Search Results (34)

The robotic exploration of space began only five decades ago, and yet in the intervening years, a wide and diverse ecosystem of robotic explorers has been developed for this purpose. Such devices have greatly benefited from miniaturization trends and the increased availability of high-quality commercial off-the-shelf (COTS) components. This review outlines the specific taxonomic distinction between planetary surface rovers and other robotic space exploration vehicles, such as orbiters and landers. Additionally, arguments are made to standardize the classification of planetary rovers by mass into categories similar to those used for orbital satellites. Discussions about recent noteworthy trends toward the miniaturization of planetary rovers are also included, as well as a compilation of previous planetary rovers. This analysis compiles relevant metrics such as the mass, the distance traveled, and the locomotion or actuation technique for previous planetary rovers. Additional details are also examined about archetypal rovers that were chosen as representatives of specific small-scale rover classes. Finally, potential future trends for miniature planetary surface rovers are examined by way of comparison to similar miniaturized orbital robotic explorers known as CubeSats. Based on the existing relationship between CubeSats and their Earth-based simulation equivalents, CanSats, the importance of a potential Earth-based analog for miniature rovers is identified. This research establishes such a device, coining the new term ‘CanBot’ to refer to pathfinding systems that are deployed terrestrially to help develop future planetary surface exploration robots. Establishing this explicit genre of robotic vehicle is intended to provide a unified means for categorizing and encouraging the development of future small-scale rovers. Full article

The article presents a new method of passive dynamic weighing of vehicles based on the registration of seismic signals that occur when wheels pass through strips specially applied to the road surface. Signal processing is carried out using spectral methods, including fast Fourier transform, consistent filtering, and regularization methods for solving inverse problems. Special attention is paid to the use of linear-frequency-modulated signals, which make it possible to distinguish the responses of individual axes even when superimposed. Field tests were carried out on a real section of the road, during which signals from vehicles of various classes were recorded using eight geophones. The average error in determining the speed of 1.2 km/h and the weight of 8.7% was experimentally achieved, while the correct determination of the number of axles was 96.5%. The results confirm the high accuracy and sustainability of the proposed approach with minimal implementation costs. It is shown that this system can be scaled up for use in intelligent transport systems and applied in real traffic conditions without the need to intervene in the design of the roadway. Full article

The risk of serious crashes is notably higher among young and novice drivers. This increased risk is due to several factors, including a lack of recognition of dangerous situations, an overestimation of driving skills, and vulnerability to peer pressure. Recently, advanced driver assistance systems (ADAS) have been integrated into vehicles to help mitigate crashes linked to these factors. While numerous studies have examined ADAS broadly, few have specifically investigated its effects on young and novice drivers. This study aimed to address that gap by exploring ADAS’s impact on these drivers. Most studies in this review conclude that ADAS is beneficial for young and novice drivers, though some research suggests its impact may be limited or even negligible. Tailoring ADAS to address the unique needs of young drivers could enhance both the system’s acceptance and reliability. The review also found that unimodal warnings (e.g., auditory or visual) are as effective as multimodal warnings. Of the different types of warnings, auditory and visual signals proved the most effective. Additionally, ADAS can influence young drivers’ car-following behavior; for instance, drivers may maintain greater safety buffers or drive closely to avoid alarm triggers, likely due to perceived system unreliability. Aggressive drivers tend to benefit most from active ADAS, which actively intervenes to assist the driver. Future research could explore the combined effects of multiple ADAS functions within a single vehicle on young and novice drivers to better understand how these systems interact and impact driver behavior. Full article

Accidents involving cyclists and trucks are among the most severe road accidents. In 2021, 199 cyclists were killed in accidents involving a truck in the EU. The main accident situation is a truck turning right and a cyclist going straight ahead. A large proportion of these accidents are caused by the inadequate visibility in an HGV (Heavy Goods Vehicle). The blind spot, in particular, is a significant contributor to these accidents. A BSD (Blind Spot Detection) system is expected to significantly reduce these accidents. There are only a few studies that estimate the potential of assistance systems, and these studies include a combined assessment of cyclists and pedestrians. In the present study, accident simulations are used to assess a warning and an autonomously intervening assistance system that could prevent truck to cyclist accidents. The main challenges are local sight obstructions such as fences, hedges, etc., rule violations by cyclists, and the complexity of correctly predicting the cyclist’s intentions, i.e., detecting the trajectory. Taking these accident circumstances into consideration, a BSD system could prevent between 26.3% and 65.8% of accidents involving HGVs and cyclists. Full article

Lithium-ion batteries currently represent the most suitable technology for energy storage in various applications, such as hybrid and electric vehicles (HEVs and BEVs), portable electronics and energy storage systems. Their wide adoption in recent years is due to their characteristics of high energy density, high power density and long life cycle. On the other hand, they still face challenges from a safety point of view for the possible faults that could generate several problems, ranging from simple malfunctioning to a dangerous thermal runaway. Overcharge is one of the most critical types of faults, and, depending on the level of abuse, it may trigger a thermal runaway. To prevent high levels of overcharge abuse, some cells include integrated protection devices that cut off the circuit when a critical condition is met. In this paper, the performance of these protection devices is evaluated to assess their effectiveness. The cells were tested at different ambient temperatures and current levels. In the worst-case scenarios, the maximum cell temperature slightly exceeded 70 °C and the State of Charge (SOC) reached a peak of 127% when the Current Interruption Device (CID) was activated. These conditions were not critical, so serious events such as thermal runaway were not triggered. These outcomes confirm the effectiveness of the CID, which always intervenes in maintaining a safe state. However, since it never intervened in the overcharge abuse tests, a specific set up was also used to investigate the operation of the other protection device, the Positive Temperature Coefficient. Full article

When a ground vehicle runs at high speeds, even a slight excess in the wheel steering angle can immediately cause the vehicle to slide sideways and lose control. In this study, we propose an active safety control system designed to address emergency situations where the driver applies excessive steering input and the vehicle speed varies significantly during control. The system combines the direct yaw moment (DYM) method with a steering saturation scheme that prevents excessive driver steering input from adversely influencing the front-wheel steering. Consequently, the control system allows the DYM to focus more on other stabilization tasks and maintain tire/road friction within its workable linear range. The implementation relies on a reference steering angle and a reference vehicle state, derived from a linear vehicle model considering tire/road friction limitations. When the driver’s steering angle and the system state deviate from these reference values, the control system intervenes by applying both the steering saturation scheme and DYM method. This ensures the front-wheel steering angle and system state remain close to the reference values. The control strategy is developed using the polytopic Linear Parameter Varying (LPV) technique and Linear Matrix Inequality (LMI) to account for the changes in vehicle speed. It is further enhanced with an input saturation technique based on a high-gain approach, which improves control utilization and system response during emergency situations. The advantages of the proposed control strategy are demonstrated through simulation results. Full article

Highly automated shuttle vehicles (SAE Level 4) have the potential to enhance public transport services by decreasing the demand for drivers, enabling more frequent and flexible ride options. However, at least in a transitionary phase, safety operators that supervise and support the shuttles with their driving tasks may be required on board the vehicle from a technical or legal point of view. A crucial component for executing supervisory and intervening tasks is the human–machine interface between an automated vehicle and its on-board operator. This research presents in-depth case studies from three heterogenous living laboratories in Germany that deployed highly automated shuttle vehicles with on-board operators on public roads. The living labs differed significantly regarding the on-board operators’ tasks and the design of the human–machine interfaces. Originally considered a provisional solution until the vehicle automation is fully capable of running without human support, these interfaces were, in general, not designed in a user-centered way. However, since technological progress has been slower than expected, on-board operator interfaces are likely to persist in the mid-term at least. Hence, this research aims to assess the aptitude of interfaces that are in practical use for the on-board operators’ tasks, in order to determine the user-centered design of future interfaces. Completing questionnaires and undergoing comprehensive, semi-structured interviews, nine on-board operators evaluated their human–machine interfaces in light of the respective tasks they complete regarding user variables such as work context, acceptance, system transparency, and trust. The results were highly diverse across laboratories and underlined that the concrete system setup, encompassing task and interface design, has a considerable impact on these variables. Ergonomics, physical demand, and system transparency were identified as the most significant deficits. These findings and derived recommendations may inform the design of on-board operator workspaces, and bear implications for remote operation workstations as well. Full article

The article outlines various approaches to developing a fuzzy decision algorithm designed for monitoring and issuing warnings about driver drowsiness. This algorithm is based on analyzing EOG (electrooculography) signals and eye state images with the aim of preventing accidents. The drowsiness warning system comprises key components that learn about, analyze and make decisions regarding the driver’s alertness status. The outcomes of this analysis can then trigger warnings if the driver is identified as being in a drowsy state. Driver drowsiness is characterized by a gradual decline in attention to the road and traffic, diminishing driving skills and an increase in reaction time, all contributing to a higher risk of accidents. In cases where the driver does not respond to the warnings, the ADAS (advanced driver assistance systems) system should intervene, assuming control of the vehicle’s commands. Full article

In order to eliminate the potential safety hazard that arises when metal foreign objects intervene in the wireless charging area of electric vehicles, this paper proposes that a metal foreign object detection method be applied to the wireless charging system of electric vehicles based on the optimal design of the array detection coil. Firstly, the equivalent circuit model of the metal foreign object detection system is established, then the principle of the foreign object detection system is analyzed, and the scale factor β is introduced as the optimization index of the detection coil. Secondly, the change of the scale factor β with the circuit parameters is analyzed and the appropriate circuit parameters are compared and selected. Thirdly, on the basis of the planar square spiral coil, Ansys Maxwell finite element simulation software is used to optimize its structural parameters, combination mode, and resonant circuit, as well as design the anti-series and anti-parallel enhanced detection coil sets with the decoupling and elimination of detection blind spots. Finally, the feasibility of the proposed detection method of metal foreign objects is verified by experiments. The results show that the two array detection coil sets can detect small-sized common metal foreign objects such as paper clips and the proposed double-layer reinforced structure can significantly improve the detection sensitivity of the system. Full article

The food production system is vulnerable to diseases more than ever, and the threat is increasing in an era of climate change that creates more favorable conditions for emerging diseases. Fortunately, scientists and engineers are making great strides to introduce farming innovations to tackle the challenge. Unmanned aerial vehicle (UAV) remote sensing is among the innovations and thus is widely applied for crop health monitoring and phenotyping. This study demonstrated the versatility of aerial remote sensing in diagnosing yellow rust infection in spring wheats in a timely manner and determining an intervenable period to prevent yield loss. A small UAV equipped with an aerial multispectral sensor periodically flew over, and collected remotely sensed images of, an experimental field in Chacabuco (−34.64; −60.46), Argentina during the 2021 growing season. Post-collection images at the plot level were engaged in a thorough feature-engineering process by handcrafting disease-centric vegetation indices (VIs) from the spectral dimension, and grey-level co-occurrence matrix (GLCM) texture features from the spatial dimension. A machine learning pipeline entailing a support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) was constructed to identify locations of healthy, mild infection, and severe infection plots in the field. A custom 3-dimensional convolutional neural network (3D-CNN) relying on the feature learning mechanism was an alternative prediction method. The study found red-edge (690–740 nm) and near infrared (NIR) (740–1000 nm) as vital spectral bands for distinguishing healthy and severely infected wheats. The carotenoid reflectance index 2 (CRI2), soil-adjusted vegetation index 2 (SAVI2), and GLCM contrast texture at an optimal distance d = 5 and angular direction θ = 135° were the most correlated features. The 3D-CNN-based wheat disease monitoring performed at 60% detection accuracy as early as 40 days after sowing (DAS), when crops were tillering, increasing to 71% and 77% at the later booting and flowering stages (100–120 DAS), and reaching a peak accuracy of 79% for the spectral-spatio-temporal fused data model. The success of early disease diagnosis from low-cost multispectral UAVs not only shed new light on crop breeding and pathology but also aided crop growers by informing them of a prevention period that could potentially preserve 3–7% of the yield at the confidence level of 95%. Full article

Electric transportation will assist in lowering emissions of greenhouse gases and mitigating the impact of rising petrol prices. To promote the widespread adoption of electric transportation, a diverse range of charging stations must be established in an atmosphere that is friendly to users. Wireless electric vehicle charging systems are a viable alternative technology that can charge electric vehicles (EVs) without any plug-in issues. Wireless power transfer (WPT), which involves the transmission of electricity via an electromagnetic field despite the presence of an intervening area, holds out the possibility of new prospects for EVs to increase environmentally responsible mobility. This review article examines the WPT technology and how it might be applied to electric vehicles from both a technical and safety standpoint. The prime aim of this review is (1) to illustrate the current state of the art in terms of technological advances as well as research limitations in the field of WPT development and use within the field of transportation; (2) to organise the experimental the deployment of WPT EV systems in the actual world; and (3) to analyse the results over a sustainable period and to identify limitations as well as chances for growth. From a technical point of view, the progress that has been made on the selection of material for designing coils, different types of coils with a specific focus on the overall performance of the system. As a result, this study aims to provide an extensive overview focusing on the magnetic materials and the architectures of the transmitter and receiver pads. Full article

With higher levels of automation in vehicles, the need for robust driver monitoring systems increases, since it must be ensured that the driver can intervene at any moment. Drowsiness, stress and alcohol are still the main sources of driver distraction. However, physiological problems such as heart attacks and strokes also exhibit a significant risk for driver safety, especially with respect to the ageing population. In this paper, a portable cushion with four sensor units with multiple measurement modalities is presented. Capacitive electrocardiography, reflective photophlethysmography, magnetic induction measurement and seismocardiography are performed with the embedded sensors. The device can monitor the heart and respiratory rates of a vehicle driver. The promising results of the first proof-of-concept study with twenty participants in a driving simulator not only demonstrate the accuracy of the heart (above 70% of medical-grade heart rate estimations according to IEC 60601-2-27) and respiratory rate measurements (around 30% with errors below 2 BPM), but also that the cushion might be useful to monitor morphological changes in the capacitive electrocardiogram in some cases. The measurements can potentially be used to detect drowsiness and stress and thus the fitness of the driver, since heart rate variability and breathing rate variability can be captured. They are also useful for the early prediction of cardiovascular diseases, one of the main reasons for premature death. The data are publicly available in the UnoVis dataset. Full article

The delivery of electricity employing an electromagnetic field that extends across an intervening region is called a wireless power transfer (WPT). This approach paves the way for electric vehicles (EVs) to use newly available options to reduce their environmental impact. This article is a review that examines the WPT technology for use in electric vehicle applications from both the technical aspect and the environmental impact. This review will attempt to accomplish the following objectives: (1) describe the present state of the technology behind the development and application of a WPT across the transportation industry; (2) substantiate the actual implementation of WPT EV systems; and (3) estimate the functioning of the autonomous system, as well as detect the potential stumbling blocks and openings for enhancement. The most recent advancements and implementation in compensating topologies, power electronics converters, and control techniques are dissected and debated scientifically to improve the system’s performance. To evaluate the performance from a sustainable perspective, energy, environmental, and economic factors are utilized, and at the same time, policy drivers and health and safety problems are researched. Full article

Minimal risk maneuvers (MRMs), as part of highly automated systems, aim at minimizing the risk during a transition phase from automated to manual driving. Previous studies show that many drivers have an urge to intervene in transition phases despite the system’s capability to safely come to a standstill. A human–machine interface (HMI) concept was developed to support driver decisions by providing environmental information and action recommendations. This was investigated in a static driving simulator experiment with 36 participants. Two scenarios that differed in the traffic on the adjacent left lane were implemented and the HMI concept displayed the content accordingly. Results of the study again show a high intervention rate of drivers overtaking the obstacle from the left, even if the lane is occupied by other vehicles. The HMI concept had a positive influence on the manner of intervention by encouraging a standstill in the shoulder lane. Nevertheless, negative consequences included accidents and dangerous situations, but at lower frequencies and proportions during drives with the HMI concept. In conclusion, the risk during the transition phase was reduced. Furthermore, the results showed a significant decrease in the subjective workload and a positive influence on the drivers’ understanding and predictability of the automated system. Full article

Remote sensing can offer stakeholders opportunities to make precise and accurate decisions on agricultural activities. For instance, farmers can exploit aircraft systems to acquire survey-level, high-resolution imagery data for crop and soil management. Therefore, the objective of this study was to analyze whether an unmanned aerial vehicle (UAV) allows for the assessment and monitoring of biofertilization of the common bean upon vegetation indices (VIs). The biological treatment of the legume crop included its inoculation with phosphate-solubilizing bacteria (PSB), namely Bacillus subtilis and B. megaterium. Indicators of photosynthetic performance, such as chlorophylls (a and b) and carotenoids, were measured from actively growing leaves to determine effectiveness. In addition, images were acquired in the field, both spatially and temporally, to establish functional relationships between biometric and computational features. Microorganisms manifested as growth-promoting agents to the crop as they significantly increased its quantities of light-harvesting pigments. VIs allowed for predicting their impact on photosynthetic performance, making them on-site markers of PSB. Therefore, this research can provide insights into the remote, non-destructive mapping of spectral changes in the common bean upon the application of PSB. Imagery data from UAV would enable producers to generate information on the crop to intervene in the field at the right time and place for improved utilization of biofertilizers. Full article