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Research on Autonomous Grasping of a Humanoid Robot Based on Vision ZHANG Xuchong, YANG Jun Journal of South China University of Technology(Natural Science Edition)    2024, 52 (7): 53-61.   DOI: 10.12141/j.issn.1000-565X.230528 Abstract （8002）   HTML （20）    PDF（pc） （3170KB）（268）       Knowledge map    Save With the development of robotics technology, humanoid robots have shown application potential and value in multiple fields. Research on autonomous grasping of humanoid robots based on machine vision aims to improve their grasping adaptability and humanoid actions in natural environments. In terms of machine vision, the Realsense-D435 depth camera was adopted, and the YOLO (You Only Look Once) object detection model was used to achieve target object recognition, spatial positioning, depth map cropping, and target point cloud generation. The object’s posture was obtained based on the registration algorithm (ICP) between the target point cloud and the standard point cloud. The robot head was modeled using the D-H method, and the position and posture of the object were converted from the camera coordinate system to the robot coordinate system. In terms of motion planning, according to the grasping law of the human arm, the grasping process was divided into 9 basic actions: initial position, moving to the pre-grasping position, grasping the object, lifting the object, moving the object, moving to placement position placing the object, retreating position, and returning to the initial position. Corresponding grasping postures were determined for different objects to improve the success rate of grasping. Based on the grasping and placing points obtained visually, the remaining key points were calculated independently, and the spatial arc was used as the grasping trajectory. Through Matlab simulation, the rationality of the end movement trajectory and joint trajectory of the robotic arm during the grasping process was verified. Finally, an object grasping experiment was conducted, and the results showed that the humanoid robot can quickly and accurately recognize and locate different objects in the natural environment, and can successfully grasp and transport them with a success rate of over 80%. And it takes into account the imitation of human nature of the action, verifying the effectiveness of the proposed solution. This study can promote the application and popularization of humanoid robots in human daily life. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Trajectory Friction Compensation Algorithm for Robots Based on Velocity Control YE Bosheng, LI Siao, TAN Shuai, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (4): 51-58.   DOI: 10.12141/j.issn.1000-565X.230368 Abstract （3255）   HTML （4）    PDF（pc） （2377KB）（51）       Knowledge map    Save Currently, robots are extensively utilized in industrial manufacturing. However, due to the influence of joint friction and other factors in the robot system, the robot trajectory tracking accuracy is difficult to meet the requirements of high-precision production. In this study, a friction compensation control algorithm in speed mode was proposed to mitigate the impact of non-linear friction factors in the mechanical structure and unmodelled disturbances on the robot’s operational stability and machining precision. The optimal excitation trajectory was designed by a combination of Fourier series and fifth-order polynomial. Dynamic parameters were then pre-identified by the least squares method and iteratively optimized through the Levenberg-Marquardt method to establish a more precise robot dynamic model. Subsequently, the Lyapunov method was adopted to design the trajectory tracking control algorithm, and the joint angles collected in the steepest discrete tracking differentiator were fed into the control algorithm to calculate the real-time compensation. The compensation value was then applied in the robot, which effectively achieving friction compensation. The proposed algorithm was validated by employing a six-degree-of-freedom serial robot as an experimental subject. The results demonstrate that the trajectory tracking error is reduced by approximately 35%, as comparing with that under the non-compensation conditions, which confirms the efficacy of the algorithm in the realm of robot friction compensation. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Travel Carbon Emission Prediction Model Based on Resident Attribute Data SU Yuejiang, WEN Huiying, YUAN Minxian, WU Dexin, ZHOU Lulu, QI Weiwei Journal of South China University of Technology(Natural Science Edition)    2024, 52 (8): 23-33.   DOI: 10.12141/j.issn.1000-565X.230355 Abstract （3124）   HTML （7）    PDF（pc） （5415KB）（215）       Knowledge map    Save It is an important basis for precise formulation of transportation emission reduction measures to accurately analyze the importance of factors influencing residents’ travel mode and the sensitivity of carbon emissions. According to the comprehensive analysis of the influencing factors such as family attributes, personal attributes, travel attributes and environmental attributes of the residents’ travel survey, the prediction model of residents’ travel mode was constructed based on LightGBM (Light Gradient Boosting Machine) and verified. Combined with the travel activity level, the carbon emission coefficient of various energy types, the standard coal coefficient and other parameters, the travel carbon emission prediction model based on the resident attribute data was constructed. Finally, taking Guangzhou as an example, the carbon emission intensity and total amount of residents’ travel mode were predicted, and importance of factors influencing travel mode and sensitivity was analyzed.The results indicate that the carbon emission prediction model constructed based on the attribute data of residents can more accurately predict the carbon emission of various modes of travel, better analyze the importance and sensitivity of the influencing factors of carbon emission, and comprehensively reveal the relationship between travel behavior, travel mode and travel carbon emission. Among them, the distance between the start and the end and the nearest bus station or the distance from the nearest subway station, the cost of self-driving and travel distance are important factors affecting the choice of residents’ travel mode. The competitiveness of subway travel increases significantly with the decrease of distance when the distance between the starting and the end point and the nearest subway station drops by 55%. In the area with high density of bus stops, the distance between the start and the nearest bus station is not sensitive to residents’ travel mode choice. It is the turning point of the residents’ travel mode and carbon emission when the carbon emission cost increases by 400%. After passing the turning point, the car travel mode is difficult to transfer. The carbon emissions fell the fastest, with a maximum reduction of 90.4% when the reduction in travel distance was within 90%. Reference | Related Articles | Metrics | Comments（0）

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Calculation and Spatial Distribution Characteristics of Carbon Emissions from New Energy Vehicles on Expressways WEN Huiying, HE Ziqi, HU Yuqing, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (8): 1-13.   DOI: 10.12141/j.issn.1000-565X.230293 Abstract （2434）   HTML （12）    PDF（pc） （25804KB）（222）       Knowledge map    Save In order to overcome the difficulty in estimating the indirect carbon emissions from new energy vehicles due to the energy consumption in a large-scale expressway network, this paper proposes a new carbon emission calculation method of new energy vehicles based on the toll data in expressway ETC network. Firstly, the traffic flow data of new energy vehicles on expressways were cleansed and processed. Then, according to the distribution of toll gantries, road sections were defined and segmented. On this basis, the energy consumption of different types of new energy vehicles was analyzed. Furthermore, a carbon emission quantification model of new energy vehicles in the operational stage was established. Finally, by taking Guangdong Province as an example, the carbon emissions of new energy vehicles on expressways were calculated, with its spatial distribution characteristics being also analyzed. The results show that (1) Category 1 pure electric passenger cars are the main source of carbon emissions from new energy vehicles on expressways, accounting for 74.20% of the total carbon emissions of new energy vehicles, followed by Category 1 pure electric trucks, whose carbon emissions account for 14.18% of the total, and Category 1 plug-in hybrid passenger cars contribute 11.62% of the total; (2) the cities in the Pearl River Delta urban agglomeration are the main contributors to high carbon emissions from new energy vehicles, and the less developed regions in eastern, western and northern Guangdong account for less than 13% of the total carbon emissions from new energy vehicles; (3) the road segments with high carbon emissions from new energy vehicles mainly locate in the transportation hubs and inner-city expressway rings of developed cities, and Guangzhou metropolitan area as well as Shenzhen metropolitan area as the center has a radiating effect on the expressway network of surrounding cities; and (4) in less developed areas, due to the low density of expressway network and relatively lagging infrastructure, the penetration rate of new energy vehicles is low, the corresponding carbon emissions from new energy vehicles are generally low. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Experimental Study on Failure Mechanism of RC Frame Structures Based on Performance Design Method LING Yuhong, HUANG Qianyi, ZHOU Jing, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (11): 9-20.   DOI: 10.12141/j.issn.1000-565X.230648 Abstract （2148）   HTML （0）    PDF（pc） （5218KB）（22）       Knowledge map    Save To verify the rationality, reliability and fault tolerance of the “two-level and two-stage” seismic performance-based design method of Guangdong standard DBJ/T 15-92—2021 “Technical specification for concrete structures of high-rise buildings”, this study designed two batches of 1∶4 scale plane RC frame structure specimens with the same seismic structure grade of first-level, second-level and third-level. During loading, iron counterweights were arranged on each floor to simulate the distributed load, and the influence of floor and floor load on the failure mechanism of frame structure was considered. The test adopted displacement-controlled single-point loading. The loading point is located at the elevation of the three-story floor beam. Before the longitudinal reinforcement of the column reaches the yield strain, it is single-cycle loading, and after the yield, it is three-cycle loading. Through the pseudo-static test, the seismic failure mode and failure mechanism of the structure were investigated, and the evolution law of seismic performance indexes such as hysteresis curves, ductility, stiffness and energy dissipation was analyzed. The test results show that the plastic hinge development paths of the specimen damage are basically the same, which conforms to the failure mechanism of the plastic hinge ductility mechanism at the beam end. The specimen has no obvious shear failure characteristics, and the bearing capacity utilization coefficient ξ can meet the seismic design requirements of “strong shear and weak bending”. The hysteresis curves of the six frame structure specimens are full, and the seismic ductility coefficient ranges from 4.36 to 6.10. The maximum value range of equivalent viscous damping coefficient is 0.125~0.165, which shows good seismic energy dissipation performance. The floor slab improves the stiffness and bearing capacity of the frame beam, which has a significant impact on the seismic failure mechanism of the specimen. The specimen maintains the seismic failure characteristics of “strong column and weak beam”, and the component importance coefficient η can ensure the seismic design requirements of “strong column and weak beam”. The failure characteristics of the specimens are random, but the overall regularity of the failure mechanism is strong, and the gradient characteristics of the specimens with different seismic structural grades are obvious. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Lane-Changing Trajectory Planning Strategy for Autonomous Vehicles on Superhighways HE Yongming, XING Wanyu, WEI Kun, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (4): 104-113.   DOI: 10.12141/j.issn.1000-565X.230339 Abstract （2012）   HTML （10）    PDF（pc） （2783KB）（86）       Knowledge map    Save To improve the driving safety of autonomous vehicles on superhighways, this paper proposed a lane-changing trajectory planning strategy. Firstly, five polynomials were used to generate general lane-changing trajectory clusters, and the trajectory planning problem was quantified as the duration of solving lane-changing behavior with the limit of vehicle dynamics and surrounding traffic vehicles. Then, considering the constraints of vehicle dynamics, the vehicle dynamics model and Brush tire model were established. Based on the tire lateral force data of the established vehicle model, the tire lateral stiffness was solved, and the magic tire model was used to verify the tire lateral stiffness. Next, the phase plane of sideslip angle and yaw rate was introduced to obtain the safe driving envelope of high-speed vehicle. CarSim simulation training was carried out on given multiple groups of vehicle speeds and adhesion coefficients to determine the shortest lane-changing time that meets the vehicle dynamics constraints. Finally, considering the collision avoidance constraints with surrounding traffic vehicles, three typical lane-changing scenarios were analyzed. The shortest and longest lane-changing durations satisfying the collision avoidance requirements were determined based on the position of single obstacle vehicle, and the threshold model of lane-changing duration satisfying the safe lane-changing requirements was established. The multi-parameter safety lane-changing domain test shows that the established vehicle safety lane-changing duration boundary model can solve the safe and feasible lane-changing trajectory under the given parameters, provide trajectory reference for the superhighway lane-changing behavior, and improve the safety of the superhighway lane-changing behavior. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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A Small Sample Rolling Bearing Fault Diagnosis Method Based on Gramian Angular Difference Field and Generative Adversarial Network QIANG Ruiru, ZHAO Xiaoqiang Journal of South China University of Technology(Natural Science Edition)    2024, 52 (10): 64-75.   DOI: 10.12141/j.issn.1000-565X.240021 Abstract （2010）   HTML （13）    PDF（pc） （4151KB）（135）       Knowledge map    Save Aiming at the problem that deep learning-based rolling bearing fault diagnosis algorithms need to learn from a large amount of labeled data and face poor diagnosis effect when the number of samples is limited, this paper proposed a small-sample rolling bearing fault diagnosis method based on the Gramian angular difference field (GADF) and generative adversarial networks (GAN). Firstly, a data enhancement method based on GADF transform was proposed, and it converts a few 1D vibration signals into 2D GADF images by GADF transform. GADF subgraphs are obtained by cropping to obtain a large number of image samples. Then, a conditional generative adversarial network (CGAN) was combined with Wasserstein GAN with gradient penalty (WGAN-GP) to construct a novel generative adversarial network, which enhances the model training stability by conditional auxiliary information with gradient penalty and designs dynamic coordinate attention mechanism to enhance the spatial perception of the model, so as to generate high-quality samples. Finally, the generative samples were used to train the classifier, and the diagnosis results were obtained on the validation set. Two sets of bearing fault diagnosis experiments in a small sample environment were conducted using the Southeast University dataset and the Case Western Reserve University dataset, respectively. The results show that, compared with traditional generative adversarial networks as well as advanced small-sample fault diagnosis methods, the proposed method can obtain the best results in five fault diagnosis metrics, including accuracy and precision, and can accurately diagnose the type of bearing faults under small-sample conditions. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Multi-Task Assisted Driving Policy Learning Method for Autonomous Driving LUO Yutao, XUE Zhicheng Journal of South China University of Technology(Natural Science Edition)    2024, 52 (10): 31-40.   DOI: 10.12141/j.issn.1000-565X.230503 Abstract （1862）   HTML （14）    PDF（pc） （3027KB）（211）       Knowledge map    Save With the development of autonomous driving technology, deep reinforcement learning has become an important means to realize the efficient driving policy learning. However, the implementation of autonomous driving is faced with the challenges brought by the complex and changeable traffic scenes, and the existing deep reinforcement learning methods have the problems of single scene adaptation ability and slow convergence speed. To address these issues and to improve the scene adaptability and policy learning efficiency of autonomous vehicles, this paper proposed a multi-task assisted driving policy learning method. Firstly, this method constructed the encoder-multi-task decoder module based on the deep residual network, squeezing high-dimensional driving scenes into low-dimensional representations, and adopted multi-task-assisted learning of semantic segmentation, depth estimation and speed prediction to improve the scene information richness of low-dimensional representations. Then, the low-dimensional representation was used as the state input to build a decision network based on reinforcement learning, and the multi-constraint reward function was designed to guide the learning of driving strategies. Finally, simulation experiments were conducted in CARLA. The experimental results show that, compared to classic methods such as DDPG and TD3, the proposed method improves the training process through multi-task assistance and learns better driving policies. It achieves higher task success rates and driving scores in several typical urban driving scenarios such as roundabouts and intersections, demonstrating excellent decision-making capabilities and scene adaptability. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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TsGAN-Based Automatic Generation Algorithm of Lane-Change Cut-in Test Scenarios on Expressways for Autonomous Vehicles ZHU Yu, XU Zhigang, ZHAO Xiangmo, WANG Runmin, QU Xiaobo Journal of South China University of Technology(Natural Science Edition)    2024, 52 (8): 76-88.   DOI: 10.12141/j.issn.1000-565X.230229 Abstract （1829）   HTML （7）    PDF（pc） （3981KB）（207）       Knowledge map    Save The event wherein vehicles from the adjacent lane execute a lane-change maneuver, cutting into the lane occupied by autonomous vehicles, epitomizes a typical high-risk scenario on expressways within the domain of autonomous driving. Replicating such scenarios for testing on actual expressways involves significant safety risks. Virtual simulation test is one of the best approaches to addressing this issue. In order to automatically generate mass high-fidelity expressway lane-change cut-in test scenarios, this paper presents an automatic generation algorithm of lane-change cut-in test scenarios for autonomous vehicles based on TsGAN (Time-Series Generative Adversarial Network). In this algorithm, the time headway and lateral gap at the cut-in moment are taken as the evaluation metrics for scenario risk assessment, and 2 853 instances of lane-change cut-in scenarios with four different risk levels are extracted from the real expressway trajectory dataset highD. A model for generating lane-change cut-in test scenarios is established based on TsGAN, and is trained with the extracted real trajectory data. Then, the model is employed to generate the trajectories for the lane-change vehicle and the tested vehicle before the cut-in moment. To authenticate the generated trajectories, the distribution similarity and spectral error between the generated and the real trajectories are compared. Furthermore, an in-depth analysis of the kinematic interplay between the two vehicles at the cut-in moment and the distribution of trajectory parameters in the generated scenarios is performed to validate the coverage of the generated scenarios within naturalistic settings. The findings can be summarized as follows: (1) as illustrated by the distribution of key trajectory parameters, the average similarity between the generated and the real lane-change trajectories is 79.7%, with an average spectral error less than 8%, and more than 83.2% of the generated trajectories are within the buffer of the most analogous real trajectories, indicating a notable fidelity of the generated trajectories; (2) as compared with the collected real scenarios, the generated instances exhibit a more expansive coverage and a more even distribution within parameter intervals, and the time headway and lateral gap between the lane-change vehicle and the tested vehicle at the cut-in moment decrease by 17.83% and 16.37% in average, respectively, the distribution range of trajectory parameters expands by 19.44%, signifying a heightened coverage of the generated scenarios; and (3) the proposed TsGAN-based generation model has the capability of emulating lane-change cut-in test scenarios with four different risk levels, exhibiting pronounced specificity. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Study on Internal Stress of Asphalt Mixture Under Three-Point Bending Mode WANG Wei, TAN Yiqiu, XU Yongjiang Journal of South China University of Technology(Natural Science Edition)    2024, 52 (10): 101-111.   DOI: 10.12141/j.issn.1000-565X.240102 Abstract （1713）   HTML （11）    PDF（pc） （5042KB）（113）       Knowledge map    Save The bending and tensile properties of asphalt mixture affect the service quality and life of asphalt pavement, and its internal stress determines the bending and tensile performance. In order to investigate the internal stress characteristics of asphalt mixtures, this paper adopted the discrete element method to quantitatively evaluate the force chains of each component in asphalt mixtures under the three-point bending mode. Firstly, it constructed a template library of coarse aggregates based on image recognition and realized efficient three-dimensional modeling of asphalt mixture specimen and proposed a three-point bending simulation method. Then the internal force chain distribution of asphalt mixture was visually represented, and data of force chains of each component were extracted. The force chain characteristics were analyzed from the three aspects of composition, strength, and angle. The results show that under the three-point bending mode, the internal force chain field of asphalt mixture exhibits tension and compression zones, and the extrusion of aggregates only takes effect in the compressed zone. 70.8% of the internal contact force of SMA 13 asphalt mixture is provided by the asphalt mortar, and that of AC13 asphalt mixture is 83.2%, indicating that coarse aggregates have little effect under bending and tensile stress and asphalt mortar plays a major role in resisting external loads. The proportion of force chains decrease as the strength increased, and the proportion of strong force chains in the interior of the mortar and the mortar-aggregate interface position is basically the same. The stress between coarse aggregates is uneven, and the mortar plays a significant role in ensuring uniform stress within the asphalt mixture. The strength of horizontal force chains at the aggregate-mortar interface is slightly higher than that in the vertical direction, and the strength of aggregate force chains fluctuates greatly with the change of angle. Asphalt mortar bears the main load during bending and tensile force of asphalt mixture and the research findings can serve as a reference for the structural design and performance evaluation of asphalt mixtures. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Study on the Impact Characteristics of Horizontal Curve Elements on Carbon Emissions from Passenger Car Operation WANG Xiaofei, LUO Zhen, WANG Shaohua, PAN Ling, ZENG Qiang Journal of South China University of Technology(Natural Science Edition)    2025, 53 (2): 68-79.   DOI: 10.12141/j.issn.1000-565X.240047 Abstract （1114）   HTML （3）    PDF（pc） （2493KB）（7）       Knowledge map    Save China’s “14th Five-Year Plan” places higher demands on green transportation development, with emissions from traffic operations being the primary source of carbon emissions in the transportation sector. To investigate the factors influencing carbon emissions of passenger cars on highway curved segments, this study conducted on-site driving tests using OBD-equipped vehicles to collect driving data from typical curved road segments in Guangdong Province, and obtains carbon emission data through the IPCC carbon emission accounting method. Re-levant evaluation indicators influencing passenger car emissions were selected based on road alignment, and gray relational analysis was used to calculate the correlations between these indicators. The results indicate that among the geometric alignment elements of horizontal curve sections, indicators such as the proportion of transition curve length and transition curve parameters are significantly correlated with the segmental carbon emission rate. The radius of the circular curve is also significantly correlated within a specific range. For non-geometric factors, indicators such as the standard deviation and mean of acceleration show significant correlations with carbon emissions, and these two indicators are further associated with geometric factors like transition curve parameters and the proportion of transition curve length. Based on the results of the grey relational analysis, eight correlated indicators were selected, and a grey GM(1, N) model was developed to predict the total carbon emissions of passenger cars on horizontal curve sections. The prediction results show an average relative error of 5.10% compared to the actual values. The predictive performance of the model surpasses that of traditional multiple regression models, demonstrating outstanding performance and reliability in scenarios with limited data.The findings of this study can identify key design and operational parameters significantly influencing carbon emissions, providing a theoretical basis for the low-carbon optimization and management of highway horizontal curve sections. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Seismic Performance of Hoop Head Tenon Timber Joint with Added Corner Dampers CHEN Qingjun, LEI Jun, LI Bingzhou, ZUO Zhiliang, CAI Jian Journal of South China University of Technology(Natural Science Edition)    2024, 52 (7): 119-134.   DOI: 10.12141/j.issn.1000-565X.230658 Abstract （1050）   HTML （8）    PDF（pc） （12990KB）（112）       Knowledge map    Save To provide theoretical basis for the restoration of Guangfu wooden structures, five hoop head tenon joint specimens were designed and manufactured using Merbau wood. Considering the influence of the size of mortise and tenon construction, quasi-static tests were carried out on undamaged and unreinforced joint specimens. Then, to preserve the original appearance of the building as much as possible, the damaged joint specimens mentioned above were reinforced by the Queti-type dampers that have minimal influence on the original appearance of the structure. Finally, quasi-static tests were conducted again on the reinforced joints to investigate the difference in their seismic performance and the strengthening effect of the dampers. The results show that the joint specimens reinforced with dampers exhibit significant indentations at the mortise and tenon connections when being loaded to failure. There is noticeable splitting on the outer side of the tenon of the beam and the detachment of the tenon, as well as obvious separation between the rubber and steel plate at the base of the damper. The addition of dampers to joints can compensate the decrease in force-bearing performance caused by initial damage, provide better post-damage stiffness for the damaged mortise and tenon joints, and enhance the ultimate load-bearing capacity and energy absorption capacity. After adding the damper, there occur enhancements in terms of post-damage stiffness, load-bearing capacity and energy absorption of specimens, as compared with the unreinforced joints, with the increment being more than 18%, 19% and 20%, respectively. Moreover, on the basis of the existing simplified mechanical model and in combination with OpenSees, a macro-modelling method was proposed for hoop head tenon timber structures, which helps to obtain hysteresis curves of the joints being in good agreement with the experimental results, meaning that the modelling method can effectively simulate the hysteresis energy dissipation characteristics of the hoop head tenon joints strengthened with dampers. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Identification of Hazardous Driving Hotspots of Conventional Urban Bus Based on Spatial Autocorrelation ZHANG Wenhui, LIU Tuo, SONG Yajing, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (4): 138-150.   DOI: 10.12141/j.issn.1000-565X.230026 Abstract （488）   HTML （0）    PDF（pc） （12362KB）（39）       Knowledge map    Save In order to obtain the spatial distributing characteristics of hazardous bus driving status, this paper identified the spatial clustering through spatial autocorrelation analysis, determined the hot spots, and analyzed the significant influencing factors. Firstly, the study collected position system data samples of the urban buses for one week in each of the four quarters and modified the duplicate, abnormal and missing data. Bus stops were used as nodes to divide spatial spots, and every spot was numbered. Over speed, urgent acceleration, urgent deceleration and sharp turn were identified as hazardous driving status. The four conditions thresholds were obtained according to the kinematic characteristics of vehicles. The study calculated statistical indicators and global Moran’s Ig of four conditions. The results show that hazardous driving status are spatially clustered (probability of a spatial random distribution p < 0.01, standard deviation score Z > 2.58). Over speed has most significant characteristic of spatial clustering (Ig = 0.731). The study performed local spatial autocorrelation analysis for the four conditions. According to the analysis, local Moran’ s I scatter plots and LISA clustering plots are plotted at 90%, 95% and 99% confidence levels. The hazardous hot spots of urban buses were obtained combining with city maps. Finally, the study selected 9 factors such as road length, number of lanes and straightness to formulate models. The compare and analysis were performed to get the fitting goodness of OLS, SLE, SEM and SDM model. The SDM model was used to obtain the significant influencing factors for 4 dangerous driving states. The results can provide a theoretical basis for supervising the safety operation and identifying the hazardous driving status of urban buses in spatial perspective. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Online Driving Style Recognition Method Considering Lane-Changing Game ZHANG Yunchao, HUANG Jianling, LI Yongxing, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (4): 126-137.   DOI: 10.12141/j.issn.1000-565X.230159 Abstract （365）   HTML （4）    PDF（pc） （7635KB）（47）       Knowledge map    Save Driving style is the external expression of driving behavior. Drivers with aggressive style tend to engage in more frequent risky driving operations, intensifying interactions between vehicles and affecting lane-changing safety. Identifying a driver’s driving style before executing a lane-changing can effectively constrain driver’s behavior through personalized warning information. This paper proposed the SHAP-XGBoost method, which considers lane-changing game in a connected environment, aiming to achieve the real-time recognition of driving styles during the lane-changing intention phase. Firstly, the fluctuation degree of individual behavior and gaming behavior during the lane-changing intention was used as input feature variables, and the driving style was marked by correlation analysis, principal component analysis, and four different clustering methods. Next, the proposed SHAP-XGBoost model was used to select key features for training the driving style recognition model, and online recognition was completed through a sliding window. Finally, experiments were conducted using the HighD dataset. Results show that: compared with clustering methods based on centroid distance, connectivity and density distribution, spectral clustering based on graph theory principles can better label driving styles based on the morphology of the input feature variables; using the proposed SHAP-XGBoost model with 14 key features for driving style recognition can improve online recognition efficiency without loss of accuracy, and the driving style recognition accuracy is up to 99%; simultaneously incorporating individual features and gaming features as inputs to the model can improve the accuracy of driving style labeling and recognition. The research results can be used to support personalized lane-changing decisions and early warnings. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Trajectory Data-Driven Model for Vehicle Lane Change Intention Recognition YUAN Renteng, WANG Chenzhu, XIANG Qiaojun, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (6): 34-44.   DOI: 10.12141/j.issn.1000-565X.230258 Abstract （305）   HTML （7）    PDF（pc） （2570KB）（46）       Knowledge map    Save In order to accurately recognize and estimate the lane-changing intentions of vehicles, a vehicle lane change intention recognition model based on TCN-LSTM network is proposed, which combines the temporal processing capability of TCN (Temporal Convolutional Network) with the gate memory mechanism of LSTM (Long Short Term Memory Network). In the investigation, firstly, the driving intentions of the target vehicle are divided into three types, namely going straight, changing lanes to the left, and changing lanes to the right. The running state indicators of the target vehicle and its surrounding neighboring vehicles (including the adjacent front and rear vehicles in the same lane, left lane and right lane) are extracted from the Citysim vehicle trajectory dataset using the median filtering algorithm. Secondly, to overcome the low recognition accuracy, long training time and slow parameter updating existing in statistical theories and traditional machine learning methods, the dilated convolution technique is used to extract the temporal features of time series, and the gate memory units are used to capture the long-term dependency relationships of temporal features. With 54 indicators, including the speed, acceleration, heading angle, heading angle change rate, and relative position information of the target vehicle and surrounding neighboring vehicles, as input parameters, and with the lane change intention of the vehicle as the output indicator, a vehicle lane -change intention recognition model based on the TCN-LSTM network is constructed. Finally, the recognition accuracy of TCN, SVM (Support Vector Machines), LSTM, and TCN-LSTM models under different input time steps are comparatively analyzed. The results show that, when the input time series length is 150 frames, the recognition accuracy of the TCN-LSTM model reaches a maximum of 96.67%; and that, in terms of overall classification accuracy, as compared with LSTM, TCN and SVM models, the TCN-LSTM model improves the classification correctness of lane change intention by 1.34, 0.84 and 2.46 percentage points, respectively, which demonstrates better classification performance. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Effect of Tea Polyphenols on Soy Protein Isolate-Stabilized Emulsions and Interfacial Protein Displacement by Bile Salts GE Ge, LIN Li, ZHENG Jiabao, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (4): 26-32.   DOI: 10.12141/j.issn.1000-565X.230325 Abstract （297）   HTML （4）    PDF（pc） （1910KB）（31）       Knowledge map    Save The soy protein isolate was modified by adding different concentrations of tea polyphenols extract to prepare the oil-in-water (O/W) emulsion. The interfacial tension, interfacial protein adsorption fraction, emulsion particle size and zeta potential were investigated to explore the effect of tea polyphenols on the properties of soy protein isolate emulsion and interfacial protein displacement. The results show that the interfacial tension of soy protein isolate is increased after the addition of tea polyphenols. When soy protein isolate (1%, mass concentration) and soy oil are prepared into O/W emulsion with 9∶1 mass ratio by high-speed shear and ultrasound, tea polyphenols addition can improve the emulsion stability. Compared to the blank control group, when the amount of tea polyphenols added is 0.04%, the particle size of emulsion decreases significantly from 1.702 μm to 1.203 μm (P < 0.05), the protein adsorption fraction increases significantly from 9.22% to 20.68% (P < 0.05), and the zeta potential increases significantly from 25.7 mV to 27.1 mV (P < 0.05), respectively. Soy protein isolate shows resistance to bile salts displacement at the oil-water interface. In addition, the soy protein isolate modified by tea polyphenols is more difficult to be displaced by bile salts because of the strong electrostatic interaction and the thicker interface layer. Lipid digestion in intestine is an interfacial process. Exploring the interfacial displacement between protein and bile salts is beneficial to the study of lipid metabolism and food precise design. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Charging Schedule Optimization of Battery Electric Bus Considering Nonlinear Charging Profile XIONG Jie, LAI Kefan, LI Tongfei, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (9): 115-130.   DOI: 10.12141/j.issn.1000-565X.230524 Abstract （253）   HTML （15）    PDF（pc） （4868KB）（206）       Knowledge map    Save Battery electric buses are increasingly applied and promoted in public transportation systems due to their advantages, such as low emissions and low noise levels. However, their limited driving range and long charging time necessitate frequent charging during daily operations, thus leading to a new charging scheduling problem. A reasonable charging schedule is of great significance in reducing the construction cost of charging facilities and charging costs. However, current research on optimizing electric bus charging schedules typically assumes a linear relationship between charging time and state of charge (SOC), and often neglects the comprehensive optimization of charging schedules and charging station operations, resulting in poor scenario reproduction and resource inefficiencies. Therefore, this paper further studied the optimization of charging schedules based on a predefined set of bus trip schedules. A mixed-integer programming model was developed to minimize the total system cost by optimizing the occurrence periods, the start and end times of charging, and the schedules of the charging piles synchronously. The model also fully considers time-of-use electricity pricing policy, partial charging strategies, and the nonlinear characteristics of battery charging. To solve the problem, this paper first linearized the nonlinear charging function of the battery into a piecewise linear one and then used the commercial solver Gurobi to obtain the optimal solution. Additionally, a tailored algorithm was designed based on the minimum-cost-maximum-flow theory and the deficit function. Multiple sets of experiments were conducted to validate the effectiveness of the proposed algorithm based on five bus routes in Beijing. The results, obtained through both Gurobi and the proposed optimized algorithm, demonstrate that the proposed algorithm can achieve a significant reduction in total system costs, ranging from 28.34% to 56.1% across various scenarios. These findings confirm the efficiency of the algorithm and its potential to optimize charging schedules effectively. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Improvement Effects of Co-administration of Cartilage Extract, Turmeric Extract, Pueraria Lobata and Coix Seed Extract on Cartilage Damage of Rats with Knee Osteoarthritis DING Liugang, GUAN Ting, MIAO Jindian, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (4): 17-25.   DOI: 10.12141/j.issn.1000-565X.220815 Abstract （244）   HTML （0）    PDF（pc） （3373KB）（34）       Knowledge map    Save This paper studied the synergistic effects of turmeric extract, cartilage extract, Pueraria lobata and Coix (Coix lacryma-jobi) seed extract alone and the combination on the improvement of cartilage damage of rats with knee osteoarthritis. The synergistic effects of the three extracts in rat knee osteoarthritis were evaluated mainly by reducing knee swelling (inflammation), protecting chondrocyte and repairing joint cartilage. The results show that the turmeric extract has a more obvious effect in inhibiting joint swelling and improving cartilage damage, which is specifically manifested in the ability to better improve the levels of Collagen Ⅱ, matrix metalloproteinase 3 (MMP3), cartilage oligomeric matrix protein (COMP), tumor necrosis factor-alpha (TNF-α) and superoxide dismutase (SOD). The cartilage extract significantly improves the arthritic lesions by improving the levels of MMP3, COMP, TNF-α, prostaglandin E2 (PGE2) and SOD. Pueraria lobata and Coix seed extract improves the levels of Collagen Ⅱ and SOD, inhibits the elevation of MMP3, COMP, TNF-α and interleukin 1β (IL-1β), and improves cartilage damage of rats with knee osteoarthritis. The combined use of the three extracts exhibits better effects on the repair of rat knee cartilage. These data imply that by optimizing the ratio of turmeric extract, cartilage extract and Pueraria lobata and Coix seed extract, functional foods can be developed with significant anti-inflammatory and cartilage repairing effects and contribute to the realization of “Healthy China 2030”. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Study on Evaluation and Influencing Factors of Cognitive Driving Ability in Elderly Drivers CHEN Bingshuo, LI Yang, ZHAO Xiaohua, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (9): 142-152.   DOI: 10.12141/j.issn.1000-565X.230579 Abstract （223）   HTML （14）    PDF（pc） （2000KB）（230）       Knowledge map    Save The number of elderly drivers in China continues to grow, and the changes in the driver structure pose challenges to traffic safety. Compared to drivers in other age groups, elderly drivers’ psychological function gradually declines and they are more prone to traffic accidents. Cognitive function is significantly correlated with driving safety performance. Based on the driving characteristics of elderly people, this article started from three cognitive functional areas of attention response ability, executive processing ability, and spatial perception ability, and designed driving simulation experiments to obtain cognitive driving behavior data. It analyzed the differences in driving behavior characteristics among young people, middle-aged people, and elderly people. By combining subjective and objective methods to determine indicator, weights, a method for calculating the cognitive driving behavior index was proposed. A generalized linear mixed model was established with driver attributes and cognitive function as independent variables and cognitive driving behavior index as dependent variable to explore the impact of different factors on cognitive driving ability. The results showed that age, weekly driving frequency, self-regulation, and TMT-B (Trail Making Test-B) were significantly correlated with cognitive driving behavior index, with MMSE (Mini-mental State Examination) showing marginal significant correlation. The cognitive driving behavior index of elderly drivers was greatly influenced by individual traits. Compared to the elderly, the cognitive driving behavior index of young people was worse, while that of middle-aged people was better. People with lower weekly driving frequency had better cognitive driving behavior index than those with higher weekly driving frequency. Drivers with low and medium self-regulation frequencies have better cognitive driving behavior indices than those with high self-regulation frequencies. TMT-B measurement showed that the cognitive driving behavior index of drivers with normal cognition was better than those with cognitive impairment. Starting from the perspective of human factors in traffic accidents, this study explored the cognitive challenges faced by elderly drivers, proposed a calculation method for the cognitive driving behavior index of elderly people, and analyzed the influencing factors, providing reference for simplifying the evaluation process of elderly driving suitability and formulating driving safety intervention strategies. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Review of Driving Technology for Permanent Magnet Synchronous Motors Without Electrolytic Capacitor WANG Xiaohong, LIANG Yu, PAN Zhifeng, LU Mingqing, LIU Manxi Journal of South China University of Technology(Natural Science Edition)    2024, 52 (12): 93-108.   DOI: 10.12141/j.issn.1000-565X.240274 Abstract （223）   HTML （0）    PDF（pc） （3716KB）（13）       Knowledge map    Save Due to their small size, low cost and high reliability, permanent magnet synchronous motors have been widely used in the fields of industrial production, transportation and household appliances. Electrolytic capacitor is the middle part of drive system connecting the power grid and the motor. Its life is easily affected by external factors such as environmental temperature and humidity, which seriously restricts the stability and reliability of the motor products. Therefore, the drive system without electrolytic capacitor has become the research hotspot at home and abroad. Scholars have proposed various control strategies for achieving high power factor, suppressing current harmonics, and stabling motor operation. In this paper, the factors affecting the power quality and motor performance of drive system without electrolytic capacitor are analyzed, the advantages and disadvantages of different control strategies are compared, the control strategies for optimizing system performance are summarized, and the driving technology of permanent magnet synchronous motor without electrolytic capacitor is prospected. There comes to the following conclusions: at present, the current power quality is improved mainly through the optimization of motor control algorithm, but the existing methods, such as indirect power control, direct power control, compensation phase current’s non-ideal characteristics and regenerative energy control, all have some limitations; the improvement of motor performance is mainly carried out by the traditional control strategies based on constant bus voltage, such as weak magnetic control and over-modulation, while simultaneously suppressing beat phenomenon and ensuring stable operation of the motor, thus, it is necessary to further consider whether the power factor and current harmonics meet the standards in the subsequent research. Moreover, it is pointed that the comprehensive performance control of non-electrolytic capacitor motor, which takes into account both power quality and motor performance, is the biggest problem faced by the current non-electrolytic capacitor control system. Therefore, it is necessary to carry out a collaborative control for the power grid and the motor to rationally allocate functions and avoid conflicts. Table and Figures | Reference | Related Articles | Metrics | Comments（0）