Multiparameter Numerical Investigation of Two Types of Moving Interactions Between the Deep-Sea Mining Vehicle Track Plate and Seabed Soil:Digging and Rotating Motions

To ensure the safe performance of deep-sea mining vehicles(DSMVs),it is necessary to study the mechanical characteristics of the interaction between the seabed soil and the track plate.The rotation and digging motions of the track plate are important links in the contact between the driving mechanism of the DSMV and seabed soil.In this study,a numerical simulation is conducted using the coupled Eulerian–Lagrangian(CEL)large deformation numerical method to investigate the interaction between the track plate of the DSMV and the seabed soil under two working conditions:rotating condition and digging condition.First,a soil numerical model is established based on the elastoplastic mechanical characterization using the basic physical and mechanical properties of the seabed soil obtained by in situ sampling.Subsequently,the soil disturbance mechanism and the dynamic mechanical response of the track plate under rotating and digging conditions are obtained through the analysis of the sensitivity of the motion parameters,the grouser structure,the layered soil features and the soil heterogeneity.The results indicate that the above parameters remarkably influence the interaction between the DSMV and the seabed soil.Therefore,it is important to consider the rotating and digging motion of the DSMV in practical engineering to develop a detailed optimization design of the track plate.

Multi-Body Dynamics Modeling of Heavy Goods Vehicle-Rail Interaction

Based on the principle of vehicle-track coupling dynamics, SIMPACK multi-body dynamics software is used to establish a C80 wagon line-coupled multi-body dynamics model with 73 degrees of freedom. And the reasonableness of the line-coupled dynamics model is verified by using the maximum residual acceleration, the nonlinear critical speed of the wagon. The experimental results show that the established vehicle line coupling dynamics model meets the requirements of vehicle line coupling dynamics modeling.

3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.

Intelligent extraction of road cracks based on vehicle laser point cloud and panoramic sequence images

In light of the limited efficacy of conventional methods for identifying pavement cracks and the absence of comprehensive depth and location data in two-dimensional photographs,this study presents an intelligent strategy for extracting road cracks.This methodology involves the integration of laser point cloud data obtained from a vehicle-mounted system and a panoramic sequence of images.The study employs a vehicle-mounted LiDAR measurement system to acquire laser point cloud and panoramic sequence image data simultaneously.A convolutional neural network is utilized to extract cracks from the panoramic sequence image.The extracted sequence image is then aligned with the laser point cloud,enabling the assignment of RGB information to the vehicle-mounted three dimensional(3D)point cloud and location information to the two dimensional(2D)panoramic image.Additionally,a threshold value is set based on the crack elevation change to extract the aligned roadway point cloud.The three-dimensional data pertaining to the cracks can be acquired.The experimental findings demonstrate that the use of convolutional neural networks has yielded noteworthy outcomes in the extraction of road cracks.The utilization of point cloud and image alignment techniques enables the extraction of precise location data pertaining to road cracks.This approach exhibits superior accuracy when compared to conventional methods.Moreover,it facilitates rapid and accurate identification and localization of road cracks,thereby playing a crucial role in ensuring road maintenance and traffic safety.Consequently,this technique finds extensive application in the domains of intelligent transportation and urbanization development.The technology exhibits significant promise for use in the domains of intelligent transportation and city development.

Vehicle-Bridge Interaction Simulation and Damage Identification of a Bridge Using Responses Measured in a Passing Vehicle by Empirical Mode Decomposition Method

To prevent early bridge failures, effective Structural Health Monitoring (SHM) is vital. Vibration-based damage assessment is a powerful tool in this regard, as it relies on changes in a structure’s dynamic characteristics as it degrades. By measuring the vibration response of a bridge due to passing vehicles, this approach can identify potential structural damage. This dissertation introduces a novel technique grounded in Vehicle-Bridge Interaction (VBI) to evaluate bridge health. It aims to detect damage by analyzing the response of passing vehicles, taking into account VBI. The theoretical foundation of this method begins with representing the bridge’s superstructure using a Finite Element Model and employing a half-car dynamic model to simulate the vehicle with suspension. Two sets of motion equations, one for the bridge and one for the vehicle are generated using the Finite Element Method, mode superposition, and D’Alembert’s principle. The combined dynamics are solved using the Newmark-beta method, accounting for road surface roughness. A new approach for damage identification based on the response of passing vehicles is proposed. The response is theoretically composed of vehicle frequency, bridge natural frequency, and a pseudo-frequency component related to vehicle speed. The Empirical Mode Decomposition (EMD) method is applied to decompose the signal into its constituent parts, and damage detection relies on the Intrinsic Mode Functions (IMFs) corresponding to the vehicle speed component. This technique effectively identifies various damage scenarios considered in the study.

Dynamic interactions of an integrated vehicle–electromagnetic energy harvester–tire system subject to uneven road excitations

An investigation is undertaken of an integrated mechanical-electromagnetic coupling system consisting of a rigid vehicle with heave, roll, and pitch motions, four electromagnetic energy harvesters and four tires subject to uneven road excitations in order to improve the passengers' riding comfort and harvest the lost engine energy due to uneven roads. Following the derived mathematical formulations and the proposed solution approaches, the numerical simulations of this interaction system subject to a continuous sinusoidal road excitation and a single ramp impact are completed. The simulation results are presented as the dynamic response curves in the forms of the frequency spectrum and the time history, which reveals the complex interaction characteristics of the system for vibration reductions and energy harvesting performance. It has addressed the coupling effects on the dynamic characteristics of the integrated system caused by: (1) the natural modes and frequencies of the vehicle; (2) the vehicle rolling and pitching motions; (3) different road excitations on four wheels; (4) the time delay of a road ramp to impact both the front and rear wheels, etc., which cannot be tackled by an often used quarter vehicle model. The guidelines for engineering applications are given. The developed coupling model and the revealed concept provide a means with analysis idea to investigate the details of four energy harvester motions for electromagnetic suspension designs in order to replace the current passive vehicle isolators and to harvest the lost engine energy. Potential further research directions are suggested for readers to consider in the future.

A Workable Solution for Reducing the Large Number of Vehicle and Pedestrian Accidents Occurring on a Yellow Light

Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.

Modeling continuous traffic flow with the average velocity effect of multiple vehicles ahead on gyroidal roads

In the future connected vehicle environment,the information of multiple vehicles ahead can be readily collected in real-time,such as the velocity or headway,which provides more opportunities for information exchange and cooperative control.Meanwhile,gyroidal roads are one of the fundamental road patterns prevalent in mountainous areas.To effectively control the system,it is therefore significant to explore the evolution mechanism of traffic flow on gyroidal roads under a connected vehicle environment.In this paper,we present a new continuum model with the average velocity of multiple vehicles ahead on gyroidal roads.The stability criterion and KdV-Burger equation are deduced via linear and nonlinear stability analysis,respectively.Solving the above KdV-Burger equation yields the density wave solution,which explores the formation and propagation property of traffic jams near the neutral stability curve.Simulation examples verify that the model can reproduce complex phenomena,such as shock waves and rarefaction waves.The analysis of the local cluster effect shows that the number of vehicles ahead and the radius information,and the slope information of gyroidal roads can exert a great influence on traffic jams.The effect of the first and second terms are positive,while the last term is negative.

A Numerical and Experimental Study on the Hull-Propeller Interaction of A Long Range Autonomous Underwater Vehicle

Range is an important factor to the design of autonomous underwater vehicles (AUVs), while drag reduction efforts are pursued, the investigation of body-propeller interaction is another vital consideration. We present a numerical and experimental study of the hull-propeller interaction for deeply submerged underwater vehicles, using a proportional-integral- derivative (PID) controller method to estimate self-propulsion point in CFD environment. The hydrodynamic performance of hull and propeller at the balance state when the AUV sails at a fixed depth is investigated, using steady RANS solver of Star-CCM+. The proposed steady RANS solver takes only hours to reach a reasonable solution. It is more time efficient than unsteady simulations which takes days or weeks, as well as huge consumption of computing resources. Explorer 1000, a long range AUV developed by Shenyang Institute of Automation, Chinese Academy of Sciences, was studied as an object, and self-propulsion point, thrust deduction, wake fraction and hull efficiency were analyzed by using the proposed RANS method. Behind-hull performance of the selected propeller MAU4-40, as well as the hull-propeller interaction, was obtained from the computed hydrodynamic forces. The numerical results are in good qualitative and quantitative agreement with the experimental results obtained in the Qiandao Lake of Zhejiang province, China.

Self-excited vibration problems of maglev vehicle-bridge interaction system

The self-excited vibration problems of maglev vehicle-bridge interaction system were addressed, which greatly degrades the stability of the levitation control, decreases the ride comfort, and restricts the cost of the whole system. Firstly, the coupled model containing the quintessential parts was built, and the mechanism of self-excited vibration was explained in terms of energy transmission from levitation system to bridge. Then, the influences of the parameters of the widely used integral-type proportion and derivation(PD) controller and the delay of signals on the stability of the interaction system were analyzed. The result shows that the integral-type PD control is a nonoptimal approach to solve the self-excited vibration completely. Furthermore, the differential-type PD controller can guarantee the passivity of levitation system at full band. However, the differentiation of levitation gap should be filtered by a low-pass filter due to noise of gap differentiation. The analysis indicates that a well tuned low-pass filter can still keep the coupled system stable.

RFHUI:an RFID based human-unmanned aerial vehicle interaction system in an indoor environment

In this paper,we present an RFID based human and Unmanned Aerial Vehicle(UAV)Interaction system,termed RFHUI,to provide an intuitive and easy-to-operate method to navigate a UAV in an indoor environment.It relies on the passive Radio-Frequency IDentification(RFID)technology to precisely track the pose of a handheld controller,and then transfer the pose information to navigate the UAV.A prototype of the handheld controller is created by attaching three or more Ultra High Frequency(UHF)RFID tags to a board.A Commercial Off-The-Shelf(COTS)RFID reader with multiple antennas is deployed to collect the observations of the tags.First,the precise positions of all the tags can be obtained by our proposed method,which leverages a Bayesian filter and Channel State Information(CSI)phase measurements collected from the RFID reader.Second,we introduce a Singular Value Decomposition(SVD)based approach to obtain a 6-DoF(Degrees of Freedom)pose of the controller from estimated positions of the tags.Furthermore,the pose of the controller can be precisely tracked in a real-time manner,while the user moves the controller.Finally,control commands will be generated from the controller's pose and sent to the UAV for navigation.The performance of the RFHUI is evaluated by several experiments.The results show that it provides precise poses with 0.045m mean error in position and 2.5∘mean error in orientation for the controller,and enables the controller to precisely and intuitively navigate the UAV in an indoor environment.

Alterable-element Method for Vehicle-bridge Interaction Considering the Transient Jump of Wheel

The so called "alterable-element method" (AEM) was introduced to deal with the coupling interac-tion of vehicle and sub-structure considering the actual transient jump of wheel, while the classical "contact all along" assumption based on which wheels and lower structure are always contact was abandoned. The alterable element used in this method is a conceptional element, which is used to calculate the coupling interaction of upper and lower structures and has some typical characteristics: firstly it flows along with the moving of contact point; secondly whether it is used for calculation depends on the contact state; thirdly its sizes could change according to specific problems and so on. VISUAL FORTRAN program was coded, and different moving vehicle models were presented taking into consideration the effects of random corrugation in the numerical study. The numerical solutions are favored comparing with the results obtained by alternative methods when there is no jump phenomenon existed. With abrupt irregularity, the transient jump of wheel was studied using the present method.

An overview of a unified theory of dynamics of vehicle–pavement interaction under moving and stochastic load

This article lays out a unified theory for dynamics of vehicle-pavement interaction under moving and stochastic loads. It covers three major aspects of the subject： pavement surface, tire-pavement contact forces, and response of continuum media under moving and stochastic vehicular loads. Under the subject of pavement surface, the spectrum of thermal joints is analyzed using Fourier analysis of periodic function. One-dimensional and two-dimensional random field models of pavement surface are discussed given three different assumptions. Under the subject of tire-pavement contact forces, a vehicle is modeled as a linear system. At a constant speed of travel, random field of pavement surface serves as a stationary stochastic process exciting vehicle vibration, which, in turn, generates contact force at the interface of tire and pavement. The contact forces are analyzed in the time domain and the frequency domains using random vibration theory. It is shown that the contact force can be treated as a nonzero mean stationary process with a normal distribution. Power spectral density of the contact force of a vehicle with walking-beam suspension is simulated as an illustration. Under the subject of response of continuum media under moving and stochastic vehicular loads, both time-domain and frequency-domain analyses are presented for analytic treatment of moving load problem. It is shown that stochastic response of linear continuum media subject to a moving stationary load is a nonstationary process. Such a nonstationary stochastic process can be converted to a stationary stochastic process in a follow-up moving coordinate.

ExperimentalVerificationofaDetailedVehicle┐TrackVerticalInteractionModel

A theoretical model has been developed to investigate vertical dynamic interactions between railway vehicles and tracks. Wheel rail forces and dynamic responses of vehicle and track components can be simulated with the model. The model has been applied to the study of high speed and heavy haul railway dynamic problems. In order to verify the model completely, a full scale field experiment was performed on the Chinese Datong Qinhuangdao railway. Accelerations of rail, sleeper and ballast were measured and compared with the simulated results both in time domain and in frequency domain.

Evaluation of High-Speed Track Quality Using Dynamic Simulation of Vehicle-Track Interaction

Track quality is a determinant factor for evaluating the overall performance of vehicle track interaction with respect to safety, ride quality and maintenance. Important parameters specifying the general quality of the track include track geometry (undamped) and track stiffness (damped), which can be evaluated by measurements taken along with track sections. A new co-simulation model based on Finite Element Method (FEM) and Multi Body Simulation (MBS) is built for the detailed description of track quality and its contribution to vehicle track interaction without simplifying the track structure as interconnected single elements. The simulation models and tools have been validated with the help of measured track geometry, track stiffness and dynamic wheel rail forces along the track sections of high speed lines. A comparative study between high speed lines using conventional ballasted track and ballastless track showed a significantly better quality in ballastless track sections. The dynamic forces which were determined by simulations and verified by measurements along the ballastless track section were comparatively less than the specified limits by German regulations for ballastless track design. Lower levels of dynamic forces can be utilized for optimization of track design and installation procedures with respect to lower initial costs.

Dual Extended Kalman Filter for Combined Estimation of Vehicle State and Road Friction

Vehicle state and tire-road adhesion are of great use and importance to vehicle active safety control systems. However, it is always not easy to obtain the information with high accuracy and low expense. Recently, many estimation methods have been put forward to solve such problems, in which Kalman filter becomes one of the most popular techniques. Nevertheless, the use of complicated model always leads to poor real-time estimation while the role of road friction coefficient is often ignored. For the purpose of enhancing the real time performance of the algorithm and pursuing precise estimation of vehicle states, a model-based estimator is proposed to conduct combined estimation of vehicle states and road friction coefficients. The estimator is designed based on a three-DOF vehicle model coupled with the Highway Safety Research Institute（HSRI） tire model; the dual extended Kalman filter （DEKF） technique is employed, which can be regarded as two extended Kalman filters operating and communicating simultaneously. Effectiveness of the estimation is firstly examined by comparing the outputs of the estimator with the responses of the vehicle model in CarSim under three typical road adhesion conditions（high-friction, low-friction, and joint-friction）. On this basis, driving simulator experiments are carried out to further investigate the practical application of the estimator. Numerical results from CarSim and driving simulator both demonstrate that the estimator designed is capable of estimating the vehicle states and road friction coefficient with reasonable accuracy. The DEKF-based estimator proposed provides the essential information for the vehicle active control system with low expense and decent precision, and offers the possibility of real car application in future.

Torque Distribution of Electric Vehicle with Four In-Wheel Motors Based on Road Adhesion Margin

With the worsening of energy crisis and environmental pollution,electric vehicles with four in?wheel motors have been paid more and more attention. The main research subject is how to reasonably distribute the driving torque of each wheel. Considering the longitudinal motion,lateral motion,yaw movement and rotation of the four wheels,the tire model and the seven DOF dynamic model of the vehicle are established in this paper. Then,the torque distribution method is proposed based on road adhesion margin,which can be divided into anti ? slip control layer and torque distribution layer. The anti?slip control layer is built based on sliding mode variable structure control,whose main function is to avoid the excessive slip of wheels caused by road conditions. The torque distribution layer is responsible for selecting the torque distribution method based on road adhesion margin. The simulation results show that the proposed torque distribution method can ensure the vehicle quickly adapt to current road adhesion conditions,and improve the handling stability and dynamic performance of the vehicle in the driving process.

A Shifting Strategy for Electric Commercial Vehicles Considering Mass and Gradient Estimation

The extended Kalman filter (EKF) algorithm and acceleration sensor measurements were used to identify vehiclemass and road gradient in the work. Four different states of fixed mass, variable mass, fixed slope and variableslope were set to simulate real-time working conditions, respectively. A comprehensive electric commercial vehicleshifting strategy was formulated according to the identification results. The co-simulation results showed that,compared with the recursive least square (RLS) algorithm, the proposed algorithm could identify the real-timevehicle mass and road gradient quickly and accurately. The comprehensive shifting strategy formulated had thefollowing advantages, e.g., avoiding frequent shifting of vehicles up the hill, making full use ofmotor braking downthe hill, and improving the overall performance of vehicles.

Smartphone-based bridge frequency identification using vehicle contact-point response

Bridge frequency(BF)identification using the vehicle scanning method has attracted considerable attention during the last two decades.However,most previous studies have adopted unrealistic vehicle models,thus finding limited practical applications.This study proposes a smartphone-based BF identification method that uses the contact-point acceleration response of a four degree-of-freedom vehicle model.The said response can be inferred from the vehicle body response measured by a smartphone.For realizing practical applications,this method is incorporated into a self-developed smartphone app to obtain data smoothly and identify BFs in a timely manner.Numerical and experimental investigations are performed to verify the effectiveness of the proposed method.In particular,the robustness of this method is investigated numerically against various factors,including the vehicle speed,bridge span,road roughness,and bridge type.Furthermore,laboratory calibration tests are performed to investigate the accuracy of the smartphone gyroscope in measuring the angular velocity,where anomalous data are detected and eliminated.Laboratory experiment results for a simply supported bridge indicate that the proposed method can be used to identify the first two BFs with acceptable accuracy.