Table of Content

25 September 2022, Volume 50 Issue 9

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Contents



2022, 50(9):  0-0. 

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Traffic & Transportation Engineering

Algebraic Method of Coordination Design for Bi-directional Red and Green Waves of Saturated Intersection



LU Kai, ZHAO Shijie, WU Huan, et al

2022, 50(9):  1-11.  doi:10.12141/j.issn.1000-565X.210809

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When there is a saturated intersection on the arterial road, it is necessary to intercept and regulate the traffic flow in the entry direction of the saturated intersection, so as to avoid the overflow of the section queue, and to conduct green wave dredging in the exit direction of the saturated intersection to facilitate the rapid departure of traffic flow. According to the coordination control requirements in different directions of saturated intersection, this paper proposed an algebraic method of coordination design for bi-directional red and green waves on arterial roads. Firstly, the general formula for calculating the ideal intersection distance was derived by using the time-space diagram, and the calculation method of bias-split for the coordinated phase was given. Secondly, for different common signal cycles, the bias-split for the coordinated phase under different signal phase modes of each intersection was calculated respectively. The signal phase mode corresponding to the bias-split with the smallest absolute value was taken as the preferred phase of each intersection. Then, the max difference of bias-split corresponding to the preferred phase under different common signal cycles was compared, and the common signal cycle with the minimum of the max difference of bias-split was selected as the best common signal cycle. Finally, based on the characteristics of red and green waves, the optimization method of fine-tuning signal offsets was given to minimize the bias-split of the green wave direction, so as to ensure that the arterial road can obtain bi-directional red and green wave bandwidth as wider as possible. The case analysis shows that, compared with the scheme of bi-directional green wave coordinated control, the bi-directional red and green waves coordinated control scheme designed by this method can significantly increase the green wave bandwidth in the direction of leaving the saturated intersection while ensuring that there is a maximum red wave bandwidth in the direction of entering the saturated intersection. The VISSIM simulation experiment shows that the scheme designed by this method can not only shorten the maximum queue length by 23.1% and the average queue length by 33.8%, and delay the time of vehicles queuing to overflow to the upstream intersection, but also reduce the travel time and the number of stops of the vehicles leaving at the saturated intersection in the downstream section by 17.5% and 76.3%, respectively. It can realize the overflow prevention and green wave dredging of the saturated intersection.

Dynamic Reservation and Allocation Optimization Model of Shared Parking Slots in Multiple Parking Lots



WANG Yuanqing, LIN Siyu, XIE Minghui, et al

2022, 50(9):  12-21.  doi:10.12141/j.issn.1000-565X.210780

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In order to alleviate the parking difficulty, make more balanced use of parking resources and realize the dynamic response to parking demands, this study established an integer programming model for dynamic reservation and allocation of shared parking slots in multiple parking lots by taking several adjacent off-street parking lots as the research object. Aiming at making full use of parking resources and saving users’ parking costs, the model adopts linear weighting to combine the goals and adaptively selects dynamic weight coefficients according to the real-time number of parking requests. The allocation results were optimized iteratively by adjusting the parking requests from the car that does not arrive. In addition, dynamic pricing mechanism was introduced to balance the utilization of each parking lot. The model was evaluated by four indicators: parking space utilization rate, parking request acceptance rate, average walking distance and equilibrium degree of parking area. the model was verified by simulation experiments. The results show that, compared with the traditional unadjusted model, the proposed model can increase the utilization and acceptance rates by 10.70% and 20.08%, respectively, on average by iteratively optimizing the unreached parking requests. The improvement degree of utilization increases first and then decreases with the number of parking requests. The average walking distance of users increases by about 10m, but it still meets the travel needs of users. Compared with the static weight model, the utilization rate and acceptance rate of the embedded dynamic weight model are increased by 2.2% and 10.88%, respectively. The dynamic weight model can better adapt to the dynamic changes of parking demand, so that parking resources can be fully utilized during peak hours. Compared with the static pricing model, the dynamic pricing mechanism was introduced to evenly distribute vehicles to each parking lot, and the equilibrium degree of parking area is reduced by 0.074 on average, so as to realize the balanced utilization of parking resources. The model can provide theoretical reference for parking allocation and management decision-making of shared parking platform and alleviate the problem of urban parking.

Study on Measuring Method of Vehicle Carbon Emission in Expressway Network



LIN Xukun, ZHANG Yang, LUO Zhiqing, et al

2022, 50(9):  22-28.  doi:10.12141/j.issn.1000-565X.220019

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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.

Study on Accident Risk Based on Driving Behavior and Traffic Operating Status



GUO Miao, ZHAO Xiaohua, YAO Ying, et al

2022, 50(9):  29-38.  doi:10.12141/j.issn.1000-565X.210629

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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.

Cross-line Combined Bus Scheduling Optimization Method Based on Passenger Flow Characteristic Identification



WENG Jiancheng, WANG Maolin, LIN Pengfei, et al

2022, 50(9):  39-48.  doi:10.12141/j.issn.1000-565X.210777

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With the increase of residents’ travel demand, there are higher requirements for bus operation efficiency and service quality. But bus operation companies usually adopt single-line scheduling, which often leads to the mismatch between passenger flow and transport capacity input, low bus service level, and resource utilization inefficiency. A more efficient scheduling optimization method is urgently needed. In the combined scheduling mode, manpower and vehicles are shared among multiple lines, which helps to integrate the existing bus resources and improve the matching degree of supply and demand of transport capacity and bus operation efficiency. In this paper, the identification rules of the cross-line scheduling line group and the determination method of the number of cross-line vehicles were proposed based on the characteristics of passenger flow. The optimization goal was to minimize the sum of passenger travel costs and bus operating costs, and an optimization model of bus cross-line combined scheduling with cross-line vehicles was constructed. The departure type and departure interval was encoded and it was solved by an improved genetic algorithm. The lines No.668 and No.122 in Beijing were selected as the case of cross-line combination scheduling, and the average waiting time of passengers, line load factor, capacity matching degree, passenger flow intensity and other indicators were introduced to evaluate the effectiveness of the optimization model. The results show that, under the condition of bus cross-line scheduling, the average waiting time of passengers on the supported bus lines is shortened by 11.8%; the line load factor is reduced by 9.8%; the capacity matching degree and passenger flow intensity are increased by 7.7% and 8.7%, respectively; passenger travel costs and bus operating costs are reduced by 15% and 6%, respectively.

Research on Roadside Environment Safety Based on Driver’s Attention Distribution Model



WU Yanxia, ZHOU Tong, HUANG Shuai, et al

2022, 50(9):  49-57.  doi:10.12141/j.issn.1000-565X.20210802

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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.

Characteristics of Transient Pressure and Pressure Gradient of a High-Speed Train Travelling Through a Double-Track Tunnel



DU Jianming, FANG Qian , WANG Gan, et al

2022, 50(9):  58-68.  doi:10.12141/j.issn.1000-565X.210608

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Transient pressure is one of the important factors affecting the structural safety of the lining of a high-speed railway tunnel. To further understand the characteristics of transient pressure and pressure gradient of a high-speed railway tunnel wall, a numerical simulation model for a high-speed train composed of eight cars with a scale of 1∶1 was established to investigate the aerodynamic characteristics induced by a high-speed train travelling through a double-track tunnel, based on the RNG k-ε two-equation turbulence model and the sliding mesh technique. The accuracy of the numerical method was verified by comparing the numerical simulation results with the field measurement. The influences of train speed, blockage ratio of train-tunnel, the number of trains, and two trains intersecting with the same speed on the transient pressure and pressure gradient on tunnel longitudinal middle section were further studied based on the analysis of the temporal-spatial traits of transient pressure on the tunnel wall. The results show that, the time-history curves of transient pressure in the tunnel cross-section are nearly overlapped, the pressure distribution in the cross-section is uniform, and the difference is low. Three typical pressure peak values (maximum positive peak value, negative peak value, and peak-to-peak value) show a linear relationship with the square of train speed or the square of blockage ratio, the positive peak value of the initial pressure gradient has a linear relationship with the third power of the train speed, the positive and negative peak values of pressure gradient have a linear relationship with the power of the blockage ratio (2.51~3.14). The relationship between the three typical pressure peaks and the number of trains satisfied an exponential function, the maximum positive peak value of pressure gradient of 8 trains is 1.25 times that of other cases (4~7 trains). The maximum positive and negative pressure peak values of the two trains intersecting with the same speed are 2.22 times and 1.15 times that of the single train passing by, respectively, and the maximum positive and negative peak values of pressure gradient of the two trains intersecting with the same speed are 1.87 times and 2.03 times that of the single train passing by, respectively. The relevant research results have important reference values for the safe operation of a high-speed train in tunnel.

Numerical Analysis of Wave Motion of Rigid Seals of Partial Air Cushion Support Catamaran



YANG Jinglei, SUN Hanbing, LI Xiaowen, et al

2022, 50(9):  69-77.  doi:10.12141/j.issn.1000-565X.210532

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Partial air cushion support catamaran (PACSCAT) is a new type of high-performance ship based on slender catamaran and supplemented by partial air-cushion support. Its bottom is flat and wide, and the air-cushion displacement volume accounts for about 30% of the whole ship. Due to the air cushion, the ship will have many nonlinear characteristics when sailing in the waves, influencing the motion performance of the hull heavily. The three-dimensional potential flow theory considers the three-dimensional effect of the flow field and it has been widely used in the field of ship hydrodynamics, so it can be effectively applied to the study of strong nonlinear motion characteristics of ships, which coincides with the study of nonlinear mechanics of hovercraft. The research was based on the rigid air seal form of the cushion system, and took into account the nonlinear characteristics of the air cushion. Therefore, in order to verify the form of numerical calculation method of PACSCAT with rigid seals, and study its movement characteristics in waves, this paper adopted the free surface method, and used overlapping grids and slip grids to analyze its performance in clam water. Furthermore, based on the best grid form, its navigation performance in regular waves was numerically simulated and compared with the experimental values, and then the calculation accuracy of the total hull resistance and the characteristics of the motion parameters under different wavelengths were studied. The results show that: overlapping grids have a higher hydrostatic resistance calculation accuracy than sliding grids, up to 5.2% when v=5.0 m/s. In the numerical calculation, the amplitude and average value of wave resistance are greater than the experimental value, and the error is the largest at the wavelength of 7.0 m. From the study of various wave motion parameters, it can be seen that there is no obvious difference between the duration curve of each motion parameter and the test value, and the calculated value of amplitude response is generally smaller than the experimental value, but the calculated value is obviously greater than the experimental value when λ/L is 2.33.

Network Synthesis Design Method of Nonlinear Mem-inerter Suspension System



NIE Jiamei, HUANG Xiaorong, ZHANG Xiaoliang, et al

2022, 50(9):  78-89.  doi:10.12141/j.issn.1000-565X.210677

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Mem-inerter, corresponding to the memcapacitor in electricity, is a nonlinear passive element with memory characteristics and adaptability. At present, nonlinear damper and spring have been widely studied, but there are few reports on nonlinear mem-inerter and its application in suspension. The structure and parameter design of mem-inerter suspension is still a difficult problem. Under this background, this study proved the equivalent inertance theorem of the mem-inerter according to the energy method. Based on this theorem, it proposed a network synthesis design method for the nonlinear suspension system of the mem-inerter, including structure synthesis and parameter synthesis. The structure synthesis regards the suspension network as a robust controller and obtains the mem-inerter suspension structure by solving the controller. The multi-objective parameter optimization method was used to determine the system parameters of the suspension, and the assembly parameters of the suspension were calculated based on the actual engineering situation. On this basis, the first-order and high-order mem-inerter suspension network system were designed, and the dynamic equations of 1/4 vehicle model was given. The simulation analysis of the suspension model was carried out. The transmission characteristics under sinusoidal excitation input show that each order of mem-inerter suspension has good load adaptability. The response characteristics under random road input show that compared with the corresponding linear suspension, the body acceleration of each order of nonlinear mem-inerter suspension designed by the network synthesis method is significantly reduced, and the dynamic tire load is improved, showing better driving comfort and handling stability and indicating the feasiblity of the suspension network synthesis design method.

Mechanical Engineering

Normal Contact Stiffness Model of Fine Particle Shot Peening Gear



MO Haijun, ZHAO Hang, CHENG Yu, et al

2022, 50(9):  90-98.  doi:10.12141/j.issn.1000-565X.210803

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Fine particle shot peening is one of the key technologies for high-performance gear manufacturing. In the study of gear dynamics and gear precision manufacturing, one of the important research topics is accurately analyzing the influence of fine particle shot peening on the normal contact stiffness of gear. In this paper, the changes of micro morphology of gear teeth surface before and after the fine particle shot peening were compared and analyzed through characterizing the micro morphology of the fine particle shot peened gear surface. Based on the fractal theory, the normal contact stiffness model of the fine particle shot peened gear was established considering the elastic-elastoplastic-plastic deformation of a single asperity and asperity interaction. It conducted a simulation analysis on the variation law of the normal contact stiffness along with the normal load, the fractal dimension D, the fractal rough amplitude G and the parameter of material property. The influence of fine particle shot peening on the normal contact stiffness of the gear was analyzed by extracting the fractal parameters of fine particle shot peened gear surface with the power spectral density function method. The results show that fine particle shot peening leads to randomly distributed micron or even nanoscale pits on the gear surface, and the decrease of surface roughness. Also, the gear surface roughness increases with the increase of fine particle shot peening strength. The normal contact stiffness increases with the increase of normal load, material yield strength, and fractal dimension D, and decreases with the increase of fractal roughness amplitude G. Fine particle shot peening can change the gear normal contact stiffness by changing the micro morphology of gear surface, and then change the fractal dimension D and fractal roughness amplitude G. Compared with the gear without fine particle shot peening, the normal contact stiffness of fine particle shot peened gears is improved. With the increase of shot peening strength, the normal contact stiffness of gears decreases. The research results provide a theoretical basis for gear dynamics research and high-performance gear manufacturing.

Design and Analysis for Actively Modified Gear with Zero Amplitude of Loaded Transmission Error



JIANG Jinke FANG Zongde

2022, 50(9):  99-108.  doi:10.12141/j.issn.1000-565X.210751

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To eliminate stiffness excitation, this paper proposed an approach of design and analysis for actively modified gears with zero amplitude of loaded transmission error (ALTE). Firstly, the maximum bearing deformation of mesh cycle was obtained based on tooth contact analysis and loaded tooth contact analysis (LTCA) for predesign modified gears. Secondly, taking bearing deformations of meshing period being equal to the maximum value as the known condition, a novel equation for LTCA was developed, then compensating tooth gaps from pitch error (additional modifications) were determined by solving the equation in reverse. Thirdly, the compensating gaps characterized by equal values along instantaneous contact line of tooth were constrained according to the meshing positions, and was added to the predesigned modified pinion to produce novel modified gears with zero ALTE. The method integrated geometric analysis and mechanical analysis of tooth, and it can accurately and quickly obtain any modified gears with zero ALTE. The results show that shape and size determined by the compensating gaps surface are related to the locations of tooth, the predesign modification and load. On the one hand, when the differences of predesigned modification is small, the rule of compensation modification curve is basically opposite to the ALTE of predesigned tooth modification, that is, the larger the bearing deformation is, the smaller the compensation gaps is.Then the overall compensation modification is also small due to only compensating the bearing deformation differences actually. On the other hand, when the differences of the predesigned modification is large, the overall compensation modification is also large due to compensating the differences of both bearing deformation and predesigned modification at the meshing position. Besides, the tooth contact pattern is not changed with the compensation modification and ALTE are reduced on wider loads for gears with zero ALTE based on preset topology modification. Appropriate locations and predesign modifications make the additional modification well integrate into the predesigned and modified surface, so as to obtain the machinable modified pinion with zeros ALTE. It provides a theoretical reference for design and analysis of tooth with vibration reduction and high performances.

On the Mechanism of Multi-process Compound Spinning for Thin-walled Deep Cup Shaped Parts



XU Xiao, ZHANG Chuanyang, XIAO Gangfeng, et al

2022, 50(9):  109-115.  doi:10.12141/j.issn.1000-565X.210804

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To solve the problems of long forming process, low efficiency, and difficult quality control in the traditional machining methods for thin-walled deep cup-shaped parts, a deep drawing-flow multi-process compound spinning method, which can realize the precise preparation of such parts with high efficiency, was proposed in this paper. Based on software Abaqus, a finite element model of Compound Spinning for the deep cup-shaped part of SPHC steel was established. It was used to study the strain and stress distribution and the flow of the material in the compound spinning process of deep cup shaped parts, and reveal the forming mechanism of compound spinning. Combining with the compound spinning forming experiments, the correctness of the finite element model was verified. The results show that the multi-process compound spinning process can obtain the thin-walled deep cup-shaped parts with good forming quality in single spinning process. According to the deformation of materials, multi process compound spinning can be divided into drawing spinning stage, flow spinning initial stage and compound spinning stable stage. In the initial stage of flow spinning, the maximum equivalent strain rises sharply with the progress of spinning. In the stable spinning stage, the maximum equivalent strain appears in the formed region, and its deformation state is axial and tangential tension and radial compression, while the transition region is axial tension, radial and tangential compression. In the initial stage of flow spinning, the axial flow of the material in the die area to the mouth increases with the increase of the axial offset between the rollers for deep drawing and flow spinning. In the stable stage of compound spinning, the outer area of the blank in contact with the roller for deep drawing spinning is subject to three-dimensional compressive stress, while the inner area is subject to three-dimensional tensile stress, and the contact area between the blank and the roller for flow spinning is subject to three-dimensional compressive stress. To ensure the spinning forming quality, the axial offset between the roller for spinning drawing and the roller for flow spinning should be greater than 5.3 mm.

A Force-Sensorless Dragging Teaching Method Based on Disturbance Kalman Filter for Robot



ZHANG Tie, XU Jinsheng, ZOU Yanbiao

2022, 50(9):  116-125.  doi:10.12141/j.issn.1000-565X.210781

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The dragging teaching method is easy to operate and has high teaching efficiency, which is more in line with modern flexible production. To realize the dragging teaching of industrial robots, it is necessary to accurately measure the external force and control the motion caused by the external force. In order to measure the external force exerted by the operator without torque sensor, an external force observer based on disturbance Kalman filter was designed. The observer takes the external joint torque as the disturbance term, and introduces generalized momentum to establish the state space equation of the robot system, and then uses the Kalman filter algorithm to obtain the optimal observed value of the external torque. Among them, in order to improve the estimation accuracy, the robot dynamic model was established by combining the rigid-body dynamic model and a deep neural network, which not only avoids modeling the complex friction torque but also compensates for the unmodeled factors through the deep neural network. Besides, in order to realize the leading control of the robot in the process of dragging teaching, the dynamic response relationship between the teaching motion and the external torque is equivalent to a mass damping system. An admittance control method with adaptive damping was proposed to convert the observed external torque into the desired joint angle of the teaching motion, and adaptively adjust the system damping parameters according to the change trend of the external torque to improve the teaching effect of the robot. The experiment results show that the proposed dynamic model has a lower mean square root error in the prediction torque, which can reduce the error by no less than 20%. The proposed control scheme can realize the dragging teaching without torque sensors on the six-degree-of-freedom industrial robot, and the adaptive damping method can reduce the torque required to rotate the joint by about 19%, which is more conducive to the start and stop of the teaching motion.

A Robot Grasping Policy Based on Viewpoint Selection Experience Enhancement Algorithm



WANG Gao, CHEN Xiaohong, LIU Ning, et al

2022, 50(9):  126-137.  doi:10.12141/j.issn.1000-565X.210769

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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.

Multi-objective Energy Management Strategy of HEV Based on Improved Dynamic Programming Method



ZHAO Kegang, HE Kunyang, LI Jie, et al

2022, 50(9):  138-148.  doi:10.12141/j.issn.1000-565X.210771

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Hybrid electric vehicle Energy Management Strategy (EMS) optimization is a multi-objective and multi-stage decision-making problem that needs to comprehensively optimize several performance indicators of hybrid electric vehicles. The traditional multi-objective optimization algorithm faces challenges such as low efficiency and difficult to guarantee convergence when dealing with these problems. Combined with the idea of non-dominated sorting algorithm, this paper extended the traditional Dynamic Programming (DP) to the field of multi-objective optimization, and proposed Non-dominated Sorting Dynamic Programming (NSDP). When using this algorithm, the driving condition was divided into several stages firstly. In each stage, the cumulative target value vector generated by the hybrid electric vehicle in different control strategies was obtained, and the current non dominated solution set and the corresponding control strategy were obtained through the non dominated sorting algorithm. Then, the non dominated solution set of each stage was used for reverse iteration in turn, until the leading edge of the non dominated solution set and the corresponding energy management control strategy of the whole driving cycle were obtained. In the simulation experiment, Weighting Dynamic Programming (WDP) and Non-dominated Sorting Dynamic Programming were applied to solve the optimization problem of multi-objective energy management strategy for power split hybrid electric vehicles and series parallel hybrid electric vehicles under constant acceleration conditions. The results show that NSDP not only can effectively complete the solution and ensure convergence, but also has significant advantages in homogeneity of solution set and solving efficiency. Furthermore, NSDP was used to solve the energy management optimization problem of series parallel hybrid electric vehicles running in Worldwide Harmonized Light Duty Vehicle Test Cycle (WLTC). The non dominated solution set can be used to analyze the working characteristics of vehicles and provides a reliable reference for the formulation of actual energy management strategy.