A comparison of ground vehicle mobility analysis based on soil moisture time series datasets from WindSat,LIS, and in situ sensors

Soil moisture is a key terrain variable in ground vehicle off-road mobility. Historically, models of the land water balance have been used to estimate soil moisture. Recently, satellites have provided another source of soil moisture estimates that can be used to estimate soil-limited vehicle mobility. In this study, we compared the off-road vehicle mobility estimates based on three soil moisture sources: WindSat (a satellite source), LIS (a computer model source), and in situ ground sensors (to represent ground truth). Mobility of six vehicles, each with different ranges of sensitivity to soil moisture, was examined in three test sites. The results demonstrated that the effect of the soil moisture error on mobility predictions is complex and may produce very significant errors in off-road mobility analysis for certain combinations of vehicles, seasons, and climates. This is because soil moisture biases vary in both direction and magnitude with season and location. Furthermore, vehicles are sensitive to different ranges of soil moistures. Modeled vehicle speeds in the dry time periods were limited by the interaction between soil traction and the vehicles’ powertrain characteristics. In the wet season, differences in soil strength resulted in more significant differences in mobility predictions.     

Use of military training doctrine to predict patterns of maneuver disturbance on the landscape. I. Theory and methodology

Modern-day military maneuvers, involving tactical formations of wheeled and tracked vehicles, can have significant physical and environmental impacts on the landscape. Numerous scientific studies of these impacts have been conducted, most notably the post-impact assessments of General Patton’s tank maneuvers of the early 1940s in the Mojave Desert of California and Arizona. On a smaller scale, numerous studies of military vehicle impacts have been conducted on military training lands throughout the United States, Canada and Europe. These studies have used a variety of measurement techniques, to include ground level photography and in situ measurements, aerial photography, satellite imagery and vehicle-mounted global positioning systems (GPS) data to define the footprint, patterns and magnitude of disturbances on the landscape. These disturbances are highly variable and can occur over tens of thousands of acres. Because scientists and land managers are generally not familiar with military decision-making, tactical doctrine, and vehicle–weapons systems capabilities, it is difficult for them to predict patterns of disturbance a priori. Even during post-event impact analysis, a full understanding of why and how maneuver disturbance patterns occur may not be readily apparent to them. This limitation can preclude knowledgeable planning, design and repair of damaged lands. In this case study, military tacticians and physical scientists developed an integrated methodology to predict these disturbance patterns more explicitly. The goal of the study was to provide land managers with a tool for understanding how these patterns evolve, and in turn, allow them to better plan and design mitigation efforts to sustain the landscape. The methodology combines a military terrain analysis technique, the modified combined obstacle overlay (MCOO), with an applied military tactics filter to predict where vehicle impacts would be most likely. A terrain and tactical analysis of the landscape at the Combat Maneuver Training Center-Live Fire (CMTC-LF) Area at the US Army Grafenwöhr Training Area, Germany, was conducted using maps, digital ortho-photography, spatial data and on-site reconnaissance to determine the tactical footprint and potential disturbance patterns caused by a new training mission. Part I of this study describes the background, theory and approach used to develop the methodology. Part II describes the field-based validation of the methodology, using post-maneuver ground observations and sampling to test the methodology’s predictions.     

Multipass coefficients for terrain impacts based on military vehicle type,size and dynamic operating properties

Quantification of multipass vehicle impacts is needed to determine terrain disturbance during military training. This study, conducted at Fort Riley, Kansas on a clay loam soil, evaluated the multipass terrain impacts of four military vehicles: the M1A1 Main Battle Tank, M998 HMMWV, M985 HEMTT, and M113 APC. Disturbed width and impact severity were assessed along 14 spirals subjected to a maximum of eight passes for a total of 696 impact points. Project goals included evaluating vegetation impacts by tracked and wheeled military vehicles across multiple passes in order to develop coefficients allowing more accurate predictive modeling of vehicle multipass impacts. Multiple passes produce increased vegetative impacts, with multipass coefficients (MPC) ranging from 0.98 to 4.44 depending on vehicle type, size and turn severity. Tracked vehicles were found to have a higher multipass coefficient than wheeled vehicles, with multipass coefficients increasing with vehicle weight and the sharpness of turns. The components of a more theoretical and universal multipass vehicle impact model are discussed. Understanding multipass dynamics will allow land managers to determine the extent and severity of terrain impacts on military training areas and quickly evaluate vehicle environmental impacts when used in conjunction with a GPS-based vehicle tracking system (VTS).     

Agile tire slippage dynamics for radical enhancement of vehicle mobility

There is a need to radically increase mobility of terrain vehicles through new modalities of vehicle locomotion, i.e., by establishing a new technological paradigm in vehicle dynamics and mobility. The new paradigm greatly applies to military vehicles for the radical improvement of tactical and operational mobility. This article presents a new technological paradigm of agile tire slippage dynamics that is studied as an extremely fast and exact response of the tire–soil couple to (i) the tire dynamic loading, (ii) transient changes of gripping and rolling resistance conditions on uniform stochastic terrains and (iii) rapid transient changes from one uniform terrain to a different uniform terrain. Tire longitudinal relaxation lengths are analyzed to characterize the longitudinal relaxation time constants. A set of agile characteristics is also considered to analyze agile tire slippage dynamics within a time interval that is close to the tire longitudinal relaxation time constants. The presented paradigm of agile tire slippage dynamics lays out a foundation to radically enhance vehicle terrain mobility by controlling the tire slippage in its transient phases to prevent the immobilization of a vehicle. Control development basis and requirements for implementing an agile tire slippage control are also analyzed and considered.     

Validation of the GeoWATCH soil moisture model and proposed bias correction method

The US Army is required to be a good steward of the land per US Army regulation AR 200-1. Based on this regulation, Army installations need to manage lands, to reduce potential damage and impacts to water quality and habitat that may occur from training. Maneuver training does impact the vegetation and soil and this damage is directly related to soil moisture. Soil moisture is an important factor for understanding the potential for soil surface disturbance due to vehicle impacts and predicting soil resilience to vehicle traffic, however, producing accurate estimates of the spatial and temporal variation of soil moisture has historically been elusive. GeoWATCH, which stands for Geospatial Weather-Affected Terrain Conditions and Hazards (formerly DASSP), simulates soil moisture world-wide, at relatively small spatial and temporal scales. GeoWATCH uses a physics-based downscaling approach that uses weather-scale land surface model estimates of soil moisture and land surface water and energy fluxes, with high resolution geospatial data. GeoWATCH soil moisture outputs coupled with vehicle impact models, are anticipated to be useful for near-real-time estimation of ground disturbance, but will require ground validation. To validate GeoWATCH soil moisture estimates, we utilized Soil Climate Analysis Network (SCAN) gauge network soil moisture data from 127 sites across 34 states. Statistical analysis of the raw GeoWATCH output indicated the model performs statistically better in certain soil textures. Model bias is largest for sandy soils, whereas clayey soils were least biased. As a result, bias correction models were applied to the raw GeoWATCH simulated values using linear regression to predict correction factor (CF) values based on physical site characteristics. The bias correction models significantly improved the performance of the GeoWATCH soil moisture model in terms of average performance statistics and number of statistically cally unbiased sites. This process could easily be incorporated into GeoWATCH, allowing for a capability to rapidly estimate vehicle impacts and determine rehabilitation requirements by installation land managers.     

Predicting terrain parameters for physics-based vehicle mobility models from cone index data

To provide terrain data for the development of physics-based vehicle mobility models, such as the Next Generation NATO Reference Mobility Model, there is a desire to make use of the vast amount of cone index (CI) data available. The challenge is whether the terrain parameters for physics-based vehicle mobility models can be predicted from CI data. An improved model for cone-terrain interaction has been developed that takes into account both normal pressure and shear stress distributions on the cone-terrain interface. A methodology based on Derivative-Free Optimization Algorithms (DFOA) has been developed in combination with the improved model to make use of continuously measured CI vs. sinkage data for predicting the three Bekker pressure-sinkage parameters, k_c, k_ϕ and n, and two cone-terrain shear strength parameters, c_c and ϕ_c. The methodology has been demonstrated on two types of soil, LETE sand and Keweenaw Research Center (KRC) soils, where continuous CI vs. sinkage measurements and continuous plate pressure vs. sinkage measurements are available. The correlations between the predicted pressure-sinkage relationships based on the parameters derived from continuous CI vs. sinkage measurements using the DFOA-based methodology and that measured were generally encouraging.     

Efficient generation of accurate mobility maps using machine learning algorithms

U.S Army’s mission is to develop, integrate, and sustain the right technology solutions for all manned and unmanned ground vehicles, and mobility is a key requirement for all ground vehicles. Mobility focuses on ground vehicles’ capabilities that enable them to be deployable worldwide, operationally mobile in all environments, and protected from symmetrical and asymmetrical threats. In order for military ground vehicles to operate in any combat zone, the planners require a mobility map that gives the maximum predicted speeds on these off-road terrains. In the past, empirical and semi-empirical techniques (Ahlvin and Haley, 1992; Haley et al., 1979) were used to predict vehicle mobility on off-road terrains such as the NATO Reference Mobility Model (NRMM). Because of its empirical nature, the NRMM method cannot be extrapolated to new vehicle designs containing advanced technologies, nor can it be applied to lightweight robotic vehicles.The mobility map is a function of different parameters such as terrain topology and profile, soil type (mud, snow, sand, etc.), vegetation, obstacles, weather conditions, and vehicle type and characteristics.A physics-based method such as the discrete element method (DEM) (Dasch et al., 2016) was identified by the NATO Next Generation NRMM Team as a potential high fidelity method to model the soil. This method allows the capture of the soil deformation as well as its non-linear behavior. Hence it allows the simulation of the vehicle on any off-road terrain and have an accurate mobility map generated. The drawback of the DEM method is the required simulation time. It takes several weeks to generate the mobility map because of the large number of soil particles (millions) even while utilizing high performance computing.One approach to reduce the computational time is to use machine learning algorithms to predict the mobility map. Machine learning (Boutell et al., 2004; Burges, 1998; Barber et al., 1997) can lead to very accurate mobility predictions over a wide range of terrains. Machine learning is divided into two categories: the supervised and the unsupervised learning. Supervised learning requires the training data to be labeled into predetermined classes, while the unsupervised learning does not require the training data to be labeled. Machine learning can help generate mobility maps using trained models created from a minimum number of simulation runs. In this study different supervised machine learning algorithms such as the support vector machine (SVM), the nearest neighbor classifier (k-NN), decision trees, and boosting methods were used to create trained models labeled as 2 classes for the ‘go/no-go’ map, 5 classes for the 5-speed map, and 7 classes for the 7-speed map. The trained models were created from the physics-based simulation runs of a nominal wheeled vehicle traversing on a cohesive soil.     

Next-generation NATO reference mobility model complex terramechanics – Part 1: Definition and literature review

The US army along with NATO member and partner nations’ militaries need an accurate software tool for predicting ground vehicle mobility (such as speed-made-good and fuel-consumption) on world-wide terrains where military vehicles may be required to operate. Currently, the NATO Reference Mobility Model (NRMM) is the only NATO recognized tool for assessing ground vehicle mobility. NRMM was developed from the 1960s to the 1980s and relies on steady-state empirical formulas which may not be accurate for new military ground vehicles. A NATO research task group (RTG-248) was established from 2016 to 2018 to develop the NG-NRMM (next-generation NRMM) software tool requirements and an NG-NRMM prototype which uses high-fidelity “simple” or “complex” terramechanics models for the terrain/soil along with modern 3D multibody dynamics software tools for modeling the vehicle. NG-NRMM Complex Terramechanics (CT) models are those that utilize full 3D soil models capable of predicting the 3D soil reaction forces on the vehicle surfaces (including tires, tracks, legs, and under body) and the 3D flow and deformation of the soil including both elastic and plastic deformation under any 3D loading condition. In Part 1 of this paper, an overview of the full spectrum of terramechanics models from the highest fidelity to the lowest fidelity is presented along with a literature review of CT ground vehicle mobility models.     

地面力学及其在行星探测研究中的应用

地面力学是研究越野行驶中机器与地面相互作用的一门力学学科,包括对机器通过性的预测和评价,行走机构的优化设计以及对地面可行驶性的预测判断等几个方面.首先简介地面力学的研究方法、试验仪器和设备以及主要的成果和结论,其中包括在这些方面的最新研究进展情况.之后重点介绍行星探测领域中所开展的地面力学研究,主要从行星探测器设计阶段对地面力学理论和方法的应用、行星模拟土壤研制和力学特性研究、行星就位土壤力学参数测量等几个方面进行了综述.最后对这一领域今后的研究方向进行了探讨.      

A high-fidelity approach for vehicle mobility simulation: Nonlinear finite element tires operating on granular material

Assessing the mobility of off-road vehicles is a complex task that most often falls back on semi-empirical approaches to quantifying the vehicle–terrain interaction. Herein, we concentrate on physics-based methodologies for wheeled vehicle mobility that factor in both tire flexibility and terrain deformation within a fully three-dimensional multibody system approach. We represent the tire based on the absolute nodal coordinate formulation (ANCF), a nonlinear finite element approach that captures multi-layered, orthotropic shell elements constrained to the wheel rim. The soil is modeled as a collection of discrete elements that interact through contact, friction, and cohesive forces. The resulting vehicle/tire/terrain interaction problem has several millions of degrees of freedom and is solved in an explicit co-simulation framework, built upon and now available in the open-source multi-physics package Chrono. The co-simulation infrastructure is developed using a Message Passing Interface (MPI) layer for inter-system communication and synchronization, with additional parallelism leveraged through a shared-memory paradigm. The formulation and software framework presented in this investigation are proposed for the analysis of the dynamics of off-road wheeled vehicle mobility. Its application is demonstrated by numerical sensitivity studies on available drawbar pull, terrain resistance, and sinkage with respect to parameters such as tire inflation pressure and soil cohesion. The influence of a rigid tire assumption on mobility is also discussed.     

Cross-country mobility on various snow conditions for validation of a virtual terrain

Realistic simulation of on- and off-road vehicle performance in all weather conditions is needed by the U.S. Army for virtual training of personnel on existing vehicles, and for new vehicle design. The virtual test site is a computer simulation representing an actual terrain defined as having spatially distributed terramechanics properties and terrain interaction with vehicles. We developed a virtual test site for Ethan Allen Firing Range (EAFR) in northern Vermont. The virtual test site for EAFR is composed of terramechanics properties including spatially distributed snow depth and density, soil type, drainage class, slope, and vegetation type. Snow depth and density were spatially distributed with regard to elevation, slope, and aspect using a surface energy balance approach. This paper evaluates whether the terramechanics representation of a virtual test site is improved by adding spatially distributed snow and soil properties, rather than using uniform properties. The evaluation was accomplished by conducting a cross-country vehicle performance analysis using the North Atlantic Treaty Organization (NATO) Reference Mobility Model (NRMM) to validate the new algorithms for realistic spatial distribution of snow properties. The results showed that the percentage of No-Go areas for uniform snow is lower than the distributed snow by 4% for the CIV (CRREL Instrumented Vehicle), 8% for the HMMWV (High Mobility Multipurpose Wheeled Vehicle), and 5% for the Stryker vehicle. For both light vehicles, approximately 12% of the No-Go areas are classified as such because of slopes 29%. These results imply that spatial distribution of snow properties provides realistic vehicle response as opposed to having the snow properties distributed uniformly throughout the entire terrain. This represents an improvement over previous versions of the terramechanics properties.     

Mobility analysis of off-road vehicles: Benefits for development, procurement and operation

Nowadays the requirements on off-road vehicles are rising steadily. The ideal vehicle has to provide excellent off-road capability with low fuel consumption, offer a high customizability for each specific mission and, last but not least, it has to be easy to operate. To meet these demands, on the development side a lot of parameter studies have to be carried out. The customer has to compare offers from a multiplicity of suppliers to decide which vehicle fulfills the designated mission task best. And finally, the operator needs the best training on the vehicle to cope with all possible situations in off-road mobility. In response to these needs, the presented simulation program WinMaku was developed to offer a tool to facilitate development, procurement and operator training. Exemplary simulation results show, on the one hand, the influence of specific design parameters, e.g. tire size, engine power, torque characteristics, gear shifting, and engine working conditions, and on the other hand the (beneficial or adverse) effects of operational parameters like driving with maximum/partial engine load, gear selection, engine speed, tire inflation pressure or track tension, on mobility performance. Furthermore results of vehicle comparison analysis are presented. These types of analysis show comparisons of mobility performance of different vehicle types or vehicle concepts (e.g. wheel vs. track) in fulfilling a certain mission profile, characterized by passing a sequence of different soils with various inclines. Endowed with such capability, the presented simulation tool serves as a training tool for operators, provides a cost effective method to assess possible development steps, allows customers to run a pre-selection process prior to expensive and time-consuming field tests, and finally supports mission planning by providing data like expected fuel consumption or time needed to pass a certain mission profile.     

Analysis of vehicle platoon movement and speed-spacing relationships during military exercises

In this study a method that identifies off-road vehicle column movement was developed and evaluated. Previous studies have revealed that multiple vehicle passes produce detrimental soil and terrain impacts. Identifying the frequency and location of this type of multi-pass impact during military maneuvers is difficult. This method will aid in the assessment of environmental impacts of off-road military vehicles by allowing land managers to characterize vehicle movement patterns, especially column movement, at military training installations during maneuvers. GPS units mounted on military vehicles collected on and off-road tracking data during a reconnaissance maneuver at Fort Lewis Military Installation, Washington. A set of data utilizing a Stryker platoon of four vehicles was used to evaluate this method. The GPS coordinates, speed, and direction of travel of each vehicle was collected at each second. A criteria to identify platoon column movement was developed based on vehicle proximity, speed and direction of travel. The results of this study show that the method can correctly identify off-road column movement for the purpose of evaluating the multi-pass impacts on the terrain. In addition, using this approach the vehicle movement patterns associated with on- and off-road platoon movement (i.e. vehicle speeds and spacing) were evaluated.     

Quantifying vegetation biomass impacts on vehicle mobility

Soil impacts on vehicle mobility are well known; however, most data are for bare soil or the type and amount of vegetation is not documented. This study summarizes results from experiments to quantify the effect of above ground and below ground vegetation biomass on vehicle performance. Soil–vegetation combinations of three soils and three grasses were used. The vegetation was tested at various growth stages and was also subjected to stressors such as trafficking, burning, and cutting. Vegetation measurements included above ground (leaves and shoots) and below ground (root) biomass weights, lengths, diameters and surface area parameters. The soils were characterized for size distribution, moisture, density and terrain strength for each test condition. Vehicle traction and motion resistance were measured for each soil–grass combination using the CRREL Instrumented Vehicle. Results showed an increase in net traction biomass in sandy soils. For clay soils above ground biomass generally increased resistance while increased root diameter clearly decreased resistance. This study represents the first measurements quantifying the impacts of specific biomass parameters on vehicle mobility. The results will serve to guide new experimental methods, improve datasets, and develop physics-based models for years to come.     

An overview of methods to convert cone index to bevameter parameters

This paper reviews experimental methods for the conversion of cone index measurements to bevameter parameters in support of vehicle soil/tire/track interactions for two general soil types, sand and lean clay. The accurate prediction of traction, motion resistance, and sinkage of tire/tracks off-road requires estimates of soil strength. Equipment used in the measurement of soil strength to support predictions of off-road mobility include the bevameter and the cone penetrometer. The portability of the cone penetrometer and rapid estimates of spatial/temporal variability in all terrain conditions make it an invaluable tool. The bevameter, a less portable tool, is used for the mechanical analysis of soils. The bevameter measures parameters defining soil strength in terms of cohesive modulus of soil deformation (k_c), frictional modulus of soil deformation (k_φ), exponent of soil sinkage (n), cohesion (c), angle of internal friction (φ), and the plate pressure at 1 in. (2.54 cm) of penetration (K) (Bekker, 1969). The field of terramechanics would greatly benefit from having the ability to convert cone penetrometer data in areas where bevameter parameters are difficult to collect. That ability to convert from cone index to bevameter parameters could be used for the large sets of existing cone index data to support determination of traction and motion resistance. This paper examines those methods for converting cone index to bevameter plate penetration parameters k_c, k_φ, and n.     

A methodology for quantitatively assessing vehicular rutting on terrains

This paper presents a quantitative method for assessing the environmental impact of terrain/vehicle interactions during tactical missions. Area wide mobility analyses were conducted using three standard US military tracked and wheeled vehicles over terrain regions representing both fine-grained and course-grained soils. The NATO reference mobility model, Version 2, was used to perform the on- and off-road mobility analysis. Vehicle and terrain characterizations along with different climate scenarios were used as input parameters to predict vehicle rut depth performance for the different vehicles and terrain conditions. The vehicles’ performance was statistically mapped over these terrain regions for percent area traveled and the resulting rut depth created by each vehicle. A selection of tactical scenarios for each vehicle was used to determine rut depth for a range of vehicle missions. A vehicle mission severity rating method, developed at the US Army Engineer Research and Development Center, was used to rate the selected missions and resulting rut depths.     

On vehicle mobility in snow-covered terrain — 1. Problem development and requirements for analysis

The problem of evaluation and prediction of vehicle mobility on snow-covered terrain needs to be studied not on the basis of application of direct technology transfer from vehicle mobility on soil, but on the basis of new perspectives on material (snowpack) properties and response performance. The complexities of snow identification and classification, arising from local environmental control and thermodynamic history, render analogies between snow and soil inapplicable. In addition, it is significant to note that in snow trafficability considerations, the first pass is the worst pass.     

Experimental validation of a differential variational inequality-based approach for handling friction and contact in vehicle/granular-terrain interaction

The observation motivating this contribution was a perceived lack of expeditious deformable terrain models that can match in mobility analysis studies the level of fidelity delivered by today’s vehicle models. Typically, the deformable terrain-tire interaction has been modeled using Finite Element Method (FEM), which continues to require prohibitively long analysis times owing to the complexity of soil behavior. Recent attempts to model deformable terrain have resorted to the use of the Discrete Element Method (DEM) to capture the soil’s complex interaction with a wheeled vehicle. We assess herein a DEM approach that employs a complementarity condition to enforce non-penetration between colliding rigid bodies that make up the deformable terrain. To this end, we consider three standard terramechanics experiments: direct shear, pressure-sinkage, and single-wheel tests. We report on the validation of the complementarity form of contact dynamics with friction, assess the potential of the DEM-based exploration of fundamental phenomena in terramechanics, and identify numerical solution challenges associated with solving large-scale, quadratic optimization problems with conic constraints.     

Torque distribution influence on tractive efficiency and mobility of off-road wheeled vehicles

Off-road vehicle performance is strongly influenced by the tire-terrain interaction mechanism. Soft soil reduces traction and significantly modifies vehicle handling; therefore tire dynamics plays a strong role in off-road mobility evaluation and needs to be addressed with ad-hoc models. Starting from a semi-empirical tire model based on Bekker–Wong theory, this paper, analyzes the performance of a large four wheeled vehicle driving on deformable terrain. A 14 degree of freedom vehicle model is implemented in order to investigate the influence of torque distribution on tractive efficiency through the simulation of front, rear, and all wheel drive configuration. Results show that optimal performance, regardless vertical load distribution, is achieved when torque is biased toward the rear axle. This suggests that it is possible to improve tractive efficiency without sacrificing traction and mobility. Vehicle motion is simulated over dry sand, moist loam, flat terrain and inclined terrain.     

Finite element modeling of tire/terrain interaction: Application to predicting soil compaction and tire mobility

Tire/terrain interaction has been an important research topic in terramechanics. For off-road vehicle design, good tire mobility and little compaction on terrain are always strongly desired. These two issues were always investigated based on empirical approaches or testing methods. Finite element modeling of tire/terrain interaction seems a good approach, but the capability of the finite element has not well demonstrated. In this paper, the fundamental formulations on modeling soil compaction and tire mobility issues are further introduced. The Drucker-Prager/Cap model implemented in ABAQUS is used to model the soil compaction. A user subroutine for finite strain hyperelasticity model is developed to model nearly incompressible rubber material for tire. In order to predict transient spatial density, large deformation finite element formulation is used to capture the configuration change, which combines with soil elastoplastic model to calculate the transient spatial density due to tire compaction on terrain. Representative simulations are provided to demonstrate how the tire/terrain interaction model can be used to predict soil compaction and tire mobility in the field of terramechanics.