Numerical Prediction of Ride Comfort of Tracked Vehicle Equipped with Novel Flexible Road Wheels

Enhancing ride comfort has always constituted a crucial focus in the design and research of modern tracked vehicles,heavily reliant on the driving system's performance.While the road wheel is a key component of the driving system,traditional road wheels predominantly adopt a solid structure,exhibiting subpar adhesion performance and damping effects,thereby falling short of meeting the demands for high-speed,stable,and long-distance driving in tracked vehicles.Addressing this issue,this paper proposes a novel type of flexible road wheel(FRW)characterized by a catenary construction.The study investigates the ride comfort of tracked vehicles equipped with flexible road wheels by integrating finite element and vehicle dynamic.First,three-dimensional(3D)finite element(FE)models of both flexible and rigid road wheels are established,considering material and contact nonlinearities.These models are validated through a wheel radial loading test.Based on the validated FE model,the paper uncovers the relationship between load and radial deformation of the road wheel,forming the basis for a nonlinear mathematical model.Subsequently,a half-car model of a tracked vehicle with seven degrees of freedom is established using Newton's second law.A random road model,considering the track effect and employing white noise,is constructed.The study concludes by examining the ride comfort of tracked vehicles equipped with flexible and rigid road wheels under various speeds and road grades.The results demonstrate that,in comparison to the rigid road wheel(RRW),the flexible road wheel enhances the ride comfort of tracked vehicles on randomly uneven roads.This research provides a theoretical foundation for the implementation of flexible road wheels in tracked vehicles.

High-speed tracked vehicle model order reduction for static and dynamic simulations

In this paper, a model order reduction strategy is adopted for the static and dynamic behaviour simulation of a high-speed tracked vehicle. The total number of degree of freedom of the structure is condensed through a selection of interface degrees of freedom and significant global mode shapes, for an approximated description of vehicle dynamic behaviour. The methodology is implemented in a customised open-source software to reduce the computational efforts. The modelled tracked vehicle includes the sprung mass, the unsprung masses, connected by means of torsional bars, and all the track assemblies, composing the track chain. The proposed research activity presents a comprehensive investigation of the influence of the track chain, combined with longitudinal vehicle speed, on statics and vehicle dynamics, focusing on vertical dynamics. The vehicle response has been investigated both in frequency and time domain. In this last case road-wheel displacements are assumed as inputs for the model, under different working conditions, hence considering several road profiles with different amplitudes and characteristic excitation frequencies. Simulation results have proven a high fidelity in model order reduction approach and a significant contribution of the track chain in the global dynamic behaviour of the tracked vehicle.

Accurately tracking hypersonic gliding vehicles via an LEO mega-constellation in relay tracking mode

In order to effectively defend against the threats of the hypersonic gliding vehicles(HGVs),HGVs should be tracked as early as possible,which is beyond the capability of the ground-based radars.Being benefited by the developing megaconstellations in low-Earth orbit,this paper proposes a relay tracking mode to track HGVs to overcome the above problem.The whole tracking mission is composed of several tracking intervals with the same duration.Within each tracking interval,several appropriate satellites are dispatched to track the HGV.Satellites that are planned to take part in the tracking mission are selected by a new derived observability criterion.The tracking performances of the proposed tracking mode and the other two traditional tracking modes,including the stare and track-rate modes,are compared by simulation.The results show that the relay tracking mode can track the whole trajectory of a HGV,while the stare mode can only provide a very short tracking arc.Moreover,the relay tracking mode achieve higher tracking accuracy with fewer attitude controls than the track-rate mode.

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.

Guaranteed Cost Attitude Tracking Control for Uncertain Quadrotor Unmanned Aerial Vehicle Under Safety Constraints

In this paper,guaranteed cost attitude tracking con-trol for uncertain quadrotor unmanned aerial vehicle(QUAV)under safety constraints is studied.First,an augmented system is constructed by the tracking error system and reference system.This transformation aims to convert the tracking control prob-lem into a stabilization control problem.Then,control barrier function and disturbance attenuation function are designed to characterize the violations of safety constraints and tolerance of uncertain disturbances,and they are incorporated into the reward function as penalty items.Based on the modified reward function,the problem is simplified as the optimal regulation problem of the nominal augmented system,and a new Hamilton-Jacobi-Bellman equation is developed.Finally,critic-only rein-forcement learning algorithm with a concurrent learning tech-nique is employed to solve the Hamilton-Jacobi-Bellman equa-tion and obtain the optimal controller.The proposed algorithm can not only ensure the reward function within an upper bound in the presence of uncertain disturbances,but also enforce safety constraints.The performance of the algorithm is evaluated by the numerical simulation.

Semantic Segmentation and YOLO Detector over Aerial Vehicle Images

Intelligent vehicle tracking and detection are crucial tasks in the realm of highway management.However,vehicles come in a range of sizes,which is challenging to detect,affecting the traffic monitoring system’s overall accuracy.Deep learning is considered to be an efficient method for object detection in vision-based systems.In this paper,we proposed a vision-based vehicle detection and tracking system based on a You Look Only Once version 5(YOLOv5)detector combined with a segmentation technique.The model consists of six steps.In the first step,all the extracted traffic sequence images are subjected to pre-processing to remove noise and enhance the contrast level of the images.These pre-processed images are segmented by labelling each pixel to extract the uniform regions to aid the detection phase.A single-stage detector YOLOv5 is used to detect and locate vehicles in images.Each detection was exposed to Speeded Up Robust Feature(SURF)feature extraction to track multiple vehicles.Based on this,a unique number is assigned to each vehicle to easily locate them in the succeeding image frames by extracting them using the feature-matching technique.Further,we implemented a Kalman filter to track multiple vehicles.In the end,the vehicle path is estimated by using the centroid points of the rectangular bounding box predicted by the tracking algorithm.The experimental results and comparison reveal that our proposed vehicle detection and tracking system outperformed other state-of-the-art systems.The proposed implemented system provided 94.1%detection precision for Roundabout and 96.1%detection precision for Vehicle Aerial Imaging from Drone(VAID)datasets,respectively.

Cooperative Target Tracking of Multiple Autonomous Surface Vehicles Under Switching Interaction Topologies

This paper is concerned with the cooperative target tracking of multiple autonomous surface vehicles(ASVs)under switching interaction topologies.For the target to be tracked,only its position can be measured/received by some of the ASVs,and its velocity is unavailable to all the ASVs.A distributed extended state observer taking into consideration switching topologies is designed to integrally estimate unknown target dynamics and neighboring ASVs'dynamics.Accordingly,a novel kinematic controller is designed,which takes full advantage of known information and avoids the approximation of some virtual control vectors.Moreover,a disturbance observer is presented to estimate unknown time-varying environmental disturbance.Furthermore,a distributed dynamic controller is designed to regulate the involved ASVs to cooperatively track the target.It enables each ASV to adjust its forces and moments according to the received information from its neighbors.The effectiveness of the derived results is demonstrated through cooperative target tracking performance analysis for a tracking system composed of five interacting ASVs.

Observer-Based Path Tracking Controller Design for Autonomous Ground Vehicles With Input Saturation

This paper investigates the problem of path tracking control for autonomous ground vehicles(AGVs),where the input saturation,system nonlinearities and uncertainties are considered.Firstly,the nonlinear path tracking system is formulated as a linear parameter varying(LPV)model where the variation of vehicle velocity is taken into account.Secondly,considering the noise effects on the measurement of lateral offset and heading angle,an observer-based control strategy is proposed,and by analyzing the frequency domain characteristics of the derivative of desired heading angle,a finite frequency H_∞index is proposed to attenuate the effects of the derivative of desired heading angle on path tracking error.Thirdly,sufficient conditions are derived to guarantee robust H_∞performance of the path tracking system,and the calculation of observer and controller gains is converted into solving a convex optimization problem.Finally,simulation examples verify the advantages of the control method proposed in this paper.

Adaptive saturated tracking control for solid launch vehicles in ascending based on differential inclusion stabilization

The large-range uncertainties of specific impulse,mass flow per second,aerodynamic coefficients and atmospheric density during rapid turning in solid launch vehicles(SLVs) ascending leads to the deviation of the actual trajectory from the reference one.One of the traditional trajectory tracking methods is to observe the uncertainties by Extended State Observer(ESO) and then modify the control commands.However,ESO cannot accurately estimate the uncertainties when the uncertainty ranges are large,which reduces the guidance accuracy.This paper introduces differential inclusion(DI) and designs a controller to solve the large-range parameter uncertainties problem.When above uncertainties have large ranges,it can be combined with the ascent dynamic equation and described as a DI system in the mathematical form of a set.If the DI system is stabilized,all the subsets are stabilized.Different from the traditional controllers,the parameters of the designed controller are calculated by the uncertain boundaries.Therefore,the controller can solve the problem of large-range parameter uncertainties of in ascending.Firstly,the ascent deviation system is obtained by linearization along the reference trajectory.The trajectory tracking system with engine parameters and aerodynamic uncertainties is described as an ascent DI system with respect to state deviation,which is called DI system.A DI adaptive saturation tracking controller(DIAST) is proposed to stabilize the DI system.Secondly,an improved barrier Lyapunov function(named time-varying tangent-log barrier Lyapunov function) is proposed to constrain the state deviations.Compared with traditional barrier Lyapunov function,it can dynamically adjust the boundary of deviation convergence,which improve the convergence rate and accuracy of altitude,velocity and LTIA deviation.In addition,the correction amplitudes of angle of attack(AOA) and angle of sideslip(AOS) need to be limited in order to guarantee that the overload constraint is not violated during actual flight.In this paper,a fixed time adaptive saturation compensation auxiliary system is designed to shorten the saturation time and accelerate the convergence rate,which eliminates the adverse effects caused by the saturation.Finally,it is proved that the state deviations are ultimately uniformly bounded under the action of DIAST controller.Simulation results show that the DI ascent tracking system is stabilized within the given uncertainty boundary values.The feasible bounds of uncertainty is broadened compared with Integrated Guidance and Control algorithm.Compared with Robust Gain-Scheduling Control method,the robustness to the engine parameters are greatly improved and the control variable is smoother.

Cognitive Granular-Based Path Planning and Tracking for Intelligent Vehicle with Multi-Segment Bezier Curve Stitching

Unmanned vehicles are currently facing many difficulties and challenges in improving safety performance when running in complex urban road traffic environments,such as low intelligence and poor comfort perfor-mance in the driving process.The real-time performance of vehicles and the comfort requirements of passengers in path planning and tracking control of unmanned vehicles have attracted more and more attentions.In this paper,in order to improve the real-time performance of the autonomous vehicle planning module and the comfort requirements of passengers that a local granular-based path planning method and tracking control based on multi-segment Bezier curve splicing and model predictive control theory are pro-posed.Especially,the maximum trajectory curvature satisfying ride comfort is regarded as an important constraint condition,and the corresponding curvature threshold is utilized to calculate the control points of Bezier curve.By using low-order interpolation curve splicing,the planning computation is reduced,and the real-time performance of planning is improved,com-pared with one-segment curve fitting method.Furthermore,the comfort performance of the planned path is reflected intuitively by the curvature information of the path.Finally,the effectiveness of the proposed control method is verified by the co-simulation platform built by MATLAB/Simulink and Carsim.The simulation results show that the path tracking effect of multi-segment Bezier curve fitting is better than that of high-order curve planning in terms of real-time performance and comfort.

Shadow Extraction and Elimination of Moving Vehicles for Tracking Vehicles

Shadow extraction and elimination is essential for intelligent transportation systems(ITS)in vehicle tracking application.The shadow is the source of error for vehicle detection,which causes misclassification of vehicles and a high false alarm rate in the research of vehicle counting,vehicle detection,vehicle tracking,and classification.Most of the existing research is on shadow extraction of moving vehicles in high intensity and on standard datasets,but the process of extracting shadows from moving vehicles in low light of real scenes is difficult.The real scenes of vehicles dataset are generated by self on the Vadodara–Mumbai highway during periods of poor illumination for shadow extraction of moving vehicles to address the above problem.This paper offers a robust shadow extraction of moving vehicles and its elimination for vehicle tracking.The method is distributed into two phases:In the first phase,we extract foreground regions using a mixture of Gaussian model,and then in the second phase,with the help of the Gamma correction,intensity ratio,negative transformation,and a combination of Gaussian filters,we locate and remove the shadow region from the foreground areas.Compared to the outcomes proposed method with outcomes of an existing method,the suggested method achieves an average true negative rate of above 90%,a shadow detection rate SDR(η%),and a shadow discrimination rate SDR(ξ%)of 80%.Hence,the suggested method is more appropriate for moving shadow detection in real scenes.

Dynamic Simulation of Tracked Vehicle Using the DADS Software

The track model used in the dynamic analysis and design system software is investigated. A home made tank is taken as an example to illustrate the method for modeling an integral tracked vehicle and perform the dynamic simulation. The obtained results have demonstrated that the simulation method has the advantage of high efficiency, more convenience and more insight into the dynamical behavior of the system.

Vehicle recognition and tracking based on simulated annealing chaotic particle swarm optimization-Gauss particle filter algorithm

Target recognition and tracking is an important research filed in the surveillance industry.Traditional target recognition and tracking is to track moving objects, however, for the detected moving objects the specific content can not be determined.In this paper, a multi-target vehicle recognition and tracking algorithm based on YOLO v5 network architecture is proposed.The specific content of moving objects are identified by the network architecture, furthermore, the simulated annealing chaotic mechanism is embedded in particle swarm optimization-Gauss particle filter algorithm.The proposed simulated annealing chaotic particle swarm optimization-Gauss particle filter algorithm(SA-CPSO-GPF) is used to track moving objects.The experiment shows that the algorithm has a good tracking effect for the vehicle in the monitoring range.The root mean square error(RMSE), running time and accuracy of the proposed method are superior to traditional methods.The proposed algorithm has very good application value.

NONLINEAR ESTIMATION METHODS FOR AUTONOMOUS TRACKED VEHICLE WITH SLIP

In order to achieve precise,robust autonomous guidance and control of a tracked vehicle,a kinematic model with longitudinal and lateral slip is established,Four different nonlinear filters are used to estimate both state vector and time-varying parameter vector of the created model jointly.The first filter is the well-known extended Kalman filter.The second filter is an unscented version of the Kalman filter.The third one is a particle filter using the unscented Kalman filter to generate the importance proposal distribution.The last one is a novel and guaranteed filter that uses a linear set-membership estimator and can give an ellipsoid set in which the true state lies.The four different approaches have different complexities,behavior and advantages that are surveyed and compared.

A Study on the Dynamic Analysis of A Tracked Vehicle for Ocean Mining on the Deep Seabed

A study is presented on the dynamic analysis of a tracked vehicle for mining on the deep seabed of very soft soil. Equations for the interaction between the track and extremely soft seabed are employed to develop a track/soil interaction module called TVAS. The vehicle is modeled as a multibody dynamic system by the use of a multibody dynamic analysis program. The module developed is cooperated with the multibody dynamic analysis program with a user-defined subroutine. The dynamic behavior and the conceptual design of the mining vehicle on the deep seabed are investigated.

Study on Steering Control Strategy for High-Speed Tracked Vehicle with Hydrostatic Drive

Steering control strategy for high-speed tracked vehicle with hydrostatic drive is designed based on analyzing the fundamental steering theories of the hydrostatic drive tracked vehicle. The strategy is completed by the cooperation between integrated steering control unit and pump ＆ motor displacement controller. The steering simulation is conducted by using Simulink of Matlab. It is indicated that this steering control strategy can reduce the average vehicle speed automatically to achieve the driver＇s expected steering radius exactly in the case of en- suring not exceeding the system pressure threshold and no sideslip.

Turning traction force of tracked mining vehicle based on rheological property of deep-sea sediment

Based on main physical and mechanical properties of deep-sea sediment from C-C poly-metallic nodule mining area in the Pacific Ocean, the best sediment simulant was successfully prepared by mixing bentonite with a certain content of water. Compression-shear coupling rheological constitutive model of the sediment simulant was established by endochronic theory and the coupling rheological parameters were obtained by compressive and compression-shear creep tests. A new calculation formula of turning traction force of the tracked mining vehicle was first derived based on the coupling rheological model and consideration of pushing resistance and sinkage of the tracked mining vehicle. Effects of the turning velocity, crawler spacing and contacting length of crawler with deep-sea sediment on the turning traction force were analyzed. Research results can provide theoretical foundation for operation safety and optimal design of the tracked mining vehicle.

Predicting the sinkage of a moving tracked mining vehicle using a new rheological formulation for soft deep-sea sediment

The sinkage of a moving tracked mining vehicle is greatly af fected by the combined compression-shear rheological properties of soft deep-sea sediments. For test purposes, the best sediment simulant is prepared based on soft deep-sea sediment from a C-C poly-metallic nodule mining area in the Pacific Ocean. Compressive creep tests and shear creep tests are combined to obtain compressive and shear rheological parameters to establish a combined compressive-shear rheological constitutive model and a compression-sinkage rheological constitutive model. The combined compression-shear rheological sinkage of the tracked mining vehicle at dif ferent speeds is calculated using the Recur Dyn software with a selfprogrammed subroutine to implement the combined compression-shear rheological constitutive model. The model results are compared with shear rheological sinkage and ordinary sinkage(without consideration of rheological properties). These results show that the combined compression-shear rheological constitutive model must be taken into account when calculating the sinkage of a tracked mining vehicle. The combined compression-shear rheological sinkage decrease with vehicle speed and is the largest among the three types of sinkage. The developed subroutine in the Recur Dyn software can be used to study the performance and structural optimization of moving tracked mining vehicles.

Configuration design and control of hybrid tracked vehicle with three planetary gear sets

The hybrid tracked vehicles(HTV)usually adopt series hybrid powertrain with extra steering mechanism,which has relatively low transmission efficiency and reduces the flexibility of structural arrangement.To overcome the disadvantages,a new kind of single-mode powertrain has been proposed.The power-split hybrid powertrain is composed of three planetary gear(PG)sets connected to one engine,left and right track outputs,and three motors.The proposed powertrain can realize steering while going forward by controlling the output torque on each side without extra steering mechanism or steering shaft.Due to the diversity of the connection way between components and planetary gear sets,a rapid configuration design approach is proposed for the design selection of HTV.The automated dynamic modelling method can show the one-to-one correspondence with the selected feasible groups by establishing two characteristic matrices,which is more simple than other researches.The analytically-based method is proposed to classify all possible connection designs into several groups to decrease the searching scope with improved design efficiency.Finally,the optimal control strategy is used to find the design with optimal fuel economy under typical condition of HTV.The case study is implemented by the proposed design approach which demonstrates better design performances compared with the existing series-hybrid HTV.

Modeling and Simulation of Adaptive Surface Tracked Vehicle Based on RecurDyn

In order to improve the adaptability of the tracked vehicle in the road and strengthen the grip of the tracked vehicle, a track surface adaptive mechanism was provided. In theory, it has been proved practically. Meanwhile, RecurDyn, which is a multi-body kinematics software, was used to build a multi-body soft hybrid model, based on structure, elasticity, linear damping adaptive tracked vehicle;meanwhile the model was used to carry on the kinematics simulation. Through the comparison between simulated motion trail and that of traditional motion trail, this paper analyzed the deviation of the motion trail and also simulated the motion trail of the warped surface so as to test the adaptive ability of the mechanism. According to the results, the adaptive mechanism was equipped with great surface adaptability. It can also adapt to the complex warped surface, and enjoy a damping effect.