Search Results (46)

In a scenario where fuel costs are notably high and the policies that we are currently witnessing tend to limit the fossil fuel resource that powers most heavy goods transport services, the optimization of space in vehicles transporting these goods, such as trucks and shipping containers, becomes an indisputable and urgent need. This urgency is manifested in the need to minimize the costs associated with transport, given its increasing growth. This experiment aims to study and implement an Internet of Things (IoT)-based solution to the problem previously presented. The developed system comprises a computer and a millimeter-wave (mmWave) sensor. The computer processes the data captured by the sensor through code in Python language and displays, through a web page allocated in a cloud/server, the volume occupied by the load, as well as the percentage of occupied and free space, considering the volume provided by the user. The validation tests consisted of checking the results in 2D and 3D, all carried out in a controlled environment focused on the detection of static objects. For the 3D analysis, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm was used to obtain the points for extracting the volume of the detected object. Several objects with different dimensions were used and the error ranged from 0.6% to 7.61%. These results denote the confirmation of the reliability and efficacy of the presented solution. With this, it was concluded that this new solution has significant potential to enter the market and compete with other existing technologies. Full article

The population surge has led to a corresponding increase in the demand for high-rise buildings, bridges, and other heavy structures. In addition to gravity loads, these structures must withstand lateral loads from earthquakes, wind, ships, vehicles, etc. A piled raft foundation (PRF) has emerged as the most favored system for high-rise buildings due to its ability to resist lateral loads. An experimental study was conducted on three different piled raft model configurations with three different relative densities (D_r) to determine the effect of D_r on the lateral response of a PRF. A model raft was constructed using a 25 mm thick aluminum plate with dimensions of 304.8 mm × 304.8 mm, and galvanized iron (GI) pipes, each 457.2 mm in length, were used to represent the piles. The lateral and vertical load cells were connected to measure the applied loads. It was found that an increase in D_r increased the soil stiffness and led to a decrease in the lateral displacement for all three PRF models. Additionally, the contribution of the piles in resisting the lateral load decreased, whereas the contribution of the raft portion in resisting the lateral load increased. With an increase in D_r from 30% to 90%, the percentage contribution of the raft increased from 42% to 66% for 2PRF, 38% to 61% for 4PRF, and 46% to 70% for 6PRF. Full article

Emissions standards describe the fuels, the procedures, and, among others, the analyzers to be used for the measurement of the different compounds during the type-approval of heavy-duty engines and vehicles. Traditionally, NOx, CO, hydrocarbons, and CO₂ were the gaseous compounds measured within the Euro standard, with the later addition of CH₄ and NH₃. Euro 7, introduced in early 2024, expanded those compounds, requiring the measurement of N₂O and HCHO. With an increasing number of molecules that need to be measured and introducing carbonless fuels, such as hydrogen, that present different requirements compared to carbon-based fuels, the test procedure needs to be updated. The performances of three laboratory-grade instruments and three portable emissions measurement systems based on Fourier-transformed infrared (FTIR) or quantum cascade laser infrared (QCL-IR) technologies were investigated while measuring from the tailpipe of a Diesel engine and a compressed natural gas (CNG) vehicle. All instruments presented good agreement when emissions of NOx, CO, CH₄, NH₃, N₂O, HCHO, and CO₂ were compared using: Z-score, F-test and two tail t-test of student. Water concentration measured by the four FTIRs was also in good agreement. Moreover, the dry emissions of CO₂ and CO measured by the laboratory non-dispersive infrared (NDIR) and corrected using water were a few percentages different from those obtained using the regulated carbon-based approach. The results indicate that all the investigated systems are suitable for the measurement of the investigated gaseous compounds, including CO₂ and H₂O. Full article

In some scenarios, electric heavy-duty trucks with battery swapping mode (ETBSm) are more cost-effective than battery charging mode. The viability of battery swapping stations is contingent upon the operational requirements and range capabilities of the ETBSm. Low temperatures have the effect of reducing the range of the ETBSm, thereby creating difficulties for battery swapping. This article proposes the use of motor waste heat recovery (MWHR) to heat batteries, which would improve range. A number of subsystem models have been established, including the ETBSm, battery, motor, and thermal management system (TMS). The calibration of battery temperature and motor efficiency is achieved with a model error of less than 5%. Comparison of performance, such as temperature, energy consumption, and range, when using only positive temperature coefficient (PTC) heating and when using both PTC heating and motor waste heat. The results indicate a 15% increase in the rate of rise in battery temperature and a 10.64 kW·h reduction in energy consumption under Chinese heavy-duty vehicle commercial vehicle test cycle (CHTC) conditions. Then, the motor waste heat percentage, energy consumption, and range are analyzed at different ambient temperatures. At an ambient temperature of −20 °C, −10 °C, and 0 °C, the percentage of the motor waste heat is 32.1%, 35%, and 40.5%; when 75% of the state of charge (SOC) is consumed, the range is improved by 6.55%, 4.37%, and 4.49%. Additionally, the effect of the PTC heater on temperature characteristics and power consumption is investigated by changing the target temperature of the coolant at the battery inlet. In accordance with the stipulated conditions of an ambient temperature of −20 °C and a target coolant temperature of 40 °C at the battery inlet, the simulation results indicated a battery temperature rise rate of 0.85 °C/min, accompanied by a PTC power consumption of 15.6 kW·h. This study demonstrates that as the ambient temperature increases, the utilization of motor waste heat becomes more effective in reducing PTC heating power consumption. At the lowest ambient temperature tested, the greatest improvement in driving range is observed. It is important to note that while an increase in the target heating temperature of the PTC helps to raise the battery temperature more rapidly, this is accompanied by a higher energy consumption. This article provides a reference for the ETBSm with MWHR. Full article

In the field of freight transport, the goal of sustainable development requires us to improve the efficiency of freight transport while reducing its negative impact on the environment, such as reducing carbon emissions and noise pollution. There is no doubt that changes in freight characteristics and volumes are compatible with the objectives of sustainable development. Thus, mining the travel distribution and freight volume of trucks has an important supporting role in the freight transport industry. In terms of truck travel, most of the traditional approaches are based on the subjective definition of parameters from the trajectory data to obtain trips for certain vehicle types. As for freight volume, it is mostly estimated through manual surveys, which are heavy and inaccurate. In this study, a data-driven approach is adopted to obtain trips from the trajectory data of heavy trucks. Combined with the traffic percentage of different vehicle types collected by highway traffic survey stations, the trips of heavy trucks are extended to all trucks. The inter-city and intra-city freight volumes are estimated based on the average truck loads collected at the motorway entrance. The results show a higher proportion of intra-city trips by trucks in port cities and a higher proportion of inter-city trips by trucks in inland cities. Truck loading and unloading times are focused in the early morning or at night, and freight demand in Shandong Province is more concentrated in the south. These results would provide strong support for optimizing freight structures, improving transportation efficiency, and reducing transportation costs. Full article

This study assessed the impacts of a toll information sign with different toll lane configurations on queue length and collision risk at a toll plaza with an estimated high percentage of heavy vehicles (HVs). The toll information sign displays information about different toll payment methods for cars and HVs upstream of the toll booth. The impacts were assessed for the toll plaza of the Gordie Howe International Bridge under construction at the Windsor–Detroit international border crossing using a traffic simulation model. Results show that the toll information sign upstream of the toll plaza and converting the toll lanes with multiple toll payment methods to electronic toll collection (ETC)-only lanes reduced queue length and collision risk. However, increasing the number of HV-only lanes for a higher percentage of HVs increased lane-change collision risk. Thus, it is recommended that toll lane configurations be changed based on the percentage of HVs to reduce collision risk at a toll plaza. Full article

Recently, the use of powerful and heavy vehicles for timber harvesting on flat or slightly sloping terrains has been widely expanded to provide safe working conditions and high productivity. However, soil disturbances during ground-based mechanized operations in South Korea are not fully investigated and difficult to avoid. Therefore, we compared the soil displacement and compaction (bulk density and hydraulic conductivity) between two different operations: cut-to-length (CTL) logging with a harvester and forwarder, and whole-tree (WTH) logging with a harvester and skidder. After clear-cutting, severe visual disturbances and rut depths were more prevalent in the forwarding trails than in the skidding trails. The CTL harvesting method created larger amounts of slash (6.9 kg/m²) along the trails than the WTH harvesting did (1.8 kg/m²). We found a significant difference in the compaction between the reference and the track and a negative correlation between the slash quantity values and the percentage increase in compaction. Our results showed that using skidding extraction can cause more severe impacts than forwarding extraction. Thus, these results may be helpful in understanding the influence of ground-based CTL and WTH harvesting operations and achieving best practices to minimize the environmental impacts on soil. Full article

This research utilized long short-term memory (LSTM) to oversee an RLS-based mass estimator based on longitudinal vehicle dynamics for heavy-duty vehicles (HDVs) instead of using the predefined rules. A multilayer LSTM network that analyzed parameters such as vehicle speed, longitudinal acceleration, engine torque, engine speed, and estimated mass from the RLS mass estimator was employed as the supervision method. The supervisory LSTM network was trained offline to recognize when the vehicle was operated so that the RLS estimator gave an estimate with the desired accuracy and the network was used as a reliability flag. High-fidelity simulation software was employed to collect data used to train and test the network. A threshold on the error percentage of the RLS mass estimator was used by the network to check the reliability of the algorithm. The preliminary findings indicate that the reliability of the RLS mass estimator could be predicted by using the LSTM network. Full article

As urban traffic challenges intensify, the growing interest for fully actuated control systems in intersection management is on the rise due to their capacity to adapt to dynamic traffic demands. These systems play a crucial role in sustainable traffic solutions, significantly reducing delays and emissions and enhancing overall system efficiency. The optimal performance of these systems relies on effectively facilitating vehicle discharge at the saturation flow rate throughout the green period. This study introduces a new parameter, lane inefficiency, evaluating vehicle discharge effectiveness by comparing saturation flow rate with instantaneous discharge for each green period. It provides a comprehensive assessment of green utilization for specific lanes. This study also explores the impact of signal control system parameters and traffic flow characteristics on lane inefficiency using principal component analysis (PCA) and multiple linear regression models. This approach holistically evaluates how both signal control system and traffic flow parameters collectively influence efficient green period utilization. The findings emphasize the impact of critical factors on lane inefficiency, including green time, the proportion of total unused green time to green time, total unused green time, the percentage of heavy vehicles in departing traffic, the ratio of effective green time to cycle time, the total time headways of the first four vehicles, and queue length. Decision makers need to pay due attention to these parameters to enhance intersection performance and foster a more sustainable urban transportation network. Full article

The aim of our research was to compare the levels of pollution in different habitats based on the concentrations of heavy metals found in pollen and the organisms of Osmia bicornis L. bees in three habitats: orchards, berry plantations, and urban habitats (near by power plant, landfill, residential areas, and heavy vehicle traffic). The concentration of Ag, Cd, Cu, Fe, Mn, Ni, Pb and Zn were determined. Samples were quantified using flame atomic absorption spectrophotometry (AAS), with evaluations being carried out three times for each sample. Bee nests were also analyzed concerning reproduction and the presence of parasites. There were no significant differences in the content of heavy metals Ag, Cd, Cu, Fe, Mn, Ni, Pb and Zn in pollen samples between the three habitat types. Bee samples differed only in their Zn content, which was significantly higher in orchards (2.67 mg/kg) than urban habitats (0.80 mg/kg) and berry plantation (0.94 mg/kg). Habitat type had no effect on most bee reproductive parameters (percentage of occupied nest tubes, population growth). Our results show that bees pollinating crops in, for example orchards or berry plantations are exposed to heavy metals to a similar extent to those urban areas. Full article

Signalized intersections are one of the typical bottlenecks in urban transport systems that have reduced speeds and which have substantial vehicle emissions. This study aims to analyze and optimize the impacts of signal control on the emissions of mixed traffic flow (CO, HC, and NO_x) containing both heavy- and light-duty vehicles at urban intersections, leveraging high-resolution field emission data. An OBEAS-3000 (Manufacturer: Xiamen Tongchuang Inspection Technology Co., Ltd., Xiamen, China.) vehicle emission testing device was used to collect microscopic operating characteristics and instantaneous emission data of different vehicle types (light- and heavy-duty vehicles) under different operating conditions. Based on the collected data, the VSP (Vehicle Specific Power) model combined with the VISSIM traffic simulation platform was used to quantitatively analyze the impact of signal control on traffic emissions. Heavy-duty vehicles contribute to most of the emissions regardless of the low proportion in the traffic flows. Afterward, a model is proposed for determining the optimal signal control at an intersection for a specific percentage of heavy-duty vehicles based on the conversion of emission factors of different types of vehicles. Signal control is also optimized based on conventional signal timing, and vehicle emissions are calculated. In the empirical analysis, the changes in CO, HC, and NO_x emissions of light- and heavy-duty vehicles before and after conventional signal control optimization are quantified and compared. After the signal control optimization, the CO, HC, and NO_x emissions of heavy-duty vehicles were reduced. The CO and HC emissions of light-duty vehicles were reduced, but the NO_x emissions of light-duty vehicles remained unchanged. The emissions of vehicles after optimized signal control based on vehicle conversion factors are reduced more significantly than those after conventional optimized signal control. This study provides a scientific basis for developing traffic management measures for energy saving and emission reduction in transport systems with mixed traffic. Full article

Following consecutive years of governance efforts, there has been a substantial reduction in sediment transport in the Yellow River, resulting in significant changes in its water–sediment dynamics. This necessitates precise monitoring of sediment-bearing tributary inflows, a crucial requirement for effective governance strategies on the Loess Plateau’s current developmental stage. While satellite remote sensing technology has been widely used to estimate suspended particulate matter concentration (C_SPM) in open water bodies like oceans and lakes, its application in narrow rivers presents challenges related to hybrid pixel and proximity effects. As a result, the effectiveness and competence of satellite remote sensing in monitoring C_SPM in such confined river environments are reduced. This study attempted to use unmanned aerial vehicle (UAV) remote sensing with multispectral technology to invert C_SPM in the Wuding River, a sediment-bearing Yellow River tributary. A novel C_SPM concentration inversion model was introduced for highly turbid river settings. The results showed that the accuracy of the new band ratio model in this study is significantly improved compared with the existing models. The validation dataset had a coefficient of determination (R²) of 0.83, a root mean square error (RMSE) of 3.73 g/L, and a mean absolute percentage error (MAPE) of 44.95% (MAPE is 40.68% at 1–20 g/L, and 12.37% at >20 g/L). On this basis, the UAV also monitored the impacts of heavy rainfall on the C_SPM, resulting in a rapid rise and fall in C_SPM over a period of ten hours. This study demonstrated the potential of UAV remote sensing for C_SPM monitoring in extremely turbid narrow rivers (tens to tens of meters), especially before and after rainfall sediment production events, which can provide technical support for accurate sediment management and source identification in the main tributaries of the Yellow River and help realize the goal of high-quality development of the Yellow River Basin. Full article

Road intersections are shared among several conflicted traffic flows. Stop signs are used to control competing traffic flows at road intersections safely. Then, driving rules are constructed to control the competing traffic flows at these stop sign road intersections. Vehicles must apply a complete stop with no motion in front of stop signs. First to arrive, first to go, straight before turns, and right then left are the main driving rules at stop sign intersections. Drivers must be aware of the stop sign’s existence, the architecture of the road intersection, and traffic distribution in the competing traffic flows. This is to make the best decision to pass the intersection or wait for other conflicted flows to pass according to the current situation. Due to bad weather conditions, obstacles, or existing heavy vehicles, drivers may miss capturing the stop sign. Moreover, the architecture of the road intersection and the characteristics of the competing traffic flows are not always clear to the drivers. In this work, we aim to keep the driver aware ahead of time of the existing stop signs, the architecture of the road intersection, and the traffic characteristics of the competing traffic flow at the targeted destination. Moreover, the best speed and driving behaviors are recommended to each driver. This is based on his/her position and the distribution of the existing traffic there. A driving assistance protocol is presented in this paper based on vehicular network technology. Real-time traffic characteristics are gathered and analyzed of vehicles around the intersections. Then, the best action for each vehicle is recommended accordingly. The experimental results show that the proposed driving assistant protocol successfully enhances the safety conditions around road intersections controlled by stop signs. This is by reducing the percentage of accident occurrences. Fortunately, the traffic efficiency of these road intersections is also enhanced; the accident percentage is decreased by 25% upon using the proposed protocol. Full article

In order to reveal the pollution characteristics and sources of PM_2.5, in this study, we collected PM_2.5 filter membrane samples in Shihezi continuously from December 2020 to January 2021, and analyzed 10 kinds of water-soluble inorganic ions (WSIIs) and 24 inorganic elements (IEs), as well as organic carbon (OC) and elemental carbon (EC). The sources and transport paths of PM_2.5 were also analyzed via PMF modeling and backward trajectory clustering analysis. The results show that, in winter, Shihezi can have a mean PM_2.5 mass concentration as high as 164.69 ± 76.48 μg/m³, and the PM_2.5 mass concentration on polluted days is 3.3 times that of clean days. Water-soluble inorganic ions (WSIIs), total carbon (TC), and inorganic elements (IEs) make up the percentage of PM_2.5 mass concentration by 64.9%, 9.3%, and 2.6%, respectively. SO₄²⁻, NO₃⁻, and NH₄⁺ (SIAs) are the major WSIIs, accounting for 91.0% of the WSII concentration. The heavier the pollution, the more SIAs contribute to PM_2.5. The OC mean mass concentration is 14.04 ± 5.32 μg/m³. As the winter pollution becomes worse and worse, the value of OC/PM_2.5 decreases constantly while that of SOC/OC follows an opposite trend. During the process of heavy pollution in Shihezi, the secondary transformation of total carbon cannot be ignored. The positive definite matrix factorization (PMF) model result suggests that the main pollution origins of PM_2.5 in Shihezi City comprise secondary sources, coal-burning sources, motor vehicle sources, industrial sources, and flying dust sources. The backward trajectory clustering analysis denotes that the winter pollution in Shihezi mainly comes from the local pollutants in Manas and the short-distance transport of pollutants from the Urumqi-Changji Region. Full article

Vehicle mass is crucial to autonomous vehicles control. Affected by the nonlinearity of vehicle dynamics between vehicle states, it is still a tough issue to estimate vehicle mass precisely and stably. The transformer aided adaptive extended Kalman filter is proposed to further improve the accuracy and stability of estimation. Firstly, the transformer-based estimator is introduced to provide an accurate pre-estimation of vehicle mass, with the nonlinear dynamics among vehicle states being learned. Secondly, on the basis of comparing the real-time input and training data of neural network, the weight adjustment module is designed to present an adaptive law. Finally, the adaptive extended Kalman filter is proposed to meet the demand of accuracy and stability, where the pre-estimation of transformer-based estimator is integrated with the adaptive law. Dataset is collected by conducting heavy-duty vehicle simulation. The mean absolute percentage error, mean absolute error, root mean square error and convergence rate averaged over simulation tests are 0.90%, 256.47 kg, 357.01 kg and 184 steps, respectively. The results show the outperformance of the proposed method in terms of accuracy and stability. Full article