Most Down Articles

Published in last 1 year| In last 2 years| In last 3 years| All| Most Downloaded in Recent Month | Most Downloaded in Recent Year|

Published in last 1 year

Please wait a minute...


For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails

Select

Axial Compression Behavior of Rectangular Concrete-Filled Steel Tube Columns Reinforced by Built-In Profiled Stirrup KANG Lan, CHEN Xuan, HONG Shutao Journal of South China University of Technology(Natural Science Edition)    2024, 52 (5): 101-113.   DOI: 10.12141/j.issn.1000-565X.230116 Abstract （189）   HTML （3）    PDF（pc） （4333KB）（511）       Knowledge map    Save Concrete-filled steel tube (CFST), as a kind of structure with broad development prospect, has good bearing capacity and plastic deformation ability. As a common form, rectangular concrete-filled steel tube column is widely used in engineering practice. Based on the two problems of inconsistent constraints on long and short sides and insufficient constraints on core concrete existing in practical application of rectangular concrete-filled steel tube, this study explored a new type of rectangular concrete-filled steel tube member, namely rectangular concrete-filled steel tube column reinforced by built-in profiled stirrup. Therefore, this study carried out the axial compression tests on 11 rectangular concrete-filled steel tube columns reinforced by built-in profiled stirrup, 2 rectangular concrete-filled steel tube columns with built-in racetrack stirrup, and 2 ordinary rectangular concrete-filled steel tube columns. It analyzed the influences of the coupling distance, steel tube thickness, concrete strength grade, stirrup spacing, stirrup diameter, built-in steel quantity on the axial compression bearing capacity and ductility of rectangular concrete-filled steel tube columns reinforced by built-in profiled stirrup. The findings reveal that reducing the thickness of the rectangular steel tube and embedding the resulting steel into the core concrete as profiled stirrup can effectively improve the axial compressive bearing capacity and ductility of the specimen, while maintaining the total amount of steel used. Additionally, the axial compression behavior of rectangular concrete-filled steel tube columns reinforced by built-in profiled stirrup can be divided into four stages: elastic stage, elastoplastic stage, plastic strengthening stage, and descending stage. Compared to ordinary rectangular concrete-filled steel tube columns, those reinforced by built-in profiled stirrup exhibit a more complete plastic strengthening stage. Based on the experimental results and parametric analysis, this study derived a calculation formula for the axial bearing capacity of rectangular concrete-filled steel tube columns reinforced by built-in profiled stirrup using an existing confined concrete constitutive model. This study can provide scientific basis and data reference for practical engineering applications. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Coupling Analysis of Rail Transit Stations’ Network Centrality, Ridership and Spatial Heat Map WU Jiaorong, CHEN Caiting, DENG Yongqi Journal of South China University of Technology(Natural Science Edition)    2024, 52 (5): 31-42.   DOI: 10.12141/j.issn.1000-565X.230302 Abstract （197）   HTML （13）    PDF（pc） （6507KB）（354）       Knowledge map    Save Urban spatial heat map reflects population aggregation and street vitality. In order to explore the interactive relationship between urban rail transit and spatial heat map, this study used Baidu heat map and rail transit station ridership data to analyze the coupling characteristics between network centrality, ridership and nearby spatial heat index of rail transit stations on a micro level, taking Shanghai as a case study. Firstly, it investigated the overall coupling relationship between two categories of station attributes and spatial heat through Pearson bivariate correlation analysis. Then, bivariate spatial autocorrelation and geographically weighted regression analysis methods were introduced to explore the spatial association patterns between network centrality and spatial heat, as well as between spatial heat and ridership, followed by a spatial differentiation comparison between the two coupling types. The results show that the coupling relationship between rail network centrality and spatial heat is obviously better than that between ridership and spatial heat at station level, since traffic location advantage can usually develop higher spatial heat, while ridership may be affected by more complex factors. Spatial heat map is more suitable for quantifying the interaction between rail transit and urban space in areas outside the urban core, where increasing rail network centrality has a multiplier effect on spatial heat improvement, but improving spatial heat in areas with low-density development is more conducive to stimulating ridership. It is feasible to evaluate the ridership potential of new stations outside the urban core area by using spatial heat map, but this data alone is not enough to predict ridership. The urban renewal around rail transit stations can be optimized by referring to the differences between the two types of coupling at different spatial locations. This study explored the analytical framework for improving the layout of rail transit network based on urban spatial heat map, and optimizing TOD (Transit-Oriented Development) stations for factors negatively affecting their coupling. It provides a new perspective for measuring the man-land relationship of urban rail transit on the micro level. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

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 （8000）   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）

Select

Skid Resistance Deterioration and Influencing Factors of Ultra-Thin Wear Layer WANG Duanyi, LI Yanbiao, PAN Yanzhu Journal of South China University of Technology(Natural Science Edition)    2024, 52 (5): 1-9.   DOI: 10.12141/j.issn.1000-565X.220806 Abstract （203）   HTML （11）    PDF（pc） （3797KB）（239）       Knowledge map    Save To accurately evaluate the decay process, mechanism and influencing factors of anti-sliding performance of asphalt ultra-thin wear layer after opening to traffic, this study first used arc mold and its supporting wheel grinding mechanism to prepare arc-shaped ultra-thin wear layer specimens. Then, it carried out the accelerated loading test of asphalt ultra-thin wear layer specimens with four gradation types and three asphalt binder grades by driving wheel accelerated loading system. Finally, it scanned the specimens after a certain number of wheel loads by laser texture scanner. Combined with the test data, the macro and micro structure depth decay models of asphalt ultra-thin wear layer based on S-type function were established respectively, and the independent and coupling effects of each porosity and asphalt binder on skid resistance were analyzed based on grey correlation analysis. The experimental results show that the driving wheel accelerated loading system combined with the S-type function model can quantitatively evaluate and predict the evolution process of the performance of the asphalt ultra-thin wear layer. The porosity affects the early decay rate of the macro and micro structural depth of the ultra-thin wear layer. The larger the porosity, the greater the early decay rate of the macro and micro structural depth of the ultra-thin wear layer. The middle and late decay rate of macro-structure depth is more affected by the grade of asphalt binder. The higher the performance grade of asphalt binder, the slower the decay rate of macrostructure depth in the middle and late stages. Void ratio and asphalt binder grade have similar influence on the decay rate of the micro-structure depth of the ultra-thin wear layer in the middle and late stage. Therefore, when designing the anti-sliding performance of the ultra-thin wear layer, it is beneficial to select the open-graded ultra-thin wear layer mixture with large porosity for the anti-sliding durability of the pavement, and the performance grade of asphalt binder can be reasonably selected according to the traffic volume. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Optimization Design of the Stereoscopic Compound Expressway Sign System Based on Unity3D GAO Longkai, ZHAO Xiaohua, OU Jushang, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (5): 20-30.   DOI: 10.12141/j.issn.1000-565X.230263 Abstract （187）   HTML （14）    PDF（pc） （5072KB）（238）       Knowledge map    Save By adding bilateral elevated layers, the renovation and expansion of the expressway have improved the traffic capacity, but a subsequent rise in problems, such as insufficient spacing, excessive traffic volume, and multi-diversion, has made the existing traffic signs fail to meet the drivers’ guidance needs. In response to this issue, this study took the Ji-He Expressway in Shenzhen as an example and designed four optimized traffic sign schemes of interchange based on the conventional standard scheme, and developed the corresponding stereoscopic compound expressway scenes by the Unity3D engine. The vehicles on the expressway will drive out of the ground-level road at the first diversion, enter the elevated-level road at the second diversion, and connect to other expressways at the third diversion. 28 drivers simulated driving in different scenes using external interactive devices, and their driving behavior data such as speed, acceleration, lane position, etc., were obtained. By calculating the point-by-point significance of indicators within each affected section in different guidance sign design schemes, differences in spatial dimensions of each indicator were presented, and further analysis shows that 3 km warning signs can help drivers perceive the situation of the ramp ahead as early as possible. Lane guidance signs can improve the longitudinal and lateral stability of vehicles at the ramp, and drivers can take better lane changing strategies. Navigation voices assistance can improve the driver’s speed control proficiency, lane changing awareness of expressway exits, and psychological comfort at the interchange of stereoscopic compound expressway. The research shows that Unity3D has high fidelity, good interactivity, and low cost, and it can provide technical support for relevant research on driving behavior in complex road scenes in the future. At the same time, this study also provides a theoretical reference for the establishment of traffic guidance signs in expressway renovation and expansion projects. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Recognition Model of Highway Toll Evasion Behavior Considering Cost-Sensitivity ZHAO Jiandong, XU Huiling, LÜ Xing, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (5): 10-19.   DOI: 10.12141/j.issn.1000-565X.230078 Abstract （168）   HTML （15）    PDF（pc） （2535KB）（235）       Knowledge map    Save In order to effectively improve the efficiency of highway vehicle toll evasion inspection, based on ETC （Electronic Toll Collection） toll data, this paper proposed a highway vehicle evasion recognition model by combining KNN (K-Nearest Neighbor), adaptive boosting (Adaboost) algorithm and cost-sensitive learning mechanism. Firstly, in view of the large volume and redundancy of the original ETC toll flow data, data discretization and standardization processing rules were developed to repair and standardize the data form, and then two types of toll evasion features were extracted. Secondly, seven types of toll evasion, such as large vehicles with small tags, were selected as the main research objects by analyzing the ETC data set. Thirdly, to address the problem of inefficient model classification due to the “high-dimensional” characteristics of the evasion data, the best subset of features showing the evasion characteristics was selected by Pearson and Spearman correlation analysis and ReliefF importance analysis. Fourthly, to address the model overfitting problem caused by the class “imbalance” between toll evasion vehicles and normal vehicles, KNN was used as the base classifier in the Adaboost algorithm, and the boundary ambiguity of different categories was alleviated through TomekLinks undersampling, then a cost-sensitive learning mechanism was introduced to improve the model’s emphasis on the minority class (toll evasion vehicles) to alleviate the tendency to discriminate the majority class (normal vehicles). Finally, the performance of the KNN-Adaboost model incorporating cost-sensitive learning mechanisms was verified by comparing the recognition effects of different classification models for various types of evasion events. The results show that the precision of the proposed model is 0.98, Recall is 0.96, F1-score is 0.97, and Kappa coefficient is 0.95, indicating that the proposed model can better solve the sample class imbalance problem than other models and has higher recognition accuracy for minority class，and it can be a reference for improving the efficiency of highway toll inspection. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Investigation into Creep Properties of Kapton Films Under Different Initial Stresses LIU Yan, XUE Xinyuan, FAN Lei, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (5): 127-138.   DOI: 10.12141/j.issn.1000-565X.230168 Abstract （185）   HTML （1）    PDF（pc） （3068KB）（232）       Knowledge map    Save As a kind of aerospace membrane material, polyimide film’s (Kapton film) creep effect is very important to its structure. In order to study its creep mechanical properties, firstly the study selected Kapton film with a thickness of 25 μm, and carried out the uniaxial creep tensile test under the four stress levels of 35%, 50%, 65% and 80% of the ultimate tensile strength. Secondly, according to the creep mechanics curves obtained, the creep characteristics of the film under different initial stresses were analyzed, and the intrinsic mechanism was discussed by combining the creep elongation. Five creep constitutive models of classical Kelvin, classical Maxwell, four-element Burgers, three-parameter generalized Kelvin and five-parameter generalized Kelvin were used to fit the experimental data, and the fitting effects of each model were compared and analyzed. The results show that Kapton film has obvious viscoelastic properties, which should be considered in the design. The initial stress has a significant effect on the creep properties of Kapton film. The greater the initial stress, the higher the strain at the initial creep stage, the higher the strain retention value at the steady creep stage, and the more obvious the viscoelasticity is. The tensile fracture stress levels in different directions lead to the differences of creep properties, and the total strain of TD (Transverse Direction) is greater than that of MD (Machine Direction) under each stress state. With the increase of the initial stress, the creep elongation of the film first increases and then decreases. This is because the influence of the initial stress on the stress state and dislocation motion inside the film is complex, and there is an equilibrium point. The five-parameter generalized Kelvin model adopted in this paper can well predict the creep properties of Kapton film, and the coefficient of determination of the fitting results is more than 0.99, followed by the Burgers model. The fitting coefficients of classical Kelvin, three-parameter generalized Kelvin and classical Maxwell model are between 0.71 and 0.86, and the fitting results meet the needs of practical engineering. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

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 （222）   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）

Select

Modeling of Source/Drain Access Region Resistance in GaN HEMT Considering Self-Heating and Quasi-Saturation Effect YAO Ruohe, YAO Yongkang, GENG Kuiwei Journal of South China University of Technology(Natural Science Edition)    2024, 52 (7): 1-8.   DOI: 10.12141/j.issn.1000-565X.230405 Abstract （196）   HTML （14）    PDF（pc） （2939KB）（227）       Knowledge map    Save The region between gate and source/drain is called source/drain access region resistances (RD,S) in GaN HEMT equivalent circuit model. Accurately constructing the source/drain access region resistance (RD,S) model is of great significance for analyzing the DC and RF characteristics and building a comprehensive large-signal model for GaN HEMTs. This paper presented an RD,S model considering self-heating and quasi-saturation effects. Firstly, the nonlinear self-heating effect model was derived based on the relationship between the temperature of the source/drain access region (TCH) and the dissipated power (Pdiss). Furthermore, based on the quasi-saturation effect and Trofimenkoff model, a nonlinear RD,S model was constructed. Under low bias conditions, the decrease of 2DEG and mobility with increasing TCH results in the increase of RD,S with TCH at ambient temperatures (Tamb) ranging from 300 to 500 K. At constant Tamb, RD,S presented a nonlinear increasing trend with the increase of bias. The results show that the average relative errors of the RD models in this paper and in the literature are 0.32% and 1.78% respectively, and the root mean square errors (RMSE) are 0.039 and 0.20 Ω respectively. The mean relative errors of RS model are 0.76% and 1.73% respectively, and RMSE are 0.023 and 0.047 Ω respectively. Compared with the experimental data reported in the literature, the results show that the average relative errors of the RD model in this paper and that in the literature are 0.91% and 1.59% respectively, and the RMSE are 0.012 and 0.015 Ω respectively. The mean relative errors of RS are 1.22% and 2.77% respectively, and RMSE were 0.001 5 and 0.003 4 Ω respectively. The proposed model with lower mean relative error and root mean square error, is able to more accurately characterize the variation of RD,S with the drain-source current (IDS) in the linear operating region of GaN HEMTs. This model can be used for the design optimization of the device or as a Spice model for circuit simulation. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Mechanism and Mechanical Characteristics of Cable-Catenary Arch Combined Structure HAO Tianzhi, LI Chunhua, YANG Tao, LONG Xiayi, DENG Nianchun Journal of South China University of Technology(Natural Science Edition)    2024, 52 (8): 89-102.   DOI: 10.12141/j.issn.1000-565X.230566 Abstract （156）   HTML （6）    PDF（pc） （3293KB）（223）       Knowledge map    Save With the increase of traffic volume and overloading of vehicles, the mechanical properties of early arch bridges under live load can no longer satisfy the needs of modern traffic due to low design load grade, lack of effective maintenance and long term operation. To improve the mechanical performance of this kind of arch bridges, this paper proposed a cable-catenary arch combined structure. The cables were symmetrically arranged on both sides of the arch rib to form a new force system, which could change the force transmission path of the catenary arch structure and reduce the internal force of the arch structure. Under the mechanical diagram of cable-arch combined structure, the force equation of the cable-arch combined structure was established based on the elastic center method, and the analytical solution of the internal force of the arch rib was deduced by the approximate curve integration method under the vertical moving load. The reliability of the analytical solution was verified by ANSYS finite element analysis software, and the influences of design parameters such as cable constraint position, arch-axis coefficient, rise-span ratio, and axial stiffness ratio on the internal force of the arch structure under lane loading were analyzed. The mechanical properties and internal variation rules of the cable-arch combined structure were revealed. The results show that the relative error between the analytical solution of the internal force and the finite element result is within 1%. The setting of the cable changes the positive and negative interval distribution of the bending moment influence line value of the arch structure, and effectively reduces the peak value of the bending moment influence line of the arch structure, which can greatly reduce the overall bending moment of the arch structure and make the bending moment distribution more uniform. From the arch foot to the arch crown, the reduction of the bending moment and the growth of the axial force of the arch structure gradually decrease. As the axial stiffness ratio increases from 0.02 to 0.10, the negative bending moment of the arch foot decreases nonlinearly, with the maximum decrease of 63.7%; the increase of the cable force is inversely proportional to its value, and when the cables are set at 0.3L (L is the span of the arch) from the arch crown, the cable force can be increased to 1.9 times that at the axial stiffness ratio of 0.02. The influence of the rise-span ratio on the internal force of the arch structure cannot be ignored. The greater the rise-span ratio is, the greater the change in internal force of the arch structure is. The effect of arch-axis coefficient on the internal force of the arch structure can be neglected. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

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）

Select

Intelligent Vehicle Object Detection Algorithm Based on Lightweight CenterNet YUE Yongheng, NING Ruihou Journal of South China University of Technology(Natural Science Edition)    2024, 52 (8): 45-55.   DOI: 10.12141/j.issn.1000-565X.230513 Abstract （191）   HTML （8）    PDF（pc） （3366KB）（221）       Knowledge map    Save Aiming at the problem that the current object detection algorithm has many parameters and larger computation amount, resulting in slower response and difficulties of application in intelligent vehicle systems, this paper proposed an improved CenterNet object detection algorithm. That is, the lightweight MobileNetV3 network was applied to replace the original ResNet-50 network to reduce the amount of computation; the depth-separable PANet was applied to replace the feature enhancement network to obtain the features after the fusion of the multi-scale feature information, and the SimAM attention mechanism was introduced to strengthen the attention of the target features before the fusion of the features, then the SiLU activation function was used to replace the original object detection network in the ReLU activation function to enhance the network learning. Finally, the CPAN-ASFF module was proposed to fuse the depth-separable PANet output multi-scale feature maps to improve the object detection accuracy. The optimized KITTI dataset was applied to train and detect the improved CenterNet object detection algorithm for validation. And the results show that its mean average precision is 80.7%, which is 12 percentage points higher than that of the original CenterNet object detection algorithm; its detection speed is 65 f/s, and its number of parameters is 8.91 M, which is 72.73% less than the original algorithm. The improved algorithm performs better in the detection of occluded objects, overlapped objects and objects similar to the background. In the SODA10M dataset, the detection accuracy and speed of the algorithm are better than the current mainstream algorithms. The optimization of the algorithm and the experiments in the paper laid the technical support for the application of intelligent vehicles in practical engineering. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

On the Nonlinear Relationship Between Land Use and Urban Rail Transit Passenger Flow WEI Liying, SHI Jingjing Journal of South China University of Technology(Natural Science Edition)    2024, 52 (5): 43-51.   DOI: 10.12141/j.issn.1000-565X.230125 Abstract （120）   HTML （12）    PDF（pc） （2972KB）（219）       Knowledge map    Save The impact of land use on passenger flow within the influence scope of urban rail transit stations has different spatiotemporal differentiation characteristics. To explore the complex nonlinear relationship between land use and passenger flow at different stations, this paper proposed a differentiation identification method based on the spatial distribution of land use variables, and through time-phased multiscale geographic weighted regression, station clustering indicators that can characterize the spatiotemporal changing characteristics of land use impact on passenger flow were obtained. K-means++ algorithm was used to divide the stations into four categories, and the complex nonlinear relationship between land use and railway passenger flow under different categories was explored based on the improved gradient boosting decision tree model. Research shows that the accuracy of nonlinear model can be effectively improved by capturing the spatiotemporal heterogeneity of the relationship between the land use and passenger flow and classifying the stations properly. According to the output results, the key factors are different for each category. For the first category, the bus station number and sidewalk density have top relative importance value of 61.35% and 30.08% respectively; the key factors are the same for the fourth, but with an importance value decreasing from 61.35% to 30.31% for the bus station number. For the second category, the building densityhas the greatest impact with a relative ratio of 66.57%, and on the contrary, which only accounts for 5.59% for the third one. Meanwhile, there are significant and varying threshold effects on the relationship between land use and rail transit passenger flow. The result shows that different types of stations should put different emphasis on land use development, and land use design indicators should be controlled within a reasonable range. This research will provide theoretical support and quantitative guidance for the formulation of differentiated land use development strategies around stations. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Experimental Study on the Noise and Transmission of Automobile Door Sealing Cavity ZHANG Binyu, WANG Yigang, YU Wuzhou, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (9): 104-114.   DOI: 10.12141/j.issn.1000-565X.240023 Abstract （158）   HTML （12）    PDF（pc） （4952KB）（217）       Knowledge map    Save The phenomenon and mechanism of sound generation and transmission of the car door sealing system with wind excitation are complex, and its research is much less.Taking the door primary sealing cavities of the B-pillar and C-pillar and the sealing cavity of the backdoor of a SUV as the research objects, this paper extracted their structures which are equivalent to regular cavity structures. It established a small acoustic wind tunnel with a testing platform and the testing method for the cavity sound generation and transmission, and conducted experiment on the sound characteristics and influencing factors, as well as the sound transmission characteristics of different compression of sealing strips and sealing gaps for the cavities with wind excitation. The results indicate that the mechanism of whistling from the door sealing cavity (backdoor cavity) is different. At low wind speeds, it is generated by coupling resonance between self-sustained oscillation and Helmholtz resonance cavity, while at high wind speeds, it is generated by coupling resonance between self-sustained oscillation and cavity mode, and self-sustained oscillation and cavity resonance with broadband excitation are the essential reasons for other peaks in the spectrum. There are significant sound characteristic differences between B-pillar and C-pillar the cavities and the backdoor cavity due to the sealing strip. The changes in yaw angle, pitch angle, and turbulence intensity of the flow have a significant impact on the amplitude and frequency of self-excited oscillation excitation, which is one of the sources of peak noise with a bandwidth below 1 000 Hz in the car. For small sealing strips compression (such as 0~4 mm) the sound transmission may increase with the increase of compression. The research on the sound phenomenon and mechanism of small cavity in car door gaps based on cavity noise theory is missing from previous studies. The sound transmission conclusion of different compression of the sealing strip has guiding significance for the design of car door seals. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

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 （3112）   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）

Select

Operational Characteristics and Eco-Safe Influence of Connected Mixed Platoon in Car-Following Event FU Qiang, ZHAO Xiaohua, LI Haijian, REN Wenhao, DAI Yibo Journal of South China University of Technology(Natural Science Edition)    2024, 52 (8): 65-75.   DOI: 10.12141/j.issn.1000-565X.230388 Abstract （217）   HTML （7）    PDF（pc） （3935KB）（213）       Knowledge map    Save Considering the current maturity level of autonomous technology and the general public’s acceptance of this technology, the connected mixed platoon mode may be a practical transitional strategy prior to the widespread deployment of fully autonomous platoons. To study the influence of connected condition and platoon mode on the operational characteristics and eco-safe influence of connected mixed platoon, this paper constructed a connected mixed platoon mode consisting of five vehicles: a human-driven leader vehicle equipped with an L2 connected driving assistance system, followed by connected autonomous vehicles. Thirty-six participants were invited to participate in driving simulation experiments using the developed test platform. Given that time-domain analysis focuses on the variation of indicators in the time dimension, while frequency-domain analysis can explore the frequency distribution characteristics of indicators, this paper analyzed vehicle operation characteristics from the time and frequency domain dimensions with indicators of speed, acceleration, fuel consumption and speed safety entropy. The results show that both the connected condition and the platoon mode contribute to stable vehicle operation and significantly enhance their eco-safety. Compared with the traditional single-vehicle mode, the connected mixed platoon has the best comprehensive efficiency and can reduce the fuel consumption by 10.67% and the speed safety entropy by 73.25%. The research results can provide scheme reference and platform support for autonomous driving enterprises and industries in executing connected HMI design, navigate on autopilot (NOA) development, and the feasibility and effectiveness test of connected mixed platoon. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

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 （1861）   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）

Select

Classification and Identification of Risky Driving Behavior Based on Hybrid Strategy Improved ASO-LSSVM HE Qingling, PEI Yulong, DONG Chuntong, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (9): 131-141.   DOI: 10.12141/j.issn.1000-565X.230753 Abstract （170）   HTML （14）    PDF（pc） （2032KB）（209）       Knowledge map    Save This paper aims to solve the problem of slow convergence rate and large error of existing intelligent algorithms in the process of optimizing support vector machine to identify risky driving behavior. Firstly, Tent mapping was used to replace the random setting of population initialization of ASO algorithm to increase the diversity and quality of atomic population. Secondly, the hybrid mechanism of dimension-by-dimension pinhole imaging reverse learning and Cauchy mutation was used to improve the diversity of preferred positions of atomic individuals and overcome the problem that ASO algorithm is easy to fall into local optimum and premature convergence. Finally, the adaptive variable spiral search strategy was introduced to improve the atomic individual position update process, so as to improve the global search ability of ASO algorithm, realize the effective balance between global search and local development, and alleviate the problem that ASO algorithm is easy to fall into local optimum and lack of convergence accuracy. Taking the vehicle trajectory data of the exit ramp of Shanghai North Cross Channel as the input, the study used the hybrid strategy to improve the ASO algorithm so as to optimize the LSSVM parameters. And it constructed the classification and identification model of the risk driving behavior of the expressway exit ramp based on IASO-LSSVM. Numerical simulation results show that the average value, standard deviation, best fitness and worst fitness of the numerical simulation results of the IASO algorithm in 12 benchmark test functions are closer to the best optimization value. Compared with ASO-LSSVM and LSSVM, the accuracy, precision, recall and F1 value of risk driving behavior classification and identification results of IASO-LSSVM model increased by 11.5~24.5, 14.1~29.0,15.1~28.6, 14.7~31.2 percentage points respectively, and the error range was the smallest in different types of risky driving behavior identification results. The accuracy and convergence rate of IASO algorithm are better than those of ASO algorithm, and the IASO-LSSVM model can be used for accurate identification of different types of risk driving behavior, which can provide data support and theoretical basis for reasonable discrimination of vehicle driving trajectory state and formulation of early warning and prevention measures of risk driving behavior. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Parametric Human Body Mesh Reconstruction Based on Global Consistency Network BAO Wenxia, TIAN Ruzhen, WANG Nian, et al Journal of South China University of Technology(Natural Science Edition)    2024, 52 (7): 19-28.   DOI: 10.12141/j.issn.1000-565X.230608 Abstract （96）   HTML （12）    PDF（pc） （2183KB）（207）       Knowledge map    Save Human body mesh reconstruction (HMR) has wide applications in human-computer interaction, virtual/augmented reality, and other fields. In order to further improve the accuracy of human body pose and shape estimation in image-based human body mesh reconstruction, this study proposed a parametric human body mesh reconstruction network based on hybrid inverse kinematics and global consistency deep convolutional neural network, called GloCoNet. To enhance the network’s global consistency and long-range dependencies, a Global Consistency Booster (GCB) module was designed on top of the feature extraction network. It can enhance the model’s perception and expression capabilities of global information, and allow the model to adaptively adjust the feature map weights of different channels and spatial positions. Furthermore, a multi-head attention mechanism was introduced to capture the model’s long-range dependencies globally, helping the model better capture key relationships and patterns when dealing with long-term dependencies, and modeling global contextual information to enrich the diversity of feature subspaces. Meanwhile, the network adopts a hybrid inverse kinematics approach to bridge the gap between human body mesh estimation and 3D human joint estimation, ultimately improving the accuracy of human 3D pose and shape estimation. Experimental results show that the GloCoNet model significantly outperforms previous mainstream methods with an average per joint position error of 51.3 mm on the publicly available Human3.6M dataset. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

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 （1828）   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）