighters on both sides, and apply cluster analysis to divide our fighter into the same number of groups as the enemy. On this basis, we sort each of our fighters’ different advantages to the enemy fighters, and obtain a series of target allocation schemes for enemy attacks by first in first serviced criteria. Finally, the maximum advantage function is used as the target, and the BOA is used to optimize the model. The simulation results show that the established model has certain decision-making ability, and the BOA can converge to the global optimal solution at a faster speed, which can effectively solve the air combat task assignment problem.
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    Synthesis and Characterization of Copper Doped Zinc Oxide Thin Films Deposited by RF/DC Sputtering Technique
    KHAN Mohibul, ALAM Md. Shabaz, AHMED Sk. Faruque∗
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 172-179.   DOI: 10.1007/s12204-022-2462-1
    Abstract120)      PDF (698KB)(39)      
    Undoped and copper (Cu) doped zinc oxide (Zn1-xCuxO, where x = 0—0.065) nano crystal thin films have been deposited on glass substrate via RF/DC reactive co-sputtering technique. The aim of this work is to investigate the crystal structure of ZnO and Cu doped ZnO thin films and also study the effect of Cu doping on optical band gap of ZnO thin films. The identification and confirmation of the crystallinity, film thickness and surface morphology of the nano range thin films are confirmed by using X-ray diffractometer (XRD), scanning electron microscope and atomic force microscope. The XRD peak at a diffractive angle of 34.44° and Miller indices at (002) confirms the ZnO thin films. Crystallite size of undoped ZnO thin films is 27 nm and decreases from 27 nm to 22 nm with increasing the atomic fraction of Cu (xCu) in the ZnO thin films from 0 to 6.5% respectively, which is calculated from XRD (002) peaks. The different bonding information of all deposited films was investigated by Fourier transform infrared spectrometer in the range of wave number between 400 cm-1 to 4 000 cm-1. Optical band gap energy of all deposited thin films was analyzed by ultraviolet visible spectrophotometer, which varies from 3.35 eV to 3.19 eV with the increase of xCu from 0 to 6.5% respectively. Urbach energy of the deposited thin films increases from 115 meV to 228 meV with the increase of xCu from 0 to 6.5% respectively.
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    Lidar-Visual-Inertial Odometry with Online Extrinsic Calibration
    MAO Tianyang (茅天阳), ZHAO Wentao (赵文韬), WANG Jingchuan∗ (王景川), CHEN Weidong (陈卫东)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 70-76.   DOI: 10.1007/s12204-023-2570-6
    Abstract115)      PDF (988KB)(39)      
    To achieve precise localization, autonomous vehicles usually rely on a multi-sensor perception system surrounding the mobile platform. Calibration is a time-consuming process, and mechanical distortion will cause extrinsic calibration errors. Therefore, we propose a lidar-visual-inertial odometry, which is combined with an adapted sliding window mechanism and allows for online nonlinear optimization and extrinsic calibration. In the adapted sliding window mechanism, spatial-temporal alignment is performed to manage measurements arriving at different frequencies. In nonlinear optimization with online calibration, visual features, cloud features, and inertial measurement unit (IMU) measurements are used to estimate the ego-motion and perform extrinsic calibration. Extensive experiments were carried out on both public datasets and real-world scenarios. Results indicate that the proposed system outperforms state-of-the-art open-source methods when facing challenging sensor-degenerating conditions.
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    Non-Line-of-Sight Multipath Detection Method for BDS/GPS Fusion System Based on Deep Learning
    SU Hong1 (苏 红), WU Bozhao2 (吴博钊), MAO Xuchu1∗ (茅旭初)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 844-854.   DOI: 10.1007/s12204-022-2430-9
    Abstract109)      PDF (3108KB)(38)      
    Non-line-of-sight (NLOS) multipath effect is the main factor that restricts the application of global navigation satellite system (GNSS) in complex environments, especially in urban canyon. The effective avoidance of NLOS signals can significantly improve the positioning performance of GNSS receiver. In this paper, an NLOS/LOS classification model based on recurrent neural network is proposed to classify satellite signals received in urban canyon environments. The accuracy of classification is 91%, and the recognition rate of NLOS is 89%; the classification performance is better than that of traditional machine learning classification models such as support vector machine. For BeiDou navigation satellite system/global positioning system (BDS/GPS) fusion system, the least square algorithm and extended Kalman filter are used to estimate the position. The experimental results show that the three-dimensional positioning accuracy after NLOS recognition is improved about 60% on average compared with the traditional methods, and the positioning stability is also improved significantly.
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    Data Driven Model-Free Adaptive Control Method for Quadrotor Trajectory Tracking Based on Improved Sliding Mode Algorithm
    YUAN Dongdong (袁冬冬), WANG Yankai∗ (王彦恺)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 790-798.   DOI: 10.1007/s12204-020-2254-4
    Abstract127)      PDF (1004KB)(37)      
    In order to solve the problems of dynamic modeling and complicated parameters identification of trajectory tracking control of the quadrotor, a data driven model-free adaptive control method based on the improved sliding mode control (ISMC) algorithm is designed, which does not depend on the precise dynamic model of the quadrotor. The design of the general sliding mode control (SMC) algorithm depends on the mathematical model of the quadrotor and has chattering problems. In this paper, according to the dynamic characteristics of the quadrotor, an adaptive update law is introduced and a saturation function is used to improve the SMC. The proposed control strategy has an inner and an outer loop control structures. The outer loop position control provides the required reference attitude angle for the inner loop. The inner loop attitude control ensures rapid convergence of the attitude angle. The effectiveness and feasibility of the algorithm are verified by mathematical simulation. The mathematical simulation results show that the designed model-free adaptive control method of the quadrotor is effective, and it can effectively realize the trajectory tracking control of the quadrotor. The design of the controller does not depend on the kinematic and dynamic models of the unmanned aerial vehicle (UAV), and has high control accuracy, stability, and robustness.
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    Effect of Moving Endwall on Hub Leakage Flow of Cantilevered Stator in a Linear Compressor Cascade
    ZHENG Biaojie (郑标颉), MA Yuchen (马宇晨), TENG Jinfang∗ (滕金芳), JU Zhenzhou (居振州), ZHU Mingmin (朱铭敏)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 780-789.   DOI: 10.1007/s12204-022-2468-8
    Abstract127)      PDF (2018KB)(36)      
    The cantilevered stator has the advantages of reducing mass and axial length of highly loaded compressor. The details of the hub leakage flow resulting from the clearance between the high-speed moving hub and the cantilevered stator hub are unclear. In this paper, the effect of a moving endwall on the hub leakage flow of a cantilevered stator in a linear compressor cascade was studied. After the simulation method was verified with the experimental results, the time-averaged results of unsteady Reynolds averaged Navier-Stokes (URANS) were selected to study a case with a hub clearance of 2 mm. The results show that the effect of the moving endwall of the cantilevered cascade on the general characteristics with below 30% span increases the leakage mass flow rate and reduces the static pressure coefficient at three conditions of 0°, 6°, and -7° incidences, and the change is most significant at -7° incidence. The effect of the moving endwall on the total pressure loss coefficient varies with different operating conditions, which decreases by 15.94% at 0° incidence, and increases by 4.77% and 18.51% at 6° incidence and -7° incidence, respectively. The influence of the moving endwall is below 14% span at -7° incidence, below 23% span at 0° incidence, and below 30% span at 6° incidence. These effects correspond to the static pressure coefficient and the difference of static pressure coefficient representing the blade loading. In designing the cantilevered stator and matching between the stages of a multistage compressor, the quantitative research results of this paper have certain guiding significance.
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    Design of a Low Respiratory Resistance Mask for COVID-19
    YANG Pufan (杨朴凡), HUANG Hongxin (黄洪鑫) WEI Siji (卫思霁), YAO Yuan (姚 远), ZHANG Zhinan∗ (张执南)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 543-551.   DOI: 10.1007/s12204-022-2434-5
    Abstract109)      PDF (1382KB)(35)      
    Observational evidence suggests that mask-wearing mitigates transmission of COVID-19; at the same time high respiratory resistance leads to an unwillingness to wear masks. This paper proposed a respiratory drive structure to reduce the air resistance of a mask. This structure provides different shapes during expiration and inspiration while focusing on filtering dust, bacteria, or viruses. Meanwhile, the assembled system on the mask can be disassembled and replaced. Then porous media simulation is used to verify the model effect. Experimental results of a new mask show that the ventilation resistance is reduced by 20%, and the bacterial filtration efficiency meets the requirements of YY 0469—2011.
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    Impact Angle/Time Constraint Guidance Design Based on Fast Terminal Error Dynamics
    QIN Xuesheng (秦雪升), LIU Yuanhe (刘远贺), LI Kebo (黎克波), LIANG Yangang∗ (梁彦刚)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 823-832.   DOI: 10.1007/s12204-022-2509-3
    Abstract121)      PDF (532KB)(34)      
    Considering the problem that the optimal error dynamics can only converge at the terminal time, an impact angle/time constraint missile guidance law with finite-time convergence is designed in this paper, which is based on the pure proportional navigation (PPN) guidance law and the fast terminal error dynamics (FTED) approach. The missile guidance model and FTED equation are given first, and the dynamic equation of impact angle/time error based on PPN is also derived. Then, the guidance law is designed based on FTED, and the guidance error can converge to 0 in a finite time. Furthermore, considering the field of view constraint, the guidance law is improved by using the saturation function mapping method. Finally, a numerical simulation example is given to verify the effectiveness of the guidance law, which shows that the guidance law proposed in this paper can make the missile quickly adjust to the desired states in advance, and effectively relieve the overload saturation pressure of the actuator.
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    Birds-Eye-View Semantic Segmentation and Voxels Semantic Segmentation Based on Frustum Voxels Modeling and Monocular Camera
    QIN Chao1 (秦 超), WANG Yafei1 (王亚飞), ZHANG Yuchao2 (张宇超), YIN Chengliang1∗ (殷承良)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 100-113.   DOI: 10.1007/s12204-023-2573-3
    Abstract107)      PDF (3885KB)(34)      
    The semantic segmentation of a bird’s-eye view (BEV) is crucial for environment perception in autonomous driving, which includes the static elements of the scene, such as drivable areas, and dynamic elements such as cars. This paper proposes an end-to-end deep learning architecture based on 3D convolution to predict the semantic segmentation of a BEV, as well as voxel semantic segmentation, from monocular images. The voxelization of scenes and feature transformation from the perspective space to camera space are the key approaches of this model to boost the prediction accuracy. The effectiveness of the proposed method was demonstrated by training and evaluating the model on the NuScenes dataset. A comparison with other state-of-the-art methods showed that the proposed approach outperformed other approaches in the semantic segmentation of a BEV. It also implements voxel semantic segmentation, which cannot be achieved by the state-of-the-art methods.
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    Intelligent Driving Assistance System for Safe Expressway Driving in Rainy and Foggy Weather based on IoT
    YAN Beirui (燕北瑞), FANG Cheng (方 成), QIU Hao (邱 昊), ZHU Wenfeng∗ (朱文峰)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 10-19.   DOI: 10.1007/s12204-023-2564-4
    Abstract157)      PDF (2162KB)(32)      
    The feature bends and tunnels of mountainous expressways are often affected by bad weather, specifically rain and fog, which significantly threaten expressway safety and traffic efficiency. In order to solve this problem, a vehicle–road coordination system based on the Internet of Things (IoT) is developed that can share vehicle–road information in real time, expand the environmental perception range of vehicles, and realize vehicle–road collaboration. It helps improve traffic safety and efficiency. Further, a vehicle–road cooperative driving assistance system model is introduced in this study, and it is based on IoT for improving the driving safety of mountainous expressways. Considering the influence of rain and fog on driving safety, the interaction between rainfall, water film, and adhesion coefficient is analyzed. An intelligent vehicle–road coordination assistance system is constructed that takes in information on weather, road parameters, and vehicle status, and takes the stopping sight distance model as well as rollover and sideslip model as boundary constraints. Tests conducted on a real expressway demonstrated that the assistance system model is helpful in bad weather conditions. This system could promote intelligent development of mountainous expressways.
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    Deformable Registration Algorithm via Non-subsampled Contourlet Transform and Saliency Map
    CHANG Qing∗ (常 青), YANG Wenyou (杨文友), CHEN Lanlan (陈兰岚)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 452-462.   DOI: 10.1007/s12204-022-2428-3
    Abstract113)      PDF (4867KB)(31)      
    Medical image registration is widely used in image-guided therapy and image-guided surgery to esti- mate spatial correspondence between planning and treatment images. However, most methods based on intensity have the problems of matching ambiguity and ignoring the influence of weak correspondence areas on the overall registration. In this study, we propose a novel general-purpose registration algorithm based on free-form defor- mation by non-subsampled contourlet transform and saliency map, which can reduce the matching ambiguities and maintain the topological structure of weak correspondence areas. An optimization method based on Markov random fields is used to optimize the registration process. Experiments on four public datasets from brain, car- diac, and lung have demonstrated the general applicability and the accuracy of our algorithm compared with two state-of-the-art methods.
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    Event-Triggered Control of Positive Semi-Markovian Jump Systems Without/with Input Saturation
    ZHANG Suhuan (张素焕), ZHANG Junfeng∗ (张俊锋), LI Shuo (李烁), YU Shanen (余善恩)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 723-736.   DOI: 10.1007/s12204-021-2335-z
    Abstract85)      PDF (1038KB)(31)      
    This paper is concerned with the event-triggered control of positive semi-Markovian jump systems without/with input saturation. The considered systems are subject to a stochastic semi-Markovian process whose sojourn time is dependent on a non-exponential distribution. First, an event-triggering condition is introduced in a linear form for the systems. A class of event-triggered feedback controllers is proposed using matrix decomposition technique. By using a stochastic co-positive Lyapunov function, the systems’ positivity and stability are guaranteed. Then, the obtained results are developed for the systems with input saturation. A cone set is chosen as the attraction domain and the corresponding attraction domain gain matrix is designed in terms of standard linear programming approach. Finally, two numerical examples are provided to verify the validity and effectiveness of the presented theoretical findings.
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    Gram Matrix-Based Convolutional Neural Network for Biometric Identification Using Photoplethysmography Signal
    WU Caiyu, (吴彩钰), SABOR Nabil, ZHOU Shihong, (周世鸿), WANG Min, (王 敏), YING Liang (应 亮), WANG Guoxing∗ (王国兴)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 463-472.   DOI: 10.1007/s12204-022-2426-5
    Abstract158)      PDF (1049KB)(30)      
    As a kind of physical signals that could be easily acquired in daily life, photoplethysmography (PPG) signal becomes a promising solution to biometric identification for daily access management system (AMS). State- of-the-art PPG-based identification systems are susceptible to the form of motions and physical conditions of the subjects. In this work, to exploit the advantage of deep learning, we developed an improved deep convolutional neural network (CNN) architecture by using the Gram matrix (GM) technique to convert time-serial PPG signals to two-dimensional images with a temporal dependency to improve accuracy under different forms of motions. To ensure a fair evaluation, we have adopted cross-validation method and “training and testing” dataset splitting method on the TROIKA dataset collected in ambulatory conditions. As a result, the proposed GM-CNN method achieved accuracy improvement from 69.5% to 92.4%, which is the best result in terms of multi-class classification compared with state-of-the-art models. Based on average five-fold cross-validation, we achieved an accuracy of 99.2%, improved the accuracy by 3.3% compared with the best existing method for the binary-class.
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    Case Study of a Personalized Scoliosis Brace Based on 3D Printing
    LU Dezhi 1,2‡ (鲁德志), LI Wentao1‡ (李文韬), WANG Xiaowen2 (王孝文), SONG Yan2 (宋 艳), ZHANG Pingping2 (张萍萍), FENG Haiyang2 (冯海洋), WU Yuncheng1 (吴云成), XU Yuanjing3 (许苑晶), LI Tao4 (李 涛), MA Zhenjiang1∗ (马振江), WANG Jinwu1,2∗ (王金武)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 528-534.   DOI: 10.1007/s12204-022-2461-2
    Abstract132)      PDF (653KB)(30)      
    We evaluated the effect of a new type of brace (primary material 3300PA) for treating scoliosis, which was produced based on 3D printing technology combined with a non-contact optical mold-taking and computer- aided design. Through the production of a brace for a 13-year-old patient with adolescent idiopathic scoliosis by a multidisciplinary team, the digital design and 3D printing of a personalized scoliosis brace were introduced. Parameters such as the Cobb angle, angle of trunk inclination, spine-coronal plane balance parameters, sagittal vertical axis (SVA), and Scoliosis Research Society-22 score (SRS-22) were measured to evaluate the treatment effect of the brace. The model-taking process of the non-contact optical scanner was successful, data were valid, and personalized scoliosis brace made by the computer-aided design and 3D printing fitted well with the patient. Before wearing, immediate in-brace, and 6 months after wearing, the Cobb angles were 29?, 9?, a n d 1 4?, respectively. The offsets between the C7 vertebra plumb line (C7PL) and central sacral vertical line (CSVL) were 3.2 cm, 2.2 cm, and 2.1 cm, respectively. SVAs were 3.3 cm, 2.9 cm, and 0.3 cm, respectively. Apex vertebral translocations were 4.3 cm, 0.3 cm, and 0.1 cm, respectively. The SRS-22 was 76 before brace application and 91 at the 6-month follow-up. The spine curve returned to normal, and the correction effect was obvious. The scoliosis brace indicates the integration between digital medicine and 3D printing technology, which has personalization and customization as advantages. The brace has good wearing comfort, invisibility, and orthopedic function, follows the psychological needs of teenagers, improves patients’ compliance, and improves the correction of the deformity.
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    Indoor Vehicle Positioning Based on Multi-Sensor Data Fusion
    WANG Mingyang (王明阳), SHI Liangren∗ (时良仁), LI Yuanlong (李元龙)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 77-85.   DOI: 10.1007/s12204-023-2571-5
    Abstract123)      PDF (705KB)(30)      
    This study proposes a Kalman filter-based indoor vehicle positioning method for cases in which the steering angle and rotation speed of the vehicle’s wheels are unknown. By fusing the position and velocity data from the ultra-wideband sensors and acceleration and orientation data from the inertial measurement unit, we developed two algorithms to estimate the real-time position of the vehicle based on a linear Kalman filter and extended Kalman filter, respectively. We then conducted simulations and experiments to examine the performances of the algorithms. In the experiment, the Kalman filtering hyperparameters are configured, and we then ran the two algorithms to determine the positioning precision and accuracy with the ground truth produced via LiDAR. We verified that our method can improve precision and accuracy compared with the raw positioning data and can achieve desirable effects for indoor vehicle positioning when vehicles travel at low speeds.
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    Straight-Going Priority in Hierarchical Control Framework for Right-Turning Vehicle Merging Based on Cooperative Game
    YANG Jingwena (杨静文), ZHANG Libina (张立彬), WANG Pinga (王 萍), YAO Junfengb∗ (姚俊峰), ZHAO Xiangmob (赵祥模)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 150-160.   DOI: 10.1007/s12204-023-2577-z
    Abstract87)      PDF (997KB)(29)      
    With the development of connected and automated vehicles (CAVs), forming strategies could extend from the typically used first-come-first-served rules. It is necessary to consider passing priorities when crossing intersections to prevent conflicts. In this study, a hierarchical strategy based on a cooperative game was developed to improve safety and efficiency during right-turning merging. A right-turn merging conflict model was established to analyze the right-turning vehicle characteristics of the traffic flow. The proposed three-layered hierarchical strategy includes a decision-making layer, a task layer, and an operation layer. A decision-making-layer cooperative game strategy was used to determine the merging priority of straight-going traffic and right-turning flows. In addition, a task-layer cooperative game strategy was designed for the merging sequence. A modified consensus algorithm was utilized to optimize the speed of vehicles in the virtual platoon of the operation layer. Traffic simulations were performed on the PYTHON-SUMO integrated platform to verify the proposed strategy. The simulation results show that, compared with other methods, the proposed hierarchical strategy has the shortest travel time and loss time and performs better than other methods when the straight-going traffic flow increases during right-turning merging at the intersection. The proposed method shows superiority under a significant traffic flow with a threshold of 900 vehicle/(h · lane). This satisfactory application of right-turning merging might be extended to ramps, lane-changing, and other scenarios in the future.
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    Spatial Temporal Correlation 3D Vehicle Detection and Tracking System with Multiple Surveillance Cameras
    XUE Weipeng (薛炜彭), WU Minghu (吴明虎), WANG Lin∗ (王 琳)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 52-60.   DOI: 10.1007/s12204-023-2567-1
    Abstract88)      PDF (1375KB)(29)      
    Compared to 3D object detection using a single camera, multiple cameras can overcome some limitations on field-of-view, occlusion, and low detection confidence. This study employs multiple surveillance cameras and develops a cooperative 3D object detection and tracking framework by incorporating temporal and spatial information. The framework consists of a 3D vehicle detection model, cooperatively spatial-temporal relation scheme, and heuristic camera constellation method. Specifically, the proposed cross-camera association scheme combines the geometric relationship between multiple cameras and objects in corresponding detections. The spatial-temporal method is designed to associate vehicles between different points of view at a single timestamp and fulfill vehicle tracking in the time aspect. The proposed framework is evaluated based on a synthetic cooperative dataset and shows high reliability, where the cooperative perception can recall more than 66% of the trajectory instead of 11% for single-point sensing. This could contribute to full-range surveillance for intelligent transportation systems.
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    Meso-Scale Tearing Mechanism Analysis of Flexible Fabric Composite for Stratospheric Airship via Experiment and Numerical Simulation
    CHEN Yonglin (陈永霖), YANG Weidong (杨伟东), XIE Weicheng (谢炜程), WANG Xiaoliang (王晓亮), FU Gongyi∗ (付功义)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 873-884.   DOI: 10.1007/s12204-022-2431-8
    Abstract80)      PDF (4194KB)(29)      
    Stratospheric airships are controllable lighter-than-air aircraft and have great potential application in surveillance and communication. The envelopes, one of the main structures of a stratospheric airship, are generally made of flexible fabric composites to be lightweight, high strength, capable of containing lifting gas, and resistant to the harsh stratospheric environment. The composites, however, are prone to tearing. Hence, their tearing behavior has attracted great attention. This paper explores the meso-scale tearing mechanism of an envelope and the temperature influence on its tear strength via experiment and numerical simulation. Biaxial tear tests were conducted on cruciform specimens, which were contacted with liquids (cold alcohol or hot water) at different temperatures including -25, 20, 50, 80 °C. The specimens’ tear stresses were measured and the meso-scale tearing behavior was captured with a microscope. Besides, a novel finite element analysis model based on truss and spring elements was established to simulate the tearing behavior. It was found that the simulation result has a relative agreement with the tests. The simulation results show that the maximum tear stress of the envelope drops by 39.62% as the temperature rises from -60 °C to 80 °C and the tensile properties of yarns and matrix account for stress concentration around a crack tip. This work deeply reveals the meso-scale tearing mechanism of the envelope and provides a valuable reference for exploring tearing properties of flexible fabric composites.
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    Game Theory Based Sensor Management in Reducing Target Threat Level Assessment Risk
    PANG Ce∗ (庞策), SHAN Ganlin (单甘霖)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 649-659.   DOI: 10.1007/s12204-021-2372-7
    Abstract138)      PDF (822KB)(28)      
    Sensor management schemes are calculated to reduce target threat level assessment risk in this paper. Hidden Markov model and risk theory are combined to build the target threat level model firstly. Then the target threat level estimation risk is defined. And the sensor management schemes are optimized with the smallest target threat level assessment risk. What’s more, the game theory is applied to calculate the optimal sensor management scheme. Some simulations are conducted to prove that the proposed sensor management method is effective.
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    Research on Real-time Dynamic Evaluation of Highway Passenger Service Satisfaction Based on Internet
    LUO Jing1 (罗 京), ZHOU Dai1∗ (周 岱), TAN Yunlong2 (谭云龙), XIA Ganlin3 (夏甘霖), ZHAO Guohua4,5 (赵国华)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 39-51.   DOI: 10.1007/s12204-023-2568-0
    Abstract102)      PDF (556KB)(28)      
    The current method of evaluating passenger satisfaction primarily adopts the traditional static evaluation mode, which can hardly satisfy the dynamic regulatory requirements of highway passenger transport service quality set by industry management departments. In this paper, we summarize the characteristics of real-time dynamic evaluation under the requirements of hierarchical and classified evaluation and analyze the entire process of the one-time travel service of highway passenger transport. We focus on station waiting and in-vehicle services, extract the elements most concerned by passengers as evaluation indexes, and construct a three-level index system. Subsequently, a multi-indicator comprehensive evaluation method based on the analytic hierarchy process and fuzzy comprehensive evaluation is selected to construct a comprehensive evaluation model. By combining with the development level of electronic ticket purchasing and the requirements of satisfaction evaluation, we propose three data collection methods and compare and analyze their strengths and weaknesses. Finally, based on actual survey data, the effectiveness of the model is verified. The verification results show that the real-time dynamic evaluation index system based on the Internet can better satisfy evaluation requirements.
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    Electric vehicle charging situation awareness for charging station ultra-short-term load forecast
    SHI Yiwei1 (史一炜), LIU Zeyu1 (刘泽宇), FENG Donghan1∗ (冯冬涵), ZHOU Yun1∗ (周 云), ZHANG Kaiyu2 (张开宇), LI Hengjie3 (李恒杰)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 28-38.   DOI: 10.1007/s12204-023-2566-2
    Abstract117)      PDF (1518KB)(27)      
    Electric vehicles (EVs) are expected to be key nodes connecting transportation–electricity–communication networks. Advanced automotive electronics technologies enhance EVs’ perception, computing, and communication capacity, which in turn can boost the operational efficiency of intelligent transportation systems (ITSs). EVs couple the ITS to the power system, providing a promising solution to charging congestion and transformer overload via navigation and forecasting approaches. This study proposes a privacy-preserving EV charging situation awareness framework and method to forecast the ultra-short-term load of charging stations. The proposed method only relies on public information from commercial service providers. In the case study, data are powered by the Baidu LBS cloud and EV-SGCC platform, and the experiment is conducted within an area of Pudong New District in Shanghai. Based on the results, the charging load of charging stations can be adequately forecasted more than 1 min ahead with low communication and computing power requirements. This research provides the basis for further studies on operation optimization and electricity market transaction of charging stations.
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    High-Performance Single-Side Fabricated (111)-Silicon Dual-Cantilever Accelerometer with Squeeze-Film Air Damping Modulation
    JIAO Ding (焦 鼎), NI Zao (倪 藻), WANG Jiachou (王家畴), LI Xinxin∗ (李昕欣)
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 197-206.   DOI: 10.1007/s12204-021-2288-2
    Abstract77)      PDF (1510KB)(27)      
    This study proposes a novel design and micromachining process for a dual-cantilever accelerometer. Comb and curved-surface structures are integrated into the sensing structure to modulate the squeeze-film damping, thus effectively optimizing the response frequency bandwidth. Owing to the high stress concentration on the dual-cantilever integrated with a fully sensitive piezoresistive Wheatstone bridge, a high sensitivity to acceleration is achieved. In addition, the dual-cantilever accelerometer is fabricated using a specifically developed low-cost and high-yield (111)-silicon single-side bulk-micromachining process. The test results show that the proposed dualcantilever accelerometer exhibits a sensitivity of 0.086—0.088 mV/g/3.3 V and a nonlinearity of ±(0.09%—0.23%) FS (full-scale). Based on dynamic characterization, an adequate frequency bandwidth of 2.64 kHz is verified. Furthermore, a resonant frequency of 4.388 kHz is measured, and a low quality factor (Q) of 7.62 is obtained, which agrees well with the design for air-damping modulation. The achieved high performance renders the proposed dual-cantilever accelerometer promising in applications such as automotive and consumer electronics.
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