Wi-Fi HaLow (IEEE 802.11ah) has emerged as a promising solution which can support Internet of Things (IoT) applications where energy efficiency and extended coverage are important. A key feature of Wi-Fi HaLow is the Target Wake Time (TWT) mechanism, which allows devices to schedule wake-up times, significantly reducing IDLE listening and energy consumption. However, there is currently no energy consumption model, leaving a gap in calculating how much energy a device actually consumes in a real network. This study aims to bridge this gap by developing a forecast model to accurately predict the energy consumption of devices with TWT enabled. The proposed model is then validated through experimental measurements using real Wi-Fi HaLow-compatible devices, ensuring an accurate representation of practical energy consumption. This research provides empirical insights and recommendations for optimizing network configurations in battery-constrained environments. In particular, the proposed energy consumption model can assist businesses in accurately estimating and managing energy usage, which is essential for cost-effective planning and improving operational efficiency in real-world IoT deployments.
Telecommunication, Transportation and communications
Road traffic crash severity is shaped by a complex interplay of human, vehicular, environmental, and infrastructural factors. While machine learning (ML) has shown promise in analyzing crash data, gaps remain in model interpretability and region-specific insights, particularly for the UK context. This study addresses these gaps by evaluating supervised ML models – Decision Tree, Support Vector Machine (SVM), and LightGBM – to predict crash severity using 2022 UK accident data. The research emphasizes interpretability through SHapley Additive exPlanations (SHAP) to identify critical factors influencing severity outcomes. Results demonstrate that LightGBM outperforms other models in predictive performance, with police officer attendance at the scene, speed limits, and the number of vehicles involved emerging as pivotal determinants of severity. The analysis reveals that higher speed limits and single-vehicle collisions correlate with severe outcomes, while police presence may mitigate accident severity. However, the study acknowledges limitations, including dataset constraints. By integrating ML with post-hoc interpretability techniques, this work advances actionable insights for policymakers to prioritize road safety interventions, such as optimizing enforcement strategies and revising speed regulations. The findings underscore the potential of interpretable ML frameworks to enhance understanding of crash dynamics and inform targeted safety measures, contributing to global efforts to reduce traffic-related fatalities and injuries.
Tomislav Kovačević, Ružica Kljajić, Hrvoje Glavaš
et al.
This paper analyzes the impact of electromobility on distribution grids and voltage stability. In line with current legislation and the European Commission’s plans for the future of electromobility, the aim is to increase the share of electric vehicles to 50% by 2050. However, achieving this target can be challenging due to the characteristics and features of the electric vehicle charging stations and the associated charging methods, which can lead to constraints within the network. The analysis includes the integration of single-phase and three-phase chargers on a radial feeder, as well as the determination of the maximum number of vehicles that can be accommodated on a given feeder without compromising voltage stability. Five scenarios are evaluated using the DigSilent software package to gain a better understanding of the impact of electromobility on the distribution grid.
Introduction. Reversible plate compactors are soil compaction machines with a flat operating device, having two or more unbalanced shafts and ability to reverse the direction and movement speed. Reversible plate compactors may be driven by gasoline, diesel or electric engines. The efficient operation of reversible plate compactors is only possible with the rational selection of technical specifications, such as oscillation frequency and driving force of the vibration exciter, base plate width, engine power, etc. To establish correlations between the technical specifications of reversible plate compactors, to assess the influence of the engine type on the main parameters and to identify the areas for improving this type of equipment, the statistical analyses was conducted.Materials and methods. 484 models of reversible plate compactors were scrutinized. The information on the models were obtained from official websites of plate compactors manufacturers and their dealers. Data processing was performed in Microsoft Excel.Results. The variation ranges of the main parameters were determined and regression equations for correlations between the oscillation frequency of the vibration exciter, the driving force, the width of the base plate, the relative exciting force and the mass of reversible plate compactors were derived. Correlation coefficients were obtained for each regression dependence. The influence of the engine type on the variation range of reversible plate compactors’ main parameters was analyzed.Conclusion. The type of engine has almost no effect on the parameters of reversible plate compactors in the corresponding mass ranges. Relatively low correlation coefficients let us suggest that manufacturers do not have reliable methods for justification of the technical specifications of reversible plate compactors. The obtained correlations may be recommended for verification of some technical specifications of reversible plate compactors. In recent decades, the values of oscillation frequency and relative exciting force have increased significantly, which affects the nature of interaction between a reversible plate compactor and soil.
In the simulation data processing of maglev tracks, the filtering and extraction of maglev track point cloud data is an important link. Thus, practical applications should adopt an efficient filtering method according to the characteristics of the maglev data to be extracted. The point cloud data objects of the maglev track primarily include the image data of the maglev track, which is obtained by Unmanned Aerial Vehicle (UAV) oblique photography and formed into dense point cloud data after 3D reconstruction, and the laser point cloud data, which is obtained by handheld lidar scanning of the maglev track. Based on the data characteristics of these point clouds and considering the complex scenes around the maglev track, the two types of point clouds are mixed and filtered. First, the octree downsampling method is used for laser point cloud data, which effectively reduces the order of magnitude of the point cloud data and saves running time. The Cloth Simulation Filtering (CSF) method is then used on the laser point cloud and dense point cloud data to filter the ground plane point cloud and retain the non-ground point cloud data, respectively. A Statistical Outlier Removal (SOR) filtering method is used to screen a large number of outliers. Based on the characteristics of the maglev track, point clouds outside the coordinate range are filtered through straight-through filtering. On the premise of not changing the structure of the maglev track, the experimental results show that the filtering rates of the proposed method are 86.15% and 64.76% for the octree-downsampled laser point cloud data and the dense point cloud data without octree downsampling, respectively. These two point cloud datasets have similar structural ranges after hybrid filtering and a number of point clouds of the same order of magnitude, which can be effective for methods such as feature extraction of point clouds in maglev orbits.
In the traditional mass concrete temperature field calculation, the accuracy of the thermal parameters is extremely important. However, the actual thermal parameters of mass concrete may have some errors with the laboratory-measured values or specification values due to the site ambient temperature, concrete surface insulation measures, cooling water flow, etc. Therefore, it can be combined with the measured temperature of the field temperature sensors using the sparrow search algorithm (SSA) for the inverse analysis of thermal parameters. Firstly, to address the problem that SSA has low convergence accuracy and easily falls into local optimum, a mixed strategy was adopted to improve the algorithm, including Logistic Chaos mapping initialization of the population, the introduction of adaptive weighting factors, and the use of the Cauchy mutation strategy. Then, the performance test was carried out to compare the performance of the algorithm with three different intelligent algorithms and reflect the superiority of the SSA that was improved by mixed strategies (SSAIMSs). Finally, the proposed method was applied to the thermal parameter inversion of a mass concrete pile cap. The inversion results demonstrated that SSAIMSs can improve the accuracy and speed of thermal parameter inversion, and the calculated results of the thermal parameters and temperatures obtained using the SSAIMSs matched well with the measured results in the field, which can meet the accuracy requirements of the actual engineering.
Compared with open roadways, traffic safety in highway tunnels requires more attention to build smoothly transitioned and well-coupled light environments for drivers to alleviate visual discomfort so as to achieve a balanced sense of driving safety and comfort. In this study, in order to overcome the drawbacks of existing tunnel lighting control modes that disregard the color temperature of natural light characteristics and collaborative influence of color temperature and luminance of natural light on tunnel lighting quality, one artificial neural network (ANN) model is designed and trained to simulate one physical lighting control system that takes into consideration color temperature and luminance simultaneously. In this model, multiple parameters of discrete and continuous types of input layer and output layer are synergistically analyzed. The model was also trained with quantities of field data from one tunnel in service and includes one hidden layer with 10 neurons. The simulation results showed that this model obtains a high degree of fitness with inside luminance and 100% recognition rate with inside color temperature in the threshold zone, which conforms to the regulation strategy of actual lighting control systems with high confidence. The proposed model will greatly enhance the reliability and sustainability of the lighting system during its normal operation, which can also support other lighting scenarios due to its flexibility and scalability with multiple-input and multiple-output (MIMO) capabilities.
Sufficient synthetic aperture radar (SAR) data is the key element in achieving excellent target recognition performance for most deep learning algorithms. It is unrealistic to obtain sufficient SAR data from the actual measurements, so SAR simulation based on electromagnetic scattering modeling has become an effective way to obtain sufficient samples. Simulated and measured SAR images are nonhomologous data. Due to the fact that the target geometric model of SAR simulation is not inevitably consistent with the real object, the SAR sensor model in SAR simulation may be different from the actual sensor, the background environment of the object is also inevitably different from that of SAR simulation, the error of electromagnetic modeling method itself, and so on. There are inevitable differences between the simulated and measured SAR images, which will affect the recognition performance. To address this problem, an SAR simulation method based on a high-frequency asymptotic technique and a discrete ray tracing technique is proposed in this paper to obtain SAR simulation images of ground vehicle targets. Next, various convolutional neural networks (CNNs) and AugMix data augmentation methods are proposed to train only on simulated data, and then target recognition on MSTAR measured data is performed. The experiments show that all the CNNs can achieve incredible recognition performance on the nonhomologous SAR data, and the RegNetX-3.2GF achieves state-of-the-art performance, up to 84.81%.
Summary: It is critical to develop a low-cost and environmentally friendly system to manufacture and recycle lithium-ion batteries (LIBs) as the demand on LIBs keeps increasing dramatically. Conventional LIB cathodes are manufactured using N-methyl-2-pyrrolidone as the solvent, which is expensive, highly toxic, flammable, and energy intensive to produce and recover. Ideally, a close-loop industrial supply chain should be built, in which the batteries are manufactured, market harvested, and recycled with minimal external toxic solvent through the whole system. This work demonstrates a green and more sustainable manufacturing method for LIBs where no hazardous organic solvent is used during electrode manufacturing and recycling. The electrodes fabricated via water-based processing demonstrate comparable rate performance and cycle life to the ones from conventional solvent-based processing. Utilization of a water-soluble binder enables recovering the cathode compound from spent electrodes using water, which is successfully regenerated to deliver comparable electrochemical performance to the pristine one.
With the rapid development of the subway, more and more people choose it as the main method of transportation. However, practically, the large number of pedestrians near some large metro stations can also correspondingly affect the traffic of motor vehicles on the roads adjacent to the stations. In this study, coordinated control of the traffic signal which considers the pedestrian crossing delay is studied based on this background. Firstly, the model of progression band in adjacent intersections is analyzed comprehensively, and the calculation formulas of progression bandwidth and the delay of vehicles which are from the progression of traffic flow under different conditions are given. Secondly, five different models of pedestrian delay are analyzed. Under different conditions of motor vehicle and pedestrian traffic flow, the Vissim fitting and proofreading are carried out and the optimal models under different conditions are obtained. Finally, the bilevel programming problem which fuses the above two models is determined; by coding an algorithm, it can be resolved. Furthermore, taking eight signalized intersections from Jiming Temple to Daxinggong along Nanjing Metro Line 3 as the actual background, the calculation and optimization of coordinated control are carried out. It is found that at the expense of the traffic efficiency of large intersections to a certain extent, a wider progression band can be formulated on the roads between them, and pedestrian delays can be reduced in general.
Transportation engineering, Transportation and communications
Raised Pavement Markers (RPMs) are used by a number of transportation agencies with the objective of improving roadway safety, especially in complex roadway geometries and along wet roads. Because of maintenance and cost issues, many transportation agencies are exploring alternatives to RPMs such as wet reflective pavement tape and barrier-mounted reflective delineators. In order to assess the relative potential of these devices to contribute to nighttime driving safety, the luminances of new and used RPM samples from different manufacturers and having different colors and of several alternative delineation devices were measured in the laboratory using a range of geometric conditions relevant to the driving task. From these data, Luminances under representative low-beam headlight illumination were determined and these quantities were used to estimate driver visual performance. Large variations in luminance yielded relatively small differences in visual performance for a viewing distance of 100 m, primarily because of the plateau characteristic of visual performance. Differences in threshold visibility distances were greater, with distances at identification threshold for the devices measured ranging approximately from 150 to 400 m. Used RPMs had luminances 20…30% lower than new RPMs but similar visibility characteristics as new devices. The analysis method in this study may be useful for practitioners seeking to characterize the visual effectiveness of RPMs and other roadway delineation devices and systems.
Abstract This paper divides the time of railway container transport chain into the drayage time by road, the storage time at departure station, the railway transit time and the storage time at arrival station according to operation procedure. Based on definition of the travel time reliability of railway container chain, the HL-RF algorithm in the field of structural engineering is introduced and travel time reliability of railway container chain evaluation model is built. Then railway container transport chain from Bengbu to Shanghai, China is considered for this study. On the basis of analysing the operation time distribution of each part of the transport chain, we imported five reliability evaluation indices namely time reliability, the average time for transportation chain, reserve time, buffer time and tolerable time boundary. Finally, the relationship between different influencing factors and reliability is quantified and various countermeasures for improving the management level of railway container transportation chain are proposed.
Road transport is recognized as having a negative impact on the environment. Policy has focused on replacement of the internal combustion engine (ICE) with less polluting forms of technology, including battery electric and fuel cell electric powertrains. However, progress is slow and both battery and fuel cell based vehicles face considerable commercialization challenges. To understand these challenges, a review of current electric battery and fuel cell electric technologies is presented. Based on this review, this paper proposes a battery electric vehicle (BEV) where components are sized to take into account the majority of user requirements, with the remainder catered for by a trailer-based demountable intelligent fuel cell range extender. The proposed design can extend the range by more than 50% for small BEVs and 25% for large BEVs (the extended range of vehicles over 250 miles), reducing cost and increasing efficiency for the BEV. It enables BEV manufacturers to design their vehicle battery for the most common journeys, decreases charging time to provide convenience and flexibility to the drivers. Adopting a rent and drop business model reduces the demand on the raw materials, bridging the gap in the amount of charging (refueling) stations, and extending the lifespan for the battery pack.
The paper focuses on the experimental verification of the results derived from numerical simulations, based on a model of the bogie-track system, where the vertical track irregularities are introduced in the form of a pseudorandom function. This function comes from an original method of synthesizing the vertical track irregularities, depending on the geometric quality of the track and on the velocity. To verify the method, the root mean square (RMS) of the simulated accelerations in the axles and the bogie frame against each axle is compared to the experimental accelerations within the frequency range of wavelengths of the track vertical irregularities from 3 to 120 m. The results have shown a good correlation between the simulated RMS accelerations for a low quality track and the measured RMS accelerations.
Alessandro Macêdo de Araújo, Manoel Mendonça de Castro Neto
Este artigo tem como objetivo principal propor um método para a modelagem do processo de aceitação de brechas em interseções urbanas não semaforizadas utilizando o microssimulador VISSIM. O método proposto tem como medida-alvo o tempo que o motorista leva no processo de avaliação das brechas, ou seja, o tempo de espera enquanto está na primeira posição da fila. O c2 da aderência entre as distribuições dos tempos de espera (simulados e observados) e a diferença entre as médias foram utilizados na estimação da brecha crítica. O método foi aplicado em uma interseção da cidade de Fortaleza. Os resultados indicaram valores levemente diferentes da brecha crítica entre os movimentos de conversão. O segundo objetivo deste trabalho é comparar o método proposto com o método de calibração mais convencional, no qual a medida-alvo é uma medida de desempenho do tráfego, como o tamanho médio da fila. O método proposto apresentou melhores resultados.