Current Issue : April - June Volume : 2021 Issue Number : 2 Articles : 5 Articles
This article presents an innovative self-reconfigurable battery (SRB) architecture, which is able to generate directly at its output any waveform signals. Thanks to that specific characteristic of the proposed system, it is even possible to dispense with any AC charger. Although the individual ability of each cell in the battery pack to perform an efficient active cell balancing has been already studied in the literature, the system presented in this article is the first of its kind. This article describes a real prototype of a high frequency SRB of 128 cells and demonstrates that it can be charged without any dedicated charger directly on the electrical grid, by generating a sinusoidal waveform voltage, while perfectly balancing the cells in real time....
This paper explores deep into the collaborative scheduling of common rail dual automatic guided vehicles (AGVs). Firstly, a dual AGV scheduling model was constructed to minimize the overall time of material distribution. Then, a novel scheduling algorithm was developed to dynamically plan the orders based on time windows. To effectively minimize the distribution time, heuristic algorithms were adopted to initialize the distribution order of materials. On this basis, the collaboration between the two AGVs was innovatively designed based on dynamic planning and time windows, making up for the defects of traditional methods in AGV cooperation. This greatly shortens the running time of the entire system in material distribution. The computing results fully demonstrate the efficiency and rationality of our algorithm. Finally, our algorithm was proved to be superior to the benchmark method through experiments on actual industrial instances....
In the large-scale transportation, the leveling of the transport vehicle loading platform will determine the safety of the transportation. Therefore, the research on the leveling of the transport vehicle loading platform with hydraulic suspension is carried out. The hydraulic suspension systems are simplified as four-point support. Based on the multisensor data collected by the pressure sensors of the suspension hydraulic cylinders and the double axis inclination sensor of the load-bearing platform, the leveling control system of the four-point load-bearing platform is designed according to the principle of the highest point chasing. In order to verify the precision of the leveling method, the leveling of the control system is simulated by using the software AMESim and MATLAB, and the PID controller is added. The results show that the leveling precision and velocity of this method fully meet the leveling requirements of the transport vehicle. On the basis, the leveling control system for the 100 ton transport vehicle is designed. The double axis inclination sensor is used to monitor the tilt angle of the loading platform in real time. The controller can make the suspension hydraulic cylinders act accordingly according to the four height differences to keep the loading platform level. Finally, the leveling experiment of the transport vehicle is carried out, and the lifting experiment is carried out under the condition of no load to full load. It is concluded that the displacement of the four points of the loadbearing platform of the transport vehicle is basically the same. The leveling control system can control the inclination angle of the platform within 0.25 degrees, and the leveling time is less than 1 second. The leveling process has higher precision and shorter time than other methods, which can provide reference for the leveling design of similar platforms....
Continuous development of urban infrastructure with a focus on sustainable transportation has led to a proliferation of vulnerable road users (VRUs), such as bicyclists and pedestrians, at intersections. Intersection safety evaluation has primarily relied on historical crash data. However, due to several limitations, including rarity, unpredictability, and irregularity of crash occurrences, quantitative and qualitative analyses of crashes may not be accurate. To transcend these limitations, intersection safety can be proactively evaluated by quantifying near-crashes using alternative measures known as surrogate safety measures (SSMs). This study focuses on developing models to predict critical near-crashes between vehicles and bicycles at intersections based on SSMs and kinematic data. Video data fromten signalized intersections in the city of San Diego were employed to train logistic regression (LR), support vector machine (SVM), and random forest (RF) models. A variation of time-to-collision called T2 and postencroachment time (PET) were used to specify monitoring periods and to identify critical near-crashes, respectively. Four scenarios were created using two thresholds of 5 and 3 s for both PETand T2. In each scenario, fivemonitoring period lengths were examined. The RF model was superior compared to other models in all different scenarios and across different monitoring period lengths. The results also showed a small trade-off between model performance and monitoring period length, identifying models with monitoring period lengths of 10 and 20 frames performed slightly better than those with lower or higher lengths. Sequential backward and forward feature selection methods were also applied that enhanced model performance. The best RF model had recall values of 85% or higher across all scenarios. Also, RF predictionmodels performed better when considering just the rear-end near-crashes with recalls of above 90%....
Vehicle type recognition algorithms are broadly used in intelligent transportation, but the accuracy of the algorithms cannot meet the requirements of production application. For the high efficiency of the multilayer perceptive layer of Network in Network (NIN), the nonlinear features of local receptive field images can be extracted. Global average pooling (GAP) can avoid the network from overfitting, and small convolution kernel can decrease the dimensionality of the feature map, as well as downregulate the number of model training parameters. On that basis, the residual error is adopted to build a novel NIN model by altering the size and layout of the original convolution kernel of NIN. The feasibility of the algorithm is verified based on the Stanford Cars dataset. By properly setting weights and learning rates, the accuracy of the NIN model for vehicle type recognition reaches 97.2%....
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