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A Robot Grasping Policy Based on Viewpoint Selection Experience Enhancement Algorithm WANG Gao, CHEN Xiaohong, LIU Ning, et al Journal of South China University of Technology(Natural Science Edition)    2022, 50 (9): 126-137.   DOI: 10.12141/j.issn.1000-565X.210769 Abstract （10025）   HTML （21）    PDF（pc） （3882KB）（1102）       Knowledge map    Save To solve the problem of the low success rate of robot vision grasping using fixed environment camera in the scene of cluttered and stacked objects, an eye-hand follow-up camera viewpoint selection policy based on deep reinforcement learning is proposed to improve the accuracy and speed of vision-based grasping. Firstly, a Markov decision process model is constructed for robot active vision-based grasping task, then the problem of viewpoint selection is transformed into a problem of solving the viewpoint value function. A deconvolution network with encoder-decoder structure is used to approximate the viewpoint action value function, and the reinforcement learning is carried out based on the deep Q-network framework. Then, to resolve the problem of sparse reward existing in reinforcement learning, a novel viewpoint experience enhancement algorithm is proposed. The different enhancement methods between the successful and failed grasping process are designed respectively. And the reward region can be expanded from a single point to a circular region for improving the convergence speed of the approximation network. The preliminary experiment is deployed on the simulation platform, and the robot model and the grasping environment are simultaneously built in the simulation platform to implement the offline reinforcement learning. In the process, the proposed viewpoint experience enhancement algorithm can effectively improve the sample utilization rate and speed up the convergence of training. Based on the proposed viewpoint experience enhancement algorithm, the viewpoint action value function approximation network can converge within 2 h. To obtain the results from the verification with application, the proposed viewpoint selection policy is applied to the real-world scenes with robot for grasping experiments. The result shows that the viewpoint optimization based on this policy can effectively promote the accuracy and speed of robot grasping. Compared with the general grasping methods, the proposed viewpoint selection policy needs only one viewpoint selection in real-world robot grasping to find the focus region with high grasping success rate. And the method can also promote the processing efficiency of the best viewpoint selection. The grasping success rate in cluttered scenes is increased by 22.8% against the single-view method, and the mean picks per hour can reach 294 units. As whole, it shows that the proposed policy has the capacity of industrial application. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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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 （8024）   HTML （20）    PDF（pc） （3170KB）（277）       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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Research Progress on Key Technologies in the Cooperative Vehicle Infrastructure System LIN Hongyi, LIU Yang, LI Shen, et al Journal of South China University of Technology(Natural Science Edition)    2023, 51 (10): 46-67.   DOI: 10.12141/j.issn.1000-565X.230200 Abstract （6208）   HTML （30）    PDF（pc） （1996KB）（432）       Knowledge map    Save With the steady growth of urban car ownership, the issue of traffic congestion is becoming increasingly prominent, bringing great pressure to urban development. To respond effectively to this challenge, it is critical to develop methods that can improve transport efficiency and reduce energy consumption. In current context, the Cooperative Vehicle Infrastructure System (CVIS), an ideal solution for realizing green and intelligent transportation systems, has become an important direction in both transportation research and practice. By integrating and optimizing various traffic resources, CVIS not only enhances traffic efficiency and reduces energy consumption but also provides key technical support for achieving “dual carbon” goals. This paper thoroughly analyzed the fundamental concepts, research methodologies and application scenarios of CVIS, and delved into its four core technological modules: fusion perception, driving cognition, autonomous decision-making, and cooperative control. The paper reviewed and summarized research achievements within these modules, ranging from traditional methods to the latest in deep reinforcement learning techniques. It also explored the potential applications of these technologies and methods for enhancing traffic efficiency, reducing energy consumption, and improving road safety. Finally, the paper scrutinized numerous challenges that CVIS may encounter in practical applications, including the security of information transmission, system stability, and environmental complexity. To overcome these challenges, the paper looked forward to the future development in four areas: developing datasets that integrate vehicle-side and roadside information, enhancing the fusion accuracy of multi-source perception information, improving the real-time performance and safety of CVIS, and optimizing multi-vehicle cooperative decision-making control methods under complex conditions. As a result, this paper not only has important reference value for the advancement of CVIS technology, but also provides important guidance for the future planning and construction of urban transportation systems. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Study on Measuring Method of Vehicle Carbon Emission in Expressway Network LIN Xukun, ZHANG Yang, LUO Zhiqing, et al Journal of South China University of Technology(Natural Science Edition)    2022, 50 (9): 22-28.   DOI: 10.12141/j.issn.1000-565X.220019 Abstract （5495）   HTML （27）    PDF（pc） （1685KB）（1141）       Knowledge map    Save Under the background of dual-carbon policy, it is imperative to maintain ecological balance and reduce carbon emissions. Nowadays, it is very important to accurately measure the carbon emission index of vehicles on a wide range of road networks. Therefore, this study proposed a measuring method of vehicle carbon emission in expressway network based on multi-source data fusion. Firstly, a basic data cleaning method for carbon emission statistics was proposed to clean the basic data required for subsequent carbon emission calculation. Secondly, the highway carbon emission calculation model was established, and then the related calculation process was designed. Finally, taking the whole highway network of Guangdong province as an example, this paper calculated the vehicle carbon emission from September 2020 to June 2021, and compared the calculation results with China’s carbon accounting database.Through this method, the proposed method was proved to be scientific and reliable. The research shows that the average carbon emission of mini buses in Guangdong province is small, but the total carbon emission accounts for the largest proportion of all types of vehicles, up to 52.1%; the total carbon emission of gasoline vehicles accounts for 49.8%, which is higher than that of diesel vehicles (45.4%) and of other energy vehicles (4.8%). Vigorously promoting new energy vehicles can effectively reduce the carbon emission of expressways. In addition, the study finds that there are significant differences in the travel patterns of different vehicles under COVID-19, but the overall impact on the transportation economy is limited. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Passenger Flow Forecast of Urban Rail Transit Based on Graph Convolution and Recurrent Neural Network LIU Xiaolei, DUAN Zhengyu, YU Qing, et al Journal of South China University of Technology(Natural Science Edition)    2022, 50 (3): 21-27.   DOI: 10.12141/j.issn.1000-565X.210320 Abstract （4650）      PDF（pc） （1449KB）（493）       Knowledge map    Save Passenger flow forecast is of great significance to the organization and management of urban rail transit. This paper constructed a graph convolution and recurrent neural network (GCGRU model) by combining graph convolutional network with recurrent neural network. The graph convolutional network was used to learn the complex topological structure of an urban rail network and capture spatial correlation characteristics. Then one of the recurrent neural network variants called gated recurrent unit was used to learn the variation of multi-characteristics of traffic trends and to capture the temporal characteristics. An experiment was carried out with the passenger flow data obtained from the entire network with all subway cross-sections in Shanghai in a whole year, and the mean decrease impurity method provided by random forest was used for feature selection. The experimental results show that the GCGRU model can well capture the temporal and spatial correlation in the prediction of large-scale urban rail transit passenger flow, with a prediction accuracy of 89%. The prediction results can provide a basis for managers to manage and organize rail transit passenger flow as well as provide travelers with early warning information, ensuring the safe and efficient operation of the urban rail transit network. Related Articles | Metrics | Comments（0）

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Obstacle Avoidance Algorithm for Unmanned Aerial Vehicle Vision Based on Deep Learning ZHANG Xiangzhu, ZHANG Lijia, SONG Yifan, et al Journal of South China University of Technology(Natural Science Edition)    2022, 50 (1): 101-108, 131.   DOI: 10.12141/j.issn.1000-565X.210096 Abstract （4605）      PDF（pc） （3578KB）（977）       Knowledge map    Save In order to solve the obstacle avoidance problem of unmanned aerial vehicle (UAV) based on monocular vision, a quadrotor autonomous obstacle avoidance method based on monocular depth estimation and object detection was proposed.The monocular depth estimation model provides the pixel-level depth information of the obstacle, and the object detection model provides the location information of the obstacles.The depth map and object detection results of a single Red-Green-Blue image were obtained by convolutional neural network (CNN).The region division of the image was based on the object detection results, and the region depth was calculated based on the depth estimation results.The linear velocity and angular velocity of UAV were calculated by the planning algorithm based on the regional depth and regional division results, so as to realize the autonomous obstacle avoidance of UAV.In order to verify the autonomous obstacle avoidance performance of the algorithm, the Parrot Bebop2 UAV was employed to carry out real flight comparison experiments between the proposed algorithm and the direct flight algorithm.The results show that the proposed algorithm can be used for low speed autonomous obstacle avoi-dance of quadrotor. Related Articles | Metrics | Comments（0）

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Optimization Model of Bus Priority Control Considering Carbon Emissions with Stochastic Characteristics HU Xinghua, CHEN Xinghui, WANG Ran, et al Journal of South China University of Technology(Natural Science Edition)    2023, 51 (10): 160-170.   DOI: 10.12141/j.issn.1000-565X.230178 Abstract （4582）   HTML （3）    PDF（pc） （2474KB）（104）       Knowledge map    Save In the context of the construction of a country with a strong transportation network, vigorously developing urban public transportation and promoting sustainable urban development has become an inevitable requirement for urban transportation development. Transit signal priority control, as an active priority strategy, can effectively reduce the carbon emissions and delays generated by buses at signal intersections, and improve the quality of bus service. A bus speed probability density function was introduced to study the effect of bus priority control strategy on traffic carbon emission, based on the speed stochastic characteristics of intersection. The effect of main parameters such as delay, stopping times, and speed on traffic carbon emission was analyzed. A bi-level optimization model of single-intersection bus priority control was established using the combination strategy of speed guidance and green extension. The model took the optimal carbon emission reduction of buses and cars with different fuel types in the upstream section of the intersection and the intersection control area as the upper-level objective, the optimal total people delay reduction as the lower-level objective, and the guidance speed as well as the compressed green time of the non-bus-priority phases as the decision variables. The Gauss-Seidel iterative algorithm was used to solve the model. Finally, the established model was applied to the calculation cases for analysis, and the results indicated that under the guidance acceleration and green extension strategy, the overall carbon emission and total passenger delay reduction of the intersection could reach 25.63% and 36.27%, respectively. The model effectively reduced carbon emissions and total passenger delays in the upstream sections of the intersection and the intersection control area, and optimized the overall traffic benefit of the intersection while promoting sustainable development. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Literature Review on Traffic Congestion Identification Methods JIA Ruo, DAI Shenghong, HUANG Ni, et al Journal of South China University of Technology (Natural Science Edition)    2021, 49 (4): 124-139.   DOI: 10.12141/j.issn.1000-565X.180463 Abstract （4574）      PDF（pc） （2018KB）（255）       Knowledge map    Save Traffic congestion is the most frequent, wide-ranging and influential problem among all the traffic problems. The key to this problem is to identify and analyze traffic congestion. This paper reviewed the methods of traffic congestion identification from the perspectives of traditional traffic flow theory and machine learning. Traditional traffic flow theory adopts models such as indicators, MFD, cellular automata, CTM and dual-flow models, using the theory of physics and mathematics to describe the traffic behavior characteristics. The models are reasonable and simple, with clear physical meaning and also with many restrictions. The probabilistic graphical model and machine learning model are practical and not constrained by fixed structures. This paper discussed the research ideas, solutions and existing problems of different congestion identification methods by combining the specific model methods. It summarized the existing traditional traffic flow theory methods and machine learning methods, and pointed out the future development direction. Related Articles | Metrics | Comments（0）

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Study on Accident Risk Based on Driving Behavior and Traffic Operating Status GUO Miao, ZHAO Xiaohua, YAO Ying, et al Journal of South China University of Technology(Natural Science Edition)    2022, 50 (9): 29-38.   DOI: 10.12141/j.issn.1000-565X.210629 Abstract （4324）   HTML （29）    PDF（pc） （2302KB）（1149）       Knowledge map    Save Accurate identification of traffic accident risk and timely mastering the change of traffic crash risk are of great significance for proactive prevention and reduction of traffic accident. Most of the existing traffic crash identification studies are based on real-time and dynamic parameters such as traffic flow and traffic conflict. The application of risky driving behavior in traffic accident risk detection is limited by the constraints of previous data acquisition technologies. To more accurately identify the risk of road traffic crashes, this study introduced risky driving behavior and traffic operating status and other big data, and extracted sharp acceleration, deceleration, turns, merge into other lane, traffic volume, average speed, and congestion index as variables. And traffic accident identification models were constructed based on accident data. The traffic accident identification model was evaluated based on the logistic regression algorithm. On the one hand, the contribution of risky driving behavior in traffic accident identification was quantified; on the other hand, the trend of traffic accident occurrence probability before and after the accident was analyzed. The results show that the sensitivity and AUC values of the traffic accident identification model considering both traffic operation state and risky driving behavior are increased by 5.00% and 0.03, respectively. The false alarm rate and missing report rate are decreased by 1.78% and 5.00%, respectively, which shows better fitting effect of the model. In addition, before and after the occurrence of traffic accidents, the risk probability of traffic crashes shows an obvious trend of rise, which is the key period of traffic accident prevention and control. The measures should be taken in corresponding sections in time to curb the rising trend of traffic crash risk and avoid the occurrence of traffic crashes. This study can provide intuitive basis for traffic accident prevention, and active prevention and control. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Axial Compression Behavior of High-Strength Circular Steel Tube Confined High-Strength Steel Reinforced Concrete Short Columns KANG Lan, CHEN Zonglin, LIN Yiwei Journal of South China University of Technology(Natural Science Edition)    2022, 50 (7): 1-12.   DOI: 10.12141/j.issn.1000-565X.210463 Abstract （4158）   HTML （20）    PDF（pc） （2161KB）（113）       Knowledge map    Save This paper carried out axial compression tests on nine circular steel tube confined steel reinforced (CSTCSR) concrete short columns, one circular steel tube confined (CSTC) concrete short column and one circular steel tube column filled with steel-reinforced concrete. The main purpose of this research is to study the influences of yield strength of steel tube and shape steel, diameter-thickness ratio of steel tube, concrete strength, inner surface treatment method of high-strength steel tube and restraint mode on the failure mode, strain response, axial compression bearing capacity and ductility of CSTCSR concrete short column. The results show that the failure mode of high-strength circular steel tube confined high-strength steel reinforced (HCSTCHSR) concrete short column is overall shear failure, and there is no obvious local buckling on the surface of high-strength steel tube, and the development of oblique cracks of concrete is effectively restricted by the embedded high-strength shape steel. For CSTCSR concrete short column, the axial compression bearing capacity ratio and ductility coefficient of this column with high-strength steel tube and high-strength shape steel are increased from 1.37 to 1.49 and from 2.22 to 3.25, respectively, compared with those of CSTCSR concrete short column using ordinary-strength steel tube and ordinary-strength shape steel. It is concluded that the HCSTCHSR concrete short column has more excellent axial bearing capacity and ductility, and high-strength steel using in such column can be fully utilized. On the basis of “technical standard for steel tube confined concrete structures” (JGJ/T471—2019) and the results of parametric analysis in this study, a modified formula for axial bearing capacity of HCSTCHSR concrete short column was proposed by using the existing confined concrete’s constitutive model to provide scientific basis and data support for practical engineering application. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Intelligent Detection of Asphalt Pavement Roughness with kNN Method ZENG Jingxiang, ZHANG Jinxi, CAO Dandan, et al Journal of South China University of Technology(Natural Science Edition)    2022, 50 (3): 50-56.   DOI: 10.12141/j.issn.1000-565X.210326 Abstract （4078）      PDF（pc） （3711KB）（318）       Knowledge map    Save Roughness is one of the main technical indexes of pavement performance. Accurate and rapid IRI detection has great significance for pavement maintenance and management. In this paper, the self-developed smart phone App was used to collect driving status and other relevant datas. Driving datas such as vibration acceleration and speed were collected through driving experiments in real road, and the feasibility of detecting road roughness IRI by using these driving datas was studied. It proposed a method to take the composite vibration acceleration as the index of driving vibration acceleration and established the normalized kNN eigenvector space . The results show that the proposed method is simple and easy to apply and it improves the detection accuracy of pavement roughness IRI by using smart phones. The absolute evaluation accuracy of IRI detection reaches more than 78%, and the re-lative accuracy after considering adjacent evaluations reaches more than 96%, which meets the real-time detection and monitoring of pavement roughness IRI in the road network. It has a promising application prospects in improving the pertinence of IRI detection of pavement roughness and reducing the overall detection amount of pavement performance, thus can provide macroscopic guidance for the maintenance decision and management of road network pavement. Related Articles | Metrics | Comments（0）

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Resilience Evolution of Multi-mode Transportation Network in Urban Agglomeration Based on Risk Diffusion MA Shuhong, YANG Lei, CHEN Xifang Journal of South China University of Technology(Natural Science Edition)    2023, 51 (6): 42-51.   DOI: 10.12141/j.issn.1000-565X.220486 Abstract （4078）   HTML （4）    PDF（pc） （4048KB）（108）       Knowledge map    Save It can help improve the risk resilience of urban agglomerations to carry out in-depth analysis of the dynamic resilience evolution characteristics of multi-modal transport networks in urban agglomerations during the risk diffusion phase. Based on complex network theory and its extension theory, this study constructed a multi-modal and multi-level transportation network model for urban agglomerations based on road, railway and air networks. It matched node degree and node betweenness with accessibility, and analyzed their static topological characteristics under risk diffusion. Based on the theory of cascading failure dynamics, it considered the initial risk level, risk warning threshold and risk resilience of nodes at different stages, and constructed a risk dynamic diffusion model based on the nodes and connected edge measures affecting risk diffusion. Considering the characteristics of structural and functional changes under risk shocks, the paper constructed a network structural and functional resilience measurement model, and the resilience performance of multi-modal transport networks was represented by their coupling values. Using the multi-modal transport network of the Guan-Zhong Plain urban agglomeration as the research object, the Python Networkx and Matlab network analysis tools were used to simulate and analyze the dynamic resilience evolution of the multi-modal transport network of the urban agglomeration during the risk diffusion phase with respect to different risk diffusion methods, network reliability, redundancy, robustness and node risk handling capacity coefficients. The results show that the model results are consistent with reality. The network resilience can be effectively enhanced by improving network reliability, redundancy, robustness and node risk handling. Compared to the risk diffusion approach based on the node measure, the risk diffusion approach based on the connected edge measure has greater impact on resilience performance, suggesting that the distribution of route hierarchy levels has a greater impact on the resilience performance of multimodal transport networks in urban agglomerations compared to the number of routes. The overall resilience of a multi-modal, multi-level transport network performs better than that of a single transport network. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Design of an Innovative Eddy Current Replaceable Coupling Beam and Its Numerical Analysis GONG Nan, LI Peizhen, HE Xuming Journal of South China University of Technology(Natural Science Edition)    2022, 50 (7): 25-34.   DOI: 10.12141/j.issn.1000-565X.210665 Abstract （3527）   HTML （9）    PDF（pc） （2320KB）（193）       Knowledge map    Save This paper carried out a detailed study on the damping characteristics of the eddy current coupling beam damper, which can start to dissipate energy under small deformation of the replaceable coupling beam. Based on the analysis of magnetic circuit theory, the study proposed the optimal arrangement of permanent magnet pole in eddy current damper. In other words, the permanent magnet poles parallel to the direction of conductor motion were arranged alternately, and the permanent magnet poles perpendicular to the direction of conductor motion were arranged in the same direction. In view of this, two kinds of eddy current dampers were designed, one of which is the plate eddy current damper with the conductor plate moving straight in the magnetic field and the other is the rotary eddy current damper with the gear-rack mechanism to amplify the rotation speed of the conductor plate in the magnetic field. Two kinds of eddy current dampers were used in the replaceable coupling beam, and the finite element simulation of the new eddy current coupling beam damper installed on the replaceable coupling beam was carried out, which revealed the nonlinear mechanical behavior of eddy current damping. It shows that the damping coefficient and stiffness coefficient are strongly related to the frequency. The higher the loading frequency, the lower the energy consumption efficiency and the higher the dynamic stiffness of the structure. So, the eddy current damper is more suitable for low frequency working conditions, and at this time, the damping coefficient of the eddy current damper is large, the energy consumption efficiency is high, and the stiffness coefficient is small, which basically does not change the natural vibration characteristics of the structure. Therefore, it is of great value in real-world application. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Effects of Fermentation and Polyphenol Complex on the Digestibility of Rice Starch LI Xiaoxi, SHEN Shaodan, LU Ping, et al Journal of South China University of Technology (Natural Science Edition)    2022, 50 (1): 1-8.   DOI: 10.12141/j.issn.1000-565X.210103 Abstract （3498）      PDF（pc） （2212KB）（363）       Knowledge map    Save In order to improve the anti-digestibility of rice starch，the change law of digestibility and multi-scale structures of the fermented rice starch-proanthocyanidins complex，including the particle morphology，lamellar structure，crystalline structure，helical structure and short-range ordered structure，were systematically studied with modern analytical techniques and the method of fermentation and interaction with proanthocyanidins.Meanwhile，the molecular mechanism of rice starch anti-digestibility controlling by fermentation and combination with proanthocyanidins was revealed.The results indicates that the rapidly digestible starch and slow digestible starch contents of the fermented rice starch after interacting with proanthocyanidins are decreased，whereas the resistant starch contents are significantly increased.Moreover，the interaction between proanthocyanidins and fermented rice starch can promote the formation of specific ordered structure.And partial proanthocyanidins in the amorphous region can be released to inhibit the action of amylase during the digestion process，which synergisticly reduces the digestibility of fermented rice starch.The results provides foundations for improving the nutritional functions of fermented rice products. Related Articles | Metrics | Comments（0）

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Optimization Design of Filters Based on Parameter Extraction and Space Mapping Chen Jian-zhong Liang Chang-hong Chen Jia Deng Kun Journal of South China University of Technology (Natural Science Edition)    2011, 39 (10): 32-36,73.   DOI: 10.3969/j.issn.1000-565X.2011.10.006 Abstract （3419）      PDF（pc） （366KB）（3769）       Knowledge map    Save In order to improve the design efficiency of microwave bandpass filters,an optimization design method is proposed based on the parameter extraction and the space mapping. In this method,first,the Cauchy-TLS ( Total Least Squares) method is used to obtain the rational fraction models of the filters. Next,by using these models,a fast convergent objective function is constructed to extract the equivalent circuit parameters. Then,according to the principle of the space mapping,the problem of solving the optimal physical dimension of the filter is transformed into a quadratic constrained optimization model,and the corresponding solution is used to guide full-wave simulation of the filters. Finally,a dual-mode circular-waveguide filter is designed and machined,and its optimal physical dimension with ideal response is achieved after six iterations. It is found that the measured results accord well with the simulated ones. Related Articles | Metrics | Comments（0）

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Research on Roadside Environment Safety Based on Driver’s Attention Distribution Model WU Yanxia, ZHOU Tong, HUANG Shuai, et al Journal of South China University of Technology(Natural Science Edition)    2022, 50 (9): 49-57.   DOI: 10.12141/j.issn.1000-565X.20210802 Abstract （3306）   HTML （7）    PDF（pc） （11743KB）（145）       Knowledge map    Save In order to explore the influence of the highway roadside environment on the driver’s attention，optimize the roadside landscape and traffic sign settings，and improve the driving safety，this study determined the roadside environment risk level interval by quantitatively analyzing the driver’s attention distribution. Four types of typical scene were selected according to the actual state of the roadside environment， and field driving tests were carried out to collect data such as driver’s eye movement parameters and heart rate. The driver’s eye movement on the corresponding road section was analyzed，including fixation behavior，scan behavior and blinking behavior. On this basis，the obvious eye movement index that characterizes the driver’s attention was determined as the fixation parameter. According to the actual scene corresponding to the driver’s fixation point and the position of the point in the visual field， the driver's visual field area was divided into three parts， namely the roadside area （S area），the way area （W area） and the car area （C area）. By constructing the driver’s attention distribution model，the roadside environment was quantified and expressed by the ratio of attention region. The relationship model between the ratio of attention region and the driver’s heart rate growth rate was established，and the risk level interval was divided. The results show that the complexity of the roadside environment has a significant impact on the driver’s eye movement behavior. Compared with scan and blink，the driver’s fixation parameter can significantly characterize the driver’s attention state. When driving on the road，the driver’s fixation point moves in the view field，the ratio of attention region is the ratio of cumulative fixation time in the S area and the total fixation time of the S area and the W area. Its safety interval is ［9.93%，62.10%］，the risk interval is ［6.44%，9.93%） and （62.10%，76.93%］，and the danger interval is ［0，6.44%） and （76.93%，100%］. This research can provide a reference for the safety evaluation and decision-making of roadside landscape improvement. 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 （3267）   HTML （4）    PDF（pc） （2377KB）（52）       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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Braking Collision Avoidance System for Vehicles Driving on Superhighway Based on Co-simulation HE Yongming, FENG Jia, QUAN Cong, et al Journal of South China University of Technology(Natural Science Edition)    2022, 50 (10): 19-28.   DOI: 10.12141/j.issn.1000-565X.210703 Abstract （3260）   HTML （6）    PDF（pc） （2693KB）（67）       Knowledge map    Save To solve the safety problem of collision between a high-speed intelligent vehicle and a low-speed vehicle on the superhighway, the vehicle braking collision avoidance system was studied by using the method of co-simulation. CarSim was used to establish the vehicle dynamics model and set the front vehicle parameters, road parameters and sensor parameters, and the control model based on vehicle distance and speed was established in MATLAB/Simulink. The signal connection is established through the input and output parameter interface module of CarSim software. When the speed of the front car is 100, 120 and 140 km/h, and the speed of an intelligent vehicle is 140, 160 and 180 km/h, respectively, the control model sends the braking deceleration signal to the intelligent vehicle through the real-time distance and speed collected by the sensor and establishes the emergency braking collision avoidance strategy for the vehicle on the superhighway. The results show that when the road adhesion coefficient is 0.60 and the car is braked on the flat straight section of the superhighway, the optimal wheel cylinder pressure is 7 MPa, and at this time, the braking distance of the car is 170.3 m at a speed of 160 km/h. The front car travels at a speed of 100, 120 and 140 km/h, and the smart car brakes at 140, 160 and 180 km/h, respectively, to the same speed as the car in front, requiring relative distances of 10.8, 10.7 and 10.5 m, respectively. When the road adhesion coefficient is 0.60, the vehicle speed of the front vehicle is 100, 120 and 140 km/h, respectively. When the initial cylinder pressure is 1 MPa and the intelligent vehicle braking decelerates to the same speed as the front vehicle, the distance between the front suspension of an intelligent vehicle and the rear suspension of the vehicle in front is 3.1, 3.5, and 3.8 m, respectively. When the initial cylinder pressure is 3 MPa and the intelligent vehicle braking decelerates to the same speed as the front vehicle, the distance between the front suspension of an intelligent vehicle and the rear suspension of the vehicle in front is 7.0, 7.3, and 7.7 m, respectively. Through the CarSim/Simulink co-simulation platform of vehicle emergency braking and collision avoidance control, the validity and accuracy of superhighway braking and collision avoidance model are verified, which can improve the safety of superhighway driving. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Robot Collision Detection Based on External Torque Observer ZHANG Tie, CHEN Yijie, ZOU Yanbiao Journal of South China University of Technology(Natural Science Edition)    2024, 52 (3): 84-92.   DOI: 10.12141/j.issn.1000-565X.230086 Abstract （3203）   HTML （2）    PDF（pc） （2873KB）（40）       Knowledge map    Save Collision detection technology can reduce the probability of equipment damage and personal injury and plays an important role in modern human-robot collaborative production. To realize the collision detection without external torque sensor, it is necessary to accurately estimate the external torque of industrial robots. However, the accuracy of external torque estimation can be affected by parameters identification error of dynamic model and measurement error of motor current. To solve these problems, this paper designed a disturbance Kalman filter external torque observer based on the disturbance principle. The observer takes the equivalent external torque of external collision as the disturbance term, defines the joint disturbance model, and introduces the generalized momentum of the robot to construct the state-space equation. Considering the parameters identification error of the dynamic model and the measurement error of the motor current, it carried out an iterative estimation based on Kalman filter algorithm to obtain the optimal external torque. In order to improve the sensitivity of collision detection, a time-varying symmetric threshold function which varies with joint velocity was proposed for collision detection. The proposed method can adjust the threshold according to the change of joint velocity to adapt to the observed values of external torques at different working speeds. Experimental results show that compared with the generalized momentum observer, the accuracy of external torque estimation of the proposed observer is improved by 52.03%. In order to verify the effectiveness of the proposed method, this paper used a 6-DOF series joint industrial robot to conduct collision detection experiments. The experimental results show that compared with the static threshold, the time-varying threshold method reduces the detection delay by 58.06%, which can improve the sensitivity of collision detection and is more conducive to the safe operation and collision protection of industrial robots. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Development Law of Traffic Network Density in the Spatial Structure of Metropolitan Area Hierarchy WU Jiaorong, HUANG Zhengwen, DENG Yongqi Journal of South China University of Technology(Natural Science Edition)    2023, 51 (2): 111-121.   DOI: 10.12141/j.issn.1000-565X.220159 Abstract （3199）   HTML （5）    PDF（pc） （3532KB）（65）       Knowledge map    Save During the "14th Five-Year Plan" period, China has entered a new stage of urbanization development. Cultivating modern metropolitan areas is an efficient approach to promote the development of urban agglomerations. Rapid transportation systems such as expressways and high-speed railways in the regional transportation network are the precondition for the formation and development of metropolitan areas. The regional heterogeneous spatiotemporal convergence effects caused by them profoundly affect the spatial pattern of metropolitan areas. Therefore, there is a urgent need to examine the interactive relationship between the spatial organization of metropolitan areas and different transportation network levels. In order to explore the development law of spatial variations on expressway and railway density caused by the dislocation of population aggregation and economic development in metropolitan area hierarchy, this paper constructed a city correlation strength model based on multi-source data. It took five metropolitan areas in the Yangtze River Delta urban agglomeration as examples and districts and counties as spatial units. Multidimensional scaling analysis and spatial distance elements were applied to identify the boundaries of the metropolitan area hierarchy, namely boundaries of core circle, tight circle, and planning range. Based on the five main indicators of population density, per capita GDP, land output rate, railway density, expressway density in each metropolitan area hierarchy, this paper discovered the correlation law between socioeconomic development and transportation network density. Results show that there are unbalanced population agglomeration and economic development in each circle of the metropolitan area, and the development curves of "population density-output per land" and "output per land-output per capita" are "S-shaped" and "logarithmic", respectively; the development laws of "population density-expressway density" and "land output rate-expressway density" both show a "logarithmic" curve, but those of the current railway density curves vary from those of expressway; when the population density is higher than 600 people/km2 and the land output rate is more than 80 million yuan/km2, the railway density in the core circle is insufficient. This study provides a new perspective for the research on integrated transportation network planning in the metropolitan area. Table and Figures | Reference | Related Articles | Metrics | Comments（0）