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In the field of intelligent transportation, the planning of traffic flows that meet energy-efficient driving requirements necessitates the acquisition of energy consumption data for each vehicle within the traffic flow. The current methods for calculating vehicle energy consumption generally rely on longitudinal dynamics models, which require comprehensive knowledge of all vehicle power system parameters. While this approach is feasible for individual vehicle models, it becomes impractical for a large number of vehicle types. This paper proposes a digital model for vehicle driving energy consumption using vehicle speed, acceleration, and battery state of charge (SOC) as inputs and energy consumption as output. The model is trained using an optimized CNN-BiLSTM-Attention (OCBA) network architecture. In comparison to other methods, the OCBA-trained model for predicting PHEV driving energy consumption is more accurate in simulating the time-dependency between SOC and instantaneous fuel and power consumption, as well as the power distribution relationship within PHEVs. This provides an excellent framework for the digital modeling of complex power systems with multiple power sources. The model requires only 54 vehicle tests for training, which is significantly fewer than over 2000 tests typically needed to obtain parameters for power system components. The model's prediction error for fuel consumption under unknown conditions is reduced to 5%, outperforming the standard error benchmark of 10%. Furthermore, the model demonstrates high generalization capability with an R2 value of 0.97 for unknown conditions. [ABSTRACT FROM AUTHOR]

Digital microfluidics, which relies on the movement of drops, is relatively immune to clogging problems, making it suited for micro-reactor applications. Here, graphene oxide paper of 100 μm thickness, fabricated by blade coating sedimented dispersions onto roughened substrates, followed by drying and mechanical exfoliation, was found to be relatively free of cracks and curling. It also exhibited high wettability and elasto-capillary characteristics. Possessing low enough stiffness, it could rapidly and totally self-wrap water drops of 20 μL volume placed 2 mm from its edge when oriented between 0 and 60° to the horizontal. This complete wrapping behavior allowed drops to be translated via movement of the paper over long distances without dislodgement notwithstanding accelerations and decelerations. An amount of 2 drops that were wrapped with separate papers, when collided with each other at speeds up to 0.64 m/s, were found to eschew coalescence. This portends the development of robust digital microfluidic approaches for micro-reactors. [ABSTRACT FROM AUTHOR]

The paper presents the results of studies of the generation of methanol in the accelerated aging of paper insulation in transformer oil under the influence of an elevated temperature. All investigated materials (cable paper, transformer oil) are of Russian origin. A description is given for the used models of paper insulation samples, specially designed test cells and a circulating bath. The results of a comparison of studies conducted by authors and other researchers from countries are analyzed. [ABSTRACT FROM AUTHOR]

The article describes an experiment involving a solid ball resting in a smooth sheet of paper. Topics discussed include the behavior of the ball being independent on the acceleration of the paper as well several different paper removal speeds being investigated experimentally. Also mentioned are calculations involving ball rolling without slipping and ball rolling with slipping.

Liquid spreading on solid surfaces and penetration into porous matrices (powders and coated papers) are investigated. The influence of chemical and structural heterogeneity on equilibrium and dynamic surface wetting is evaluated both experimentally and theoretically. Single capillary systems are used to identify the predominating mechanisms for acceleration, momentum, inertial and viscous liquid penetration. Different stages of vertical and horizontal penetration of liquids from non-limited, restricted (sessile drop) and cut-off sources into powders and papers are evaluated with reference to a range of frequently used models. For all types of liquid transport power-law exponents are used to relate all observations. The applicability of models from which the exponents are derived is discussed. Results are compared to theoretical predictions for liquid penetration. Models are of general validity, but the focus is placed on probe liquid spreading on and penetrating into coated and uncoated papers. This sets a particular challenge, since papers are heterogeneous layered composites of powder compacts on fibrous network. For the evaluation of models published results are supported by extended original results. [ABSTRACT FROM AUTHOR]

Aiming at the demand for subjective evaluation of driveability for fuel cell vehicles, the modeling and evaluation method of driveability for fuel cell vehicles were studied in this paper. Firstly, a real-time model of the fuel cell vehicle powertrain system was established, which included the fuel cell model, power battery model, DC/DC converter model and drive motor model. Secondly, it was integrated with the vehicle dynamics model to form a virtual prototype of a fuel cell vehicle. And a virtual subjective evaluation platform for fuel cell vehicles was built by combining the virtual prototype and high-fidelity driving simulator. Thirdly, a subjective evaluation method of driveability for fuel cell vehicles was proposed, which included the starting performance, acceleration performance, uniform speed performance and tip-in/tip-out performance. Finally, the paper used the platform and method mentioned above to conduct subjective evaluations of the fuel cell vehicles. [ABSTRACT FROM AUTHOR]

Track smoothness has become an important factor in the safe operation of high-speed trains. In order to ensure the safety of high-speed operations, studies on track smoothness detection methods are constantly improving. This paper presents a track irregularity identification method based on CNN-Bi-LSTM and predicts track irregularity through car body acceleration detection, which is easy to collect and can be obtained by passenger trains, so the model proposed in this paper provides an idea for the development of track irregularity identification method based on conventional vehicles. The first step is construction of the data set required for model training. The model input is the car body acceleration detection sequence, and the output is the irregularity sequence of the same length. The fluctuation trend of the irregularity data is extracted by the HP filtering (Hodrick Prescott Filter) algorithm as the prediction target. The second is a prediction model based on the CNN-Bi-LSTM network, extracting features from the car body acceleration data and realizing the point-by-point prediction of irregularities. Meanwhile, this paper proposes an exponential weighted mean square error with priority inner fitting (EIF-MSE) as the loss function, improving the accuracy of big value data prediction, and reducing the risk of false alarms. In conclusion, the model is verified based on the simulation data and the real data measured by the high-speed railway comprehensive inspection train. [ABSTRACT FROM AUTHOR]

The paper is devoted to comparison of experimental data with theoretical predictions concerning the dependence of the current of accelerated ions on the operating voltage of a Hall thruster with an anode layer. The error made in the paper published by the authors in Plasma Phys. Rep. 40, 229 (2014) occurred because of a misprint in the Encyclopedia of Low-Temperature Plasma. In the present paper, this error is corrected. It is shown that the simple model proposed in the above-mentioned paper is in qualitative and quantitative agreement with experimental results. [ABSTRACT FROM AUTHOR]

Connected Autonomous Vehicle (CAV) dedicated lanes can spatially eliminate the disturbance from Human-Driven Vehicles (HDVs) and increase the probability of vehicle cooperative platooning, thereby enhancing road capacity. However, when the penetration rate of CAVs is low, CAV dedicated lanes may lead to a waste of road resources. This paper proposes a cooperative lane-changing control method for multiple vehicles considering Dynamic Intelligent Connected (DIC) dedicated lanes. Initially, inspired by the study of dedicated bus lanes, the paper elucidates the traffic regulations for DIC dedicated lanes, and two decision-making approaches are presented based on the type of lane-change vehicle and the target lane: CAV autonomous cooperative lane change and HDV mandatory cooperative lane change. Subsequently, considering constraints such as acceleration, speed, and safe headway, cooperative lane-change control models are proposed with the goal of minimizing the weighted sum of vehicle acceleration and lane-change duration. The proposed model is solved by the TOPSIS multi-objective optimization algorithm. Finally, the effectiveness and advancement of the proposed cooperative lane-changing method are validated through simulation using the SUMO software (Version 1.19.0). Simulation results demonstrate that compared to traditional lane-changing models, the autonomous cooperative lane-changing model for CAVs significantly improves the success rate of lane changing, reduces lane-changing time, and causes less speed disturbance to surrounding vehicles. The mandatory cooperative lane-changing model for HDVs results in shorter travel times and higher lane-changing success rates, especially under high traffic demand. The methods presented in this paper can notably enhance the lane-changing success rate and traffic efficiency while ensuring lane-changing safety. [ABSTRACT FROM AUTHOR]

The algorithms for determining the active space object maneuver parameters in the conditions of near-circular orbits are presented in the paper. The right ascension and declination angles are used to determine the parameters of a single maneuver with transversal and lateral components (the application moment and the velocity impulse magnitude). Two pairs of angles are used to determine the parameters of the maneuver with only a lateral component. Two pairs of angles are needed for the determination of the parameters of the long-duration maneuver performed by a low-thrust engine (moments of the maneuver start and finish, and components of the acceleration delivered by the engine). The essential detail that makes it possible to determine the parameters of long-duration maneuvers is their symmetry relative to the center of the engine operating interval. Considerable perturbing accelerations, which are not accounted for by traditional perturbing models, affect passive objects, especially membranous objects with a big and variable area-to-mass ratio. This decreases dramatically the accuracy of these objects' motion propagation. In this paper, the magnitude of perturbing acceleration is determined with the assumption that it is constant and is active throughout the whole time interval from the moment of the last orbit determination to the moment of the new measurement used. Examples of the assessment of maneuvers performed by an object in the geostationary orbit are presented. [ABSTRACT FROM AUTHOR]

In this paper, an automatic obstacle avoidance trajectory planning strategy is proposed for the simultaneous motion of multi-robots, which perform anthropomorphic skill operations in a large curved preformed three-dimensional (3D) weaving environment with multiple obstacles and limited space, to eliminate tedious manual calibration work of robot path in engineering. Firstly, an Adaptive Goal-guided Rapidly-exploring Random Trees (AGG-RRT) algorithm is proposed, combined with the robot obstacle avoidance strategy, to search the discrete position of the collision-free path of the end-effector gradually from the starting point to the ending point. Then the optimization of the path is completed by bidirectional pruning of redundant nodes and cubic non-uniform rational B-spline (NURBS) curve fitting. And finally, the robot trajectory is interpolated based on S-shaped acceleration/deceleration planning to ensure smooth robot joint motion. The simulation results demonstrate the superiority of the AGG-RRT algorithm over the basic RRT algorithm and related improved algorithms in terms of search time and success rate. The simulated experiments also achieve the smooth trajectory planning of multiple robotic arms with the synchronous obstacle avoidance motion, which shows that the AGG-RRT algorithm is successfully applied and the collision-free trajectory planning strategy is effective. [ABSTRACT FROM AUTHOR]

When the temporary backfilled subgrade is not sufficiently compacted, the result is low stiffness of the track system. Excessive deformation of railway tracks under the action of freight trains will aggravate track wear and reduce service life. However, traditional reinforcement technology to increase the stiffness of the track system is sometimes limited due to requirements of working space, efficiency, and little disturbance of the normal operation of the existing railway. Battered grouted helical piles (BGHP) are a kind of strengthening technology that has little influence on the existing railway and high construction efficiency. This paper presents a field case study of the implementation of BGHP to reinforce the freight railway subgrade. The paper evaluates the effect of the BGHP on the dynamic response of the treated subgrade. The subgrade soil was initially characterized by cone penetration tests at one location before BGHP reinforcement. The subgrade dynamic deformation modulus was measured before and after BGHP installation. In addition, the acceleration and velocity time histories of the subgrade were monitored during the passage of a freight train before and after BGHP reinforcement. The field measurement showed that the vibration acceleration, velocity, and displacement of the subgrade all decreased while the dynamic deformation modulus of the subgrade increased after BGHP reinforcement. Further, the vibration level reduced remarkably, mainly in the frequency band of 44.7 to 56.2 Hz, and the distribution of the normalized accumulated energy of velocity and acceleration was significantly influenced after BGHP reinforcement. The findings from this case study are of practical value to the emerging application of the freight railway subgrade reinforced by BGHP. [ABSTRACT FROM AUTHOR]

Featured Application: This paper proposes a method to determine the dynamic response of a planar mechanism with a practical application to a flap and wing control mechanism of a light sport aircraft. For this, a topological model and its related theory are used. This paper presents a more general method to study the dynamic behavior of a planar mechanism with joints. To do this, Graph Theory is used. A topological description is presented based on which a corresponding graph is attached to any mechanism. This method can be used for both kinematic and dynamic study in the same model, and many of the descriptors used in kinematic analysis can also be used for dynamic analysis. As a final result, the motion equations of the studied mechanical system can be obtained. An application is made to a flap and wing control system of a light sport aircraft. The graph associated with the mechanism first used to determine the field of velocities and accelerations of the mechanism elements is then used to obtain the motion equation for the control system. In this way, Graph Theory proves useful for the parallel study of both the kinematic and dynamic study of such problems. [ABSTRACT FROM AUTHOR]

This paper investigates a global fixed-time control strategy for a search and rescue unmanned surface vehicle (SRUSV) targeting water rescue missions. Firstly, an improved time allocation trajectory generation (ITATG) method is proposed to generate a smooth and continuous desired trajectory, incorporating position, velocity, and acceleration information. Secondly, a fixed-time sideslip angle observer-based adaptive line-of-sight (FTSOALOS) guidance law is designed. This law integrates time-varying look-ahead distances with a fixed-time sideslip angle observer (FTSO) to ensure rapid convergence of positional errors within a fixed timeframe. Additionally, this paper employs a first-order fixed-time disturbance observer (FOFTDO) to accurately estimate external disturbances. To alleviate network pressure and reduce actuator failure rates, a fixed-time event-triggered sliding mode control (FTETSMC) mechanism is developed, ensuring the convergence of tracking errors within a fixed timeframe. Finally, using Lyapunov theory, this paper proves that the entire control system designed possesses consistent global fixed-time stability. Comparative simulation experiments validate the effectiveness and superiority of the FTSOALOS guidance law and the FTETSMC controller. [ABSTRACT FROM AUTHOR]

Simple Summary: In the process of large-scale cage chicken breeding, using inspection robots instead of manual detection can solve the problems of large workload and low detection efficiency. However, poor driving stability of an inspection robot will lead to low inspection accuracy. In order to ensure high efficiency, accuracy, and stability of detection, this study takes the stability of visual navigation for inspection robots as the optimization goal, and designs an efficient and accurate road extraction algorithm and a navigation line fitting algorithm with better robustness. The experimental results show that the algorithm proposed in this study can improve the stability of detection, achieve a faster running speed, and achieve a better detection effect and a higher detection efficiency while keeping the detection effect unchanged. The navigation algorithm can accelerate the automation process of large-scale cage chicken breeding and promote the realization of fast and accurate monitoring. The speed and accuracy of navigation road extraction and driving stability affect the inspection accuracy of cage chicken coop inspection robots. In this paper, a new grayscale factor (4B-3R-2G) was proposed to achieve fast and accurate road extraction, and a navigation line fitting algorithm based on the road boundary features was proposed to improve the stability of the algorithm. The proposed grayscale factor achieved 92.918% segmentation accuracy, and the speed was six times faster than the deep learning model. The experimental results showed that at the speed of 0.348 m/s, the maximum deviation of the visual navigation was 4 cm, the average deviation was 1.561 cm, the maximum acceleration was 1.122 m/s2, and the average acceleration was 0.292 m/s2, with the detection number and accuracy increased by 21.125% and 1.228%, respectively. Compared with inertial navigation, visual navigation can significantly improve the navigation accuracy and stability of the inspection robot and lead to better inspection effects. The visual navigation system proposed in this paper has better driving stability, higher inspection efficiency, better inspection effect, and lower operating costs, which is of great significance to promote the automation process of large-scale cage chicken breeding and realize rapid and accurate monitoring. [ABSTRACT FROM AUTHOR]

In recent years, the Internet of Things (IoT) and the Internet of Vehicles (IoV) represent rapidly developing technologies. The majority of car manufacturing companies invest large amounts of money in the field of connected autonomous vehicles. Applications of connected and autonomous vehicles (CAVs) relate to smart transport services and offer benefits to both society and the environment. However, the development of autonomous vehicles may create vulnerabilities in security systems, through which attacks could harm both vehicles and their drivers. To this end, CAV development in vehicular ad hoc networks (VANETs) requires secure wireless communication. However, this kind of communication is vulnerable to a variety of cyber-attacks, such as spoofing. In essence, this paper presents an in-depth analysis of spoofing attack impacts under realistic road conditions, which may cause some traffic congestion. The novelty of this work has to do with simulation scenarios that take into consideration a set of cross-layer parameters, such as packet delivery ratio (PDR), acceleration, and speed. These parameters can determine the integrity of the exchanged wave short messages (WSMs) and are aggregated in a central trusted authority (CTA) for further analysis. Finally, a statistical metric, coefficient of variation (CoV), which measures the consequences of a cyber-attack in a future crash, is estimated, showing a significant increase (12.1%) in a spoofing attack scenario. [ABSTRACT FROM AUTHOR]

The present paper proposes the use of fractional derivatives in the definition of sliding function, giving a new mode control applied to induction motor drives in electric vehicle (EV) applications. The proposed Fractional-Order Sliding Mode Direct Torque Control-Space Vector Modulation (FOSM-DTC-SVM) strategy aims to address the limitations of conventional control techniques and mitigate torque and flux ripples in induction motor systems. The paper first introduces the motivation for using fractional-order control methods to handle the nonlinear and fractional characteristics inherent in induction motor systems. The core describes the proposed FOSM-DTC-SVM control strategy, which leverages a fractional sliding function and the associated Lyapunov stability analysis. The efficiency of the proposed strategy is validated via three scenarios. (i) The first scenario, where the acceleration of the desired speed is defined by pulses, leading to Dirac impulses in its second derivative, demonstrates the advantage of the proposed control approach in tracking the desired speed while minimizing flux ripples and generating pulses in the rotor pulsation. (ii) The second scenario demonstrates the effectiveness of filtering the desired speed to eliminate Dirac impulses, resulting in smoother rotor pulsation variations and a slightly slower speed response while maintaining similar flux ripples and stator current characteristics. (iii) The third scenario consists of eliminating the fractional derivatives of the pulses existing in the expression of the control, leading to the elimination of Dirac impulses. These results demonstrate the potential of the FOSM-DTC-SVM to revolutionize the performance and efficiency of EVs. By incorporating fractional control in the control scheme for PV-powered EVs, the paper showcases a promising avenue for sustainable transportation. [ABSTRACT FROM AUTHOR]

In relativity, the Newtonian concepts of velocity and acceleration are observer-dependent quantities that vary with the chosen frame of reference. It is well established that in the comoving frame, cosmic expansion is currently accelerating; however, in the rest frame, this expansion is actually decelerating. In this paper, we explore the implications of this distinction. The traditional measure of cosmic acceleration, denoted by q, is derived from the comoving frame and describes the acceleration of the scale factor a for a 3D space-like homogeneous sphere. We introduce a new parameter q E representing the acceleration experienced between observers within the light cone. By comparing q E to the traditional q using observational data from Type Ia supernovae (SN) and the radial clustering of galaxies and quasars (BAO)—including the latest results from DESI2024—our analysis demonstrates that q E aligns more closely with these data. The core argument of the paper is that Λ —regardless of its origin—creates an event horizon that divides the manifold into two causally disconnected regions analogous to conditions inside a black hole's interior, thereby allowing for a rest-frame perspective q E in which cosmic expansion appears to be decelerating and the horizon acts like a friction term. Such a horizon suggests that the universe cannot maintain homogeneity outside. The observed cosmological constant Λ can then be interpreted not as a driver of new dark energy or a modification of gravity but as a boundary term exerting an attractive force, akin to a rubber band, resisting further expansion and preventing event horizon crossings. This interpretation calls for a reconsideration of current cosmological models and the assumptions underlying them. [ABSTRACT FROM AUTHOR]

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This paper presents a design method of a suspension controller with an adaptive feedforward algorithm for ride comfort enhancement and motion sickness mitigation. Recently, it was shown that motion sickness is caused by combined heave and pitch motions of a sprung mass within the range of 0.8 and 8 Hz. For this reason, it is necessary to design a suspension controller for the purpose of reducing the heave and pitch vibration of a sprung mass within this range. To represent the heave acceleration and the pitch rate of a sprung mass, a 4-DOF half-car model is adopted as a vehicle model. For easy implementation in a real vehicle, a static output feedback control is adopted instead of a full-state one. To reduce the heave acceleration of a sprung mass for ride comfort enhancement, a linear quadratic SOF controller is designed. To reduce the pitch rate of a sprung mass for motion sickness mitigation, a filtered-X LMS algorithm is applied. To validate the method, simulation on vehicle simulation software is conducted. From the simulation results, it is shown that the proposed method is effective for ride comfort enhancement and motion sickness mitigation. [ABSTRACT FROM AUTHOR]

In a recent Comment, Chang et al. [Phys. Plasmas 29, 114703 (2022)] have studied the electron dynamics for an electron accelerating in a tightly focused Gaussian laser pulse with the higher order correction terms, and it is found that the initial position of the electron is the reason why the electron is pushed to the −z axis at the end. In this Reply, the electron dynamics and its nonlinear Thomson backscattering in a tightly focused Gaussian laser pulse with the higher order correction terms are presented, and it is found that the result is consistent with the lowest order approximation case in our paper [Hong et al., Phys. Plasmas 29, 043102 (2022)]. Meanwhile, it is also found that when the longitudinal deceleration effect of the ponderomotive force on the electron introduced by the falling part of the tightly focused laser pulse is greater than the longitudinal acceleration effect of the rising part, the electron that is initially stationary will be slightly pushed to the −z axis at the end, which can well explain the "return" phenomenon of the electron in the longitudinal direction both in our paper and in the Comment. [ABSTRACT FROM AUTHOR]

The paper presents an analysis of the dynamic parameters of a compact class passenger car powered by LPG/DME blends. The presented results are part of the research cycle of this vehicle, the purpose of which was to check the possibility of using DME (dimethyl ether) as an additive in the fuel mixture with LPG. In the presented part of the experimental research, the acceleration times of the vehicle under specific conditions were measured. On the basis of the obtained results, the relations between the average acceleration in the tested speed ranges, the fuel composition, and the degree of engine load were developed. The results of the analysis indicate that in the examined range of changes in the DME share in the fuel, comparable or higher acceleration values were obtained for all engine load levels. This confirms the usefulness of DME as a fuel component used to power SI engines. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to establish a dynamic model considering the actual operating conditions of the train and to study the dynamic performance and vibration characteristics of axle box bearings under different operating conditions. Design/methodology/approach: In this paper, based on the internal contact characteristics of double-row tapered roller bearings, a dynamic model considering the actual operating conditions of the train is established. The correctness of the model is verified by the vibration test of the bearing. Comparative analysis was conducted on the effects of axial force, radial force and rotational speed on the angular velocity of the cage, slip rate and vibration acceleration level of the inner ring. Findings: As the force increases, the slip rate of the cages on both sides decreases, and the vibration acceleration level of the inner ring increases. With the increase of rotational speed, the cage slip rate of the axle box bearing increases and the vibration acceleration level of the inner ring increases. Originality/value: A dynamic model is established considering the actual operating conditions, and the dynamic performance and vibration characteristics of the axle box bearing under different operating conditions are analyzed by numerical method. The research content can provide reference for the parameter design of high-speed railway bearings. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0085/ [ABSTRACT FROM AUTHOR]

This paper describes control methods to improve electric vehicle performance in terms of handling, stability and cornering by adjusting the weight distribution and implementing control systems (e.g., wheel slip control, and yaw rate control). The vehicle is first simulated using the bicycle model to capture the dynamics. Then, a study on the effect of weight distribution on the driving behavior is conducted. The study is performed for three different weight configurations. Moreover, a yaw rate controller and a wheel slip controller are designed and implemented to improve the vehicle's performance for cornering and longitudinal motion under the different loading conditions. The simulation through the bicycle model is compared to the experiments conducted on a rear-wheel driven radio-controlled (RC) electric vehicle. The paper shows how the wheel slip controller contributes to the stabilization of the vehicle, how the yaw rate controller reduces understeering, and how the location of the center of gravity (CoG) affects steering behavior. Lastly, an analysis of the combination of control systems for each weight transfer is conducted to determine the configuration with the highest performance regarding acceleration time, braking distance, and steering behavior. [ABSTRACT FROM AUTHOR]

The objectives of this paper are to investigate the trade-offs between a physically constrained neural network and a deep, convolutional neural network and to design a combined ML approach ("VarioCNN"). Our solution is provided in the framework of a cyberinfrastructure that includes a newly designed ML software, GEOCLASS-image (v1.0), modern high-resolution satellite image data sets (Maxar WorldView data), and instructions/descriptions that may facilitate solving similar spatial classification problems. Combining the advantages of the physically-driven connectionist-geostatistical classification method with those of an efficient CNN, VarioCNN provides a means for rapid and efficient extraction of complex geophysical information from submeter resolution satellite imagery. A retraining loop overcomes the difficulties of creating a labeled training data set. Computational analyses and developments are centered on a specific, but generalizable, geophysical problem: The classification of crevasse types that form during the surge of a glacier system. A surge is a glacial catastrophe, an acceleration of a glacier to typically 100–200 times its normal velocity. GEOCLASS-image is applied to study the current (2016-2024) surge in the Negribreen Glacier System, Svalbard. The geophysical result is a description of the structural evolution and expansion of the surge, based on crevasse types that capture ice deformation in six simplified classes. [ABSTRACT FROM AUTHOR]

A novel technique suitable for the propulsion of small unmanned aerial vehicles (UAV) is discussed in this paper. This approach utilizes the rotational energy of airborne gyro rotors and converts it into translational propulsion for the vehicle. The energy conversion is achieved by generating precisely directed centrifugal force pulses through short-duration rotor unbalances. The accurate control of the timing and magnitude of these unbalances is crucial for successful propulsion generation. Our first-order theory of controlled unbalance propulsion (CUP) predicts the potential for achieving high translational accelerations and vehicle velocities up to orbital levels. Power-saving levitation of UAVs can be attained. In this paper, we provide traceable evidence that pulsed centrifugal propulsion is based on well-established laws of physics and can be realized using state-of-the-art technologies. [ABSTRACT FROM AUTHOR]

Correct determination of deceleration is very important from the aspect of the investigation of traffic accidents, because deceleration of the vehicle involved in the traffic accident is of key importance for the preparation of a quality finding and opinion of traffic expert. In this paper it was conducted the investigation how the change of the pressure affects the change of the temperature of the brake couple and how this change is later reflected in the deceleration of the vehicle and the braking distance. In order to find how the temperature influences the deceleration, it was conducted experimental investigation. The experimental investigation was conducted on the experimental test rig, which simulates the braking process for the quarter of the vehicle mass, and the experimental investigation was conducted for four different braking pressures: 2 MPa, 3 MPa, 4 MPa, and 5 MPa. The temperature of the brake couple was measured during the entire braking process. Also the difference between mean fully developed deceleration and average vehicle deceleration is shown. It was found that for the case when the braking pressure was 5 MPa, the maximum deceleration value was greater than the value of gravity of Earth which may impair the stability of the vehicle. When the braking pressure was 2 MPa, 3 MPa, and 4 MPa, the temperature increased, respectively, but in the last measurement, when the braking pressure was 5 MPa, it began to decrease. Braking distance decreased with the increment of the braking pressure. Also, with the braking pressure increment, the deceleration increased in all case. [ABSTRACT FROM AUTHOR]

In the present paper, motion trajectories corresponding to the working process for a multibody system, specifically a serial robot structure, have been studied. Within working processes, robots perform mechanical motions, where active forces are governed by laws of temporal variation, thus inducing higher-order accelerations in the mechanical system. These accelerations become essential in the analysis of acceleration energies. The study of advanced dynamics of multibody systems, often characterized by symmetry, is approached by applying differential and variational principles, frequently utilizing Lagrange-Euler equations, as well as Gibbs--Appell equations, where the central function is represented by the acceleration energy of first order. Considering these aspects, in this paper will be determined generalized inertia forces, as components in dynamic control functions of the mechanical systems. [ABSTRACT FROM AUTHOR]

The Green Light Optimal Speed Advisory (GLOSA) system suggests speeds to vehicles to assist them pass intersections during green intervals. In application, drivers can ultimately decide whether to change speed based on their driving experience. However, with the gradual popularization of autonomous driving, drivers are gradually leaving the driving area. Therefore, the central algorithms in on-board systems need to be trained more intelligently for autonomous decision-making. Specifically, we found that the frequency of decision making can significantly affect the performance of the GLOSA system, but this issue has not been discussed in previous research. In this paper, we propose an adaptive frequency GLOSA (AF-GLOSA) model based on deep reinforcement learning (DRL) algorithm. Different from traditional models, this model can extract effective features from raw data and learn decision-making experience through constant interaction with simulated environments. By using parameterized action spaces, we divided the GLOSA task into two parts: frequency control and speed consultation. The frequency control module helps filter out unnecessary operations, and the speed consultation module provides acceleration suggestions based on the results of the upper model. In addition, we have designed a novel reward function to balance fuel consumption and travel efficiency. Finally, the AF-GLOSA model was evaluated in both single intersection and multi-intersection scenarios in SUMO. The results indicate that the model can effectively reduce fuel consumption and carbon dioxide emissions in both cases. In term of the number of stops, the single-intersection outperforms the state-of-the-art method and the multi-intersection approaches the state-of-the-art method. The final results also demonstrate the necessity of considering decision-making frequency. [ABSTRACT FROM AUTHOR]

China's southwestern region boasts abundant hydropower resources. However, the area is prone to frequent strong earthquakes. The areas surrounding dam sites typically have deep overburden, and the liquefaction of saturated sand foundations by earthquakes poses significant safety risks to the construction of high dams in the southwest. The effects of liquefaction and reinforcing measures on the foundations of rockfill dams on liquefiable overburden under seismic action are currently the subject of somewhat unsystematic investigations. The paper utilizes the total stress and effective stress methods, based on the equivalent linear model, to perform numerical simulations on the overburden foundations of rockfill dams. The study explores how factors such as dam height, overburden thickness, liquefiable layer depth, liquefiable layer thickness, ground motion intensity, and seismic wave characteristics affect the liquefaction of the overburden foundations. Additionally, it examines how rockfill dams impact the dynamic response, considering the liquefaction effects in the overburden. The results show that although the total stress method, which ignores the cumulative evolution of pore pressure during liquefaction, can reveal the basic response trend of the dam, its results in predicting the acceleration response are significantly biased compared to those of the effective stress method, which comprehensively considers the cumulative changes in liquefaction pore pressure. Specifically, when the effect of soil liquefaction is considered, the predicted acceleration response is reduced compared to that when liquefaction is not considered, with the reduction ranging from 4% to 30%; with increases in the thickness and burial depth of the liquefiable layer, the effective stress method considering liquefaction significantly reduces the predicted peak acceleration; the effect of liquefiable soil on the attenuation of the speed response is more sensitive to the low-frequency portion of the seismic wave. The study's findings are a significant source of reference for the planning and building of rockfill dams on liquefiable overburden. [ABSTRACT FROM AUTHOR]

The integration of external devices and network connectivity into autonomous vehicles has raised significant concerns about in-vehicle security vulnerabilities. Existing security mechanisms for in-vehicle bus systems, which mainly rely on appending authentication codes and data encryption, have been extensively studied in the context of CAN and CAN-FD buses. However, these approaches are not directly applicable to Ethernet buses due to the much higher data transmission rates of Ethernet buses compared to other buses. The real-time encryption and decryption required by Ethernet buses cannot be achieved with conventional methods, necessitating an acceleration in the speed of cryptographic operations to match the demands of Ethernet communication. In response to these challenges, our paper introduces a range of cryptographic solutions specifically designed for in-vehicle Ethernet networks. We employ an AES-ECC hybrid algorithm for critical vehicle control signals, combining the efficiency of AES with the security of ECC. For multimedia signals, we propose an improved AES-128 (IAES-128) and an improved MD5 (IMD), which improve encryption time by 15.77%. Our proposed security mechanisms have been rigorously tested through attack simulations on the CANoe (version 10) platform. These tests cover both in-vehicle control signals, such as braking and throttle control, and non-critical systems like multimedia entertainment. The experimental results convincingly demonstrate that our optimized algorithms and security mechanisms ensure the secure and reliable operation of real-time communication in autonomous vehicles. [ABSTRACT FROM AUTHOR]

Predictive models for spatial correlation play an effective role in the assessment of seismic risk associated with distributed infrastructure and building portfolios. However, existing models often rely on simplified approaches, assuming isotropy and stationarity. This paper verifies these assumptions by presenting a comprehensive study using a database of 3D physics-based simulated broadband ground motions for Istanbul, generated by the SPEED software. The results reveal significant event-to-event variability and nonstationary and anisotropic characteristics of spatial correlation influenced by source, path, and site effects. The development of nonstationary correlation models requires exploring influential metrics beyond spatial proximity and gaining a deep understanding of their impact, which is the focus of this study. Analysis of the spatial correlations of peak ground displacement, peak ground velocity, peak ground acceleration, and response spectral accelerations at different periods, employing both stationary and nonstationary correlation modelling methods and considering the finite fault model, indicates that the slip distribution pattern, direction and distance of station pairs relative to earthquake rupture, soil softness, and homogeneity of soil properties significantly influence the spatial correlations of near-field earthquake ground motions. Implementation of the introduced parameters in predictive spatial correlation models enhances the precision of regional seismic hazard assessments. [ABSTRACT FROM AUTHOR]

In complex terrain, such as uneven roads or irregular terrain, two-wheeled heavy-duty self-balancing vehicles are easily affected by external interference factors, causing rollover or rendering the vehicle unable to move, which poses a greater challenge to its stability control. Therefore, it is necessary to establish a kinematic model of a two-wheeled vehicle and design a control system to study its driving stability. This paper aims to study the stability control system of a two-wheeled self-balancing vehicle under complex terrain. First, a self-balancing vehicle modeling method based on complex terrain is designed. By analyzing the motion characteristics of the self-balancing vehicle, a kinematic model suitable for complex terrain is established, which provides a basis for subsequent control algorithms. Secondly, a precise control system is designed for different terrain conditions, and parameters such as vehicle attitude, speed and acceleration are adjusted through the Proportional–Integral–Derivative (PID) control algorithm to achieve the smooth operation of the self-balancing vehicle in complex terrain. In addition, a vehicle-mounted camera is used to capture terrain images in real time, and different terrains are accurately identified through the terrain recognition algorithm based on deep learning, thereby determining the friction coefficient and effectively improving the stability of the self-balancing vehicle on complex terrain. The experimental results show that the designed control system can enable the self-balancing two-wheeled vehicle to achieve stable balance control in different terrains, and has good applicability and stability. [ABSTRACT FROM AUTHOR]

Renewable energy generation methods such as wind power and photovoltaic power have problems of randomness, intermittency, and volatility. Gravity energy storage technology can realize the stable and controllable conversion of gravity potential energy and electric energy by lifting and lowering heavy loads. The hoisting system is an important component of a gravity energy storage system, and its lifting capacity and speed seriously restrict its energy storage capacity, energy conversion efficiency, and operational safety and reliability. In this paper, a design method for a multi-rope friction hoisting system of a vertical shaft gravity energy storage system is proposed. The parameter design and calculation of the hoisting rope, balance rope, and friction wheel of the friction hoisting system under typical conditions were carried out. The static and dynamic anti-slip capabilities of the friction hoisting system under the typical condition were explored. The results show that the maximum acceleration and deceleration speed of the compacted strand wire rope scheme is the largest, and the lifting and lowering time is the shortest. The maximum acceleration and deceleration speed of the triangular strand wire rope scheme is the lowest, and the lifting and lowering time is the longest. The dynamic tension of the hoisting rope at the heavy-load end is positively correlated with the acceleration, and the maximum value occurs in the accelerated lifting stage and decelerated lowering stage of the heavy load. The static anti-slip safety factor between the hoisting rope and the friction lining and the specific pressure between the hoisting rope and the friction lining comply with the requirements of China's Safety Regulations for Coal Mines. The dynamic anti-slip safety factor of the hoisting system under different rope selection schemes is greater than the minimum value of 1.25 stipulated in the Safety Regulations for Metal and Nonmetal Mines. The research results are of great significance for the safety, reliability, and stable and efficient energy storage of a gravity energy storage system. [ABSTRACT FROM AUTHOR]

Autonomous vehicles frequently encounter performance degradation during high-speed cornering due to excessive speed and lateral acceleration, potentially leading to collisions or rollovers. This paper proposes a novel curve-passing control approach that first estimates the curve radius and then controls the steer and speed for smooth and comfortable handling. In particular, the curve radius is innovatively estimated using a combination of a camera-based lane detection model and a steering wheel dynamic model. The curve-passing control approach is validated on high-speed ramps and curves, demonstrating its robustness and intelligence to adapt to dynamic changes in curve curvature. The model effectively prevents vehicles from entering curves at dangerously high speeds from straight roads and mitigates sudden accelerations or decelerations when entering curves. Experimental results indicate that the vehicle speed is reduced to around 50 km/h and the corresponding acceleration is −0.6 m/s2 upon entering curves with a minimum radius of 150 m. This demonstrates that the proposed control model can ensure a comfortable and safe driving experience by autonomously decelerating the vehicle before entering various types of curves. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive analysis of the electric-drive-wheel (EDW) with idler gear. From the perspective of automotive engineering, the EDW is an integrated execution unit that combines the function of powertrain and suspension. As a result, the research on EDW involves the intersection of multiple disciplines. The evolution of idler gear configuration requires some geometric constraints. Under this premise, the longitudinal and vertical dynamic characteristics of the system were studied, respectively. There are several factors that influence the system performance, such as the gear parameters, the position of the electric motor, and the suspension K&C value. The principles of each parameter on the output indicators were studied, with an optimized plan and simulation comparison to check the correctness of theory. In the end, the prototype was equipped with a test bench, covering a wide range of working operations to examine the expected performance of EDW design. The step response test of the EDW result showed a balanced performance in transmission smoothness and responsiveness agility. [ABSTRACT FROM AUTHOR]

The traffic environment in tunnel entrance area is complex, with prominent issues related to safety and efficiency. However, existing models find it difficult to accurately capture the traffic situation in this area. Therefore, this paper establishes a vehicle dynamics model for the entrance area of a tunnel based on the social force model and artificial potential field. This model can characterize the deceleration behavior of vehicles at the entrance of the tunnel and the interaction between vehicles. By considering the special effects of the tunnel environment, the simulation experiments successfully reproduce the congestion phenomenon in the entrance of the tunnel. Based on this model, this paper proposes a coordinated driving model under vehicle to vehicle (V2V) communication environment, and the simulation results show that this model can effectively alleviate the congestion in the entrance area of the tunnel and improve traffic efficiency. [ABSTRACT FROM AUTHOR]

This paper demonstrates the enhanced resilience performance of steel structures with viscoelastic friction dampers (VEFDs) based on numerical simulations of building responses. Velocity-dependent dampers, which are widely used to increase seismic resilience, may increase the axial force of the column under strong earthquake conditions because the generated force depends on the interstory velocity. This often leads to plastic hinges being placed on the columns of the structure, which can lead to structural collapse via weak-layer failure. In addition, while viscoelastic dampers are effective in reducing story drift, peak acceleration, and peak velocity, the proposed hybrid VEFD offers the additional benefit of reducing base shear via the friction damper. Simulation results for 10- and 20-story buildings with the novel VEFDs show that the proposed dampers can control drift and plastic deformation in structural members. Nonlinear dynamic analysis of 20 far-fault seismic ground motion records conducted using OpenSees also reveals lower peak absolute floor acceleration and velocity. Overall, the results suggest that the proposed VEFD has excellent potential for use in the performance-based seismic design of structures because it can reduce both structural and nonstructural damage. The results verify the damper's effectiveness in controlling story drift without a significant increase in the base shear. Collapse probability assessment also demonstrates the collapse resistance of moment-resisting frames when used in conjunction with VEFDs. [ABSTRACT FROM AUTHOR]

This study proposes a cooperative lane‐changing control framework for multiple vehicles in freeway ramp merging areas, aiming to achieve safe and efficient merging. Specifically, multiple connected and automated vehicles (CAVs) form triplets to participate in cooperative lane‐changing. The framework consists of two stages: Longitudinal Headway Adjustment (LHA) and Lane‐Changing Execution (LCE). In the LHA stage, a centralized longitudinal controller is developed based on the vehicle's longitudinal dynamics model to optimize the longitudinal velocity of the cooperative vehicles and create suitable gaps for merging vehicles. In the LCE stage, an optimal lane‐changing reference trajectory is generated using a quintic polynomial and a lateral controller is designed based on the vehicle's lateral dynamics model. Model Predictive Control (MPC) is utilized for trajectory tracking. The simulation results obtained using MATLAB/Simulink, GPOPS, and CarSim demonstrate that the proposed control strategy can be applied to different vehicle speed control scenarios. Taking a specific velocity combination as an example, the cumulative control errors in the longitudinal and lateral directions for PV (Preceding Vehicle), SV (Subject Vehicle), and FV (Following Vehicle) are 1.4014 m, 0.5631 m, and −0.7601 m, respectively, satisfying the safety distance requirements. Compared to the Linear Quadratic Regulator (LQR) control, the proposed strategy improves control efficiency by 145.03%, 69.64%, 43.18%, and 67.61% in terms of comprehensive spacing errors, synthesized acceleration, front wheel angle, and speed fluctuation, respectively. These research findings highlight the superior performance of the proposed control strategy in terms of traffic efficiency, comfort, safety, and vehicle stability. [ABSTRACT FROM AUTHOR]

In addressing the critical issue of right-of-way conflicts in mixed-traffic environments, this paper introduces a novel shared right-of-way driving strategy that encompasses two guiding frameworks for resolution. The first framework applies to active lane changing. Before lane changing occurs, this framework allocates the right of way for autonomous vehicles (AVs). Based on the allocated right of way, the AVs decide whether to send a request for a shared right of way to relevant vehicles. To enhance lane-changing comfort, the vehicle assesses whether the variance of roll and lateral acceleration exceeds a preset threshold, ultimately deciding whether to proceed with the lane change. The second framework pertains to passive lane changing. After detecting an obstacle, this framework allocates the right of way. The AVs calculate acceleration based on their speed and distance from the obstacle, using this information to determine whether to change lanes or decelerate in order to avoid the obstacle. If lane changing is chosen, further evaluation is necessary. Based on the allocated right of way, the AVs decide whether to request a shared right of way from relevant vehicles. To improve lane-changing comfort, the AVs compare the variance of roll and lateral acceleration with that of pitch and longitudinal acceleration, and then they decide whether to proceed with the lane change. The proposed strategy has been validated in various scenarios, including high-speed (105 km/h), low speed (13 km/h), and general scenarios with AVs and obstacles at a distance of 125 m. The results show that the strategy effectively functions in both high-speed and low-speed scenarios. [ABSTRACT FROM AUTHOR]

This paper reports an application of the Lie algebra s e (3) of the Euclidean group S E (3) , which is isomorphic to the theory of screws in the velocity and acceleration analyses of serial manipulators. The symbolic computation of the infinitesimal kinematics allows one to obtain algebraic expressions related to the kinematic characteristics of the end effector of the serial manipulator, while in the case of complex manipulators, numerical computations are preferred owing to the emergence of long terms. The algorithm presented enables the symbolic computation of the velocity and acceleration characteristics of the end effector in serial manipulators in order to allow the compact and efficient modeling of velocity and acceleration analyses of both parallel and serial robotic manipulators. Unlike other algebras, these procedures can be extended without significant effort to higher-order analyses such as the jerk and jounce. [ABSTRACT FROM AUTHOR]

Trajectory-following control is the basis for the practical application of an articulated virtual rail train transportation system. In this paper, a planar nonlinear dynamics model of an articulated vehicle is derived using the Euler–Lagrange method. A trajectory-following control strategy based on the first following point is proposed, and a feedback linearization control algorithm is designed based on the vehicle dynamics model to achieve the trajectory following of the rear vehicle. Based on the target trajectory formed by the first following point and measured by virtual sensors, a vector analysis method grounded in geometric relationships is proposed to solve in real time for the desired position, velocity, and acceleration of the vehicle. Finally, a MATLAB/SIMPACK dynamics virtual prototype is established to test the vehicle's trajectory-following effectiveness and dynamics performance under lane change and circular curve routes. The results indicate that the control algorithm can achieve trajectory following while maintaining good vehicle dynamics performance. It is robust to variations in vehicle mass, vehicle speed, tire cornering stiffness, and road friction coefficient. [ABSTRACT FROM AUTHOR]

A method to deduce the characteristics of rail corrugation was developed and presented in this paper. It has been found that noise and vibration in the train vehicle were primarily contributed by rail corrugation and wheel polygonalisation. As the characteristics of wheel sets of a particular train can be assumed to be unchanged during a trip, rail corrugation along the tracks of the trip can be identified. Wavelet analysis was employed in analysing interior noise and vibration data collected inside a high‐speed train vehicle traveling on a typical high‐speed line in China. Noise and vibration data corresponding to increasing, decreasing, and unchanged train speeds were grouped and examined using time‐frequency domain analysis. For both acceleration and deceleration speed conditions, the characteristic frequency of interior noise and vibration changes as the train speed changes, in a discontinuous pattern, and with a fixed speed‐frequency ratio, which can be deducted as the pinned‐pinned frequency of rail vibration and wavelength of rail corrugation in corresponding rail track sections. This method enables accurate restoration of rail corrugation characteristics, without having to apply for railway possession for rail corrugation tests onsite, which is an inexpensive yet reliable method to provide a basis for the formulation of line maintenance and rail grinding plans. [ABSTRACT FROM AUTHOR]

Recently, hub motor driven vehicles (HMDV) have been recognized as the ideal configuration of electric vehicles in the future. However, the adverse effect of its special structure configuration seriously affects the vehicles dynamic performance, and becomes the bottleneck of its further development and industrial application. In this paper, the characteristics of inertial suspension adjusting vertical motion inertia are utilized to suppress the HMDV adverse effect. Firstly, the coupling model of vehicle suspension and hub motor is established, and the coupling excitation of road surface and unbalanced electromagnetic force on vehicle suspension is studied. Aiming at the influence mechanism of the adverse effect, an inertial suspension model of the skyhook and groundhook (SH-GH) algorithm is established. Moreover, with the primary goal of improving the ride comfort, an inertial suspension and the mixed skyhook and power-driven-damper (SH-PDD) algorithm are combined. Particle swarm optimization (PSO) is utilized to optimize suspension performance. The results show that the RMS value of body acceleration, unbalanced radial force and dynamic tire load of inertial suspension decreased by 10.91%, 50% and 8.53%. It is proved that its characteristics can effectively suppress the HMDV adverse effects. The SH-GH inertial suspension also further reduces the vehicle performance index. The SH-PDD inertial suspension reduces the RMS value of body acceleration by 27.45%, significantly improves the vehicle ride comfort. In general, the inertial suspension proposed in this paper can effectively suppress the adverse effect of HMDV vertical vibration, and improve the HMDV ride comfort and road friendliness. It provides a new direction for the research of suppressing the adverse effect of HMDV vertical vibration. [ABSTRACT FROM AUTHOR]

In this paper, we study the jerk vector that is the rate of change of the acceleration vector over time. In three‐dimensional space, the decomposition of the jerk vector is a new concept in the field. This decomposition expresses the jerk vector as the sum of three unique components in specific directions: the tangential direction, the radial direction in the osculating plane, and the radial direction in the rectifying plane. The snap vector is the rate of change of the jerk vector over time. In this paper, the authors examine non‐relativistic particles moving along non‐lightlike Frenet curves at low speeds compared to the speed of light in Minkowski 3‐space. They resolve the jerk and snap vectors using Frenet–Serret frames. Additionally, the cases for motion along non‐lightlike Frenet planar curves in the Minkowski 3‐space are given as corollaries. To help understand these results, the paper provides some illustrative examples [ABSTRACT FROM AUTHOR]

Background: In example‐based learning, examples are often combined with generative activities, such as comparative self‐explanations of example cases. Comparisons induce heavy demands on working memory, especially in complex domains. Hence, only stronger learners may benefit from comparative self‐explanations. While static text‐based examples can be compared easily, this is challenging for transient video‐based modelling examples used in complex domains because simultaneous processing of two videos is not feasible. Objectives: To allow for such comparisons, we combined video‐based modelling examples with static representations (i.e., summarizing tables) of the observed optimal and a suboptimal solution of the problem‐solving process. A comparative self‐explanation prompt asked learners to compare the different solution approaches. Our study investigated the impact of video‐based modelling examples versus independent problem‐solving on cognitive load and problem‐solving skill development. Moreover, we investigated the effects of comparative versus sequential self‐explanation prompts, depending on learners' prior knowledge. Methods: In an experiment, 118 automotive apprentices learned a car malfunction diagnosis strategy. Apprentices were divided into three groups: (1) modelling examples with comparative self‐explanation prompts, (2) modelling examples with sequential prompts, and (3) no examples or prompts. Diagnostic knowledge and skills were assessed before and after the intervention. Cognitive load was measured retrospectively. Results and conclusions: Despite no observed effects on cognitive load, modelling examples enhanced diagnostic knowledge and diagnostic skills with scaffolds, though not independent diagnostic skills without scaffolds. The need for more practice opportunities to foster independent diagnostic skills is assumed. Additionally, comparative prompts seem promising for learners with higher prior knowledge. Takeaways: Video‐based modelling examples were more beneficial for learning than practising to apply the diagnostic strategy. Static representations allow for comparisons of video examples and comparative prompts are promising for learners with higher prior knowledge (cf. expertise‐reversal effect). Further research, especially on the effects on cognitive load, is necessary. Lay Description: What is already known about the topic?: Text and video examples that model how to solve a problem are widely used in education.Text examples often include self‐explanation prompts that ask learners to compare several examples.For video examples, such comparison prompts have seldom been investigated, because comparisons are difficult to implement for transient videos. What does this paper add?: This paper shows that video examples combined with static summaries of processes that have been shown in the video example are effective and allow for comparisons of video examples.Such comparisons seem to be more promising for learners with higher prior knowledge. Implications for practice: Practitioners could combine video examples with static summaries of the processes shown in the video examples to allow for comparisons. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel equivalent composite control architecture for electro-optical equipment. The improved tracking performance and loss of robustness caused by this structure have a clear relationship with a 2 , the time coefficient of the compensation circuit. The compensation circuit can make the speed quality factor and the acceleration quality factor of the system infinite, and the jerk quality factor can be expanded to 1 / a 2 times the original acceleration quality factor, but it will cause a main zero point of the servo system to be far away from the virtual axis and the main poles to be close to the virtual axis. As the time coefficient of the compensation loop controller decreases, the tracking performance of the system increases, but the robustness decreases, the dynamic response deteriorates, the water bed effect becomes more obvious, and the system is more susceptible to noise and disturbances. Compared to the existing method, our method focuses on system performance and robustness. Experimental results show that our method can achieve target tracking with a peak accuracy of 64 ″ and 22 ″ (RMS), which is superior to the tracking performance without equivalent composite control. [ABSTRACT FROM AUTHOR]

In warehouses with vast quantities of heavy goods, heavy-duty forklift Automated Guided Vehicles (AGVs) play a key role in facilitating efficient warehouse automation. Due to their large load capacity and high inertia, heavy-duty forklift AGVs struggle to automatically navigate optimized routes. Additionally, rapid acceleration and deceleration can pose safety hazards. This paper proposes a velocity-adaptive model predictive control (MPC)-based path tracking method for heavy-duty forklift AGVs. The movement of heavy-duty forklift-type AGVs is categorized into straight-line and curve-turning motions, corresponding to the straight and curved sections of the reference path, respectively. These sections are segmented based on their curvature. The best driving speeds for straight and curved sections were 1.5 m/s and 0.3 m/s, respectively, while the optimal acceleration rates were 0.2 m/s2 for acceleration and −0.2 m/s2 for deceleration in straight paths and 0.3 m/s2 for acceleration with −0.15 m/s2 for deceleration in curves. Moreover, preferred sampling times, prediction domain, and control domain were determined through simulations at various speeds. Four path tracking methods, including pure tracking, Linear Quadratic Regulator (LQR), MPC, and the velocity-adaptive MPC, were simulated and evaluated under straight-line, turning, and complex double lane change conditions. Field experiments conducted in a warehouse environment demonstrated the effectiveness of the proposed path tracking method. Findings have implications for advancing path tracking control in narrow aisles. [ABSTRACT FROM AUTHOR]