Starting a few decades ago, the unmanned wheeled vehicle research has drawn lately more attention, especially for off-road environment. As the demand to use electric vehicles increased, the need to conceptualize the use of electrically driven vehicles in autonomous operations became a target. That is because in addition to the fact that they are more environmentally friendly, they are also easier to control. This also gives another reason to enhance further the energy economy of those unmanned electric vehicles. Off-road vehicles research was always challenging, but in the present work the nature of the off-road land is utilized to benefit from in order to enhance the energy consumption of those vehicles. An algorithm for energy consumption optimization for electrically driven unmanned wheeled vehicles is presented. The algorithm idea is based on the fact that in off-road conditions, when the vehicle passes a ditch or a hole, the kinetic energy gained while moving downhill could be utilized to reduce the energy consumption for moving uphill if the dimensions of the ditch/hole were known a distance ahead. Two manipulated variables are evaluated: the wheels DC motors supply voltage and the DC armature current. The developed algorithm is analysed and compared to the PID speed iii controller and to the open-loop control of DC motors. The developed predictive controller achieved encouraging results compared to the PID speed control and also compared to the open-loop control. Also, the use of the DC armature current as a manipulated variable showed more noticeable improvement over using the DC input voltage. Experimental work was carried out to validate the predictive control algorithm. A mobile robot with two DC motor driven wheels was deployed to overcome a ditch-like hindrance. The experimental results verified the simulation results. A parametric study for the predictive control is conducted. The effect of changing the downhill angle and the uphill angle as well as the size of the prediction horizon on the consumed electric energy by the DC motors is addressed. The simulation results showed that, when using the proposed approach, the larger the prediction horizon, the lower the energy consumption is.

A ground vehicle is a dynamic system containing many non-linear components, ranging from the non-linear engine response to the tyre-road interface. In pursuit of developing driver-assist systems for accident avoidance, as well as fully autonomous vehicles, the application of modern mechatronics systems to vehicles are widely investigated. Extensive work has been done in an attempt to model and control the lateral response of the vehicle system utilising a wide variety of conventional control and intelligent systems theory. The majority of driver models are however intended for low speed applications where the vehicle dynamics are fairly linear. This study proposes the use of adaptive control strategies as robust driver models capable of steering the vehicle without explicit knowledge of vehicle parameters. A Model Predictive Controller (MPC), self-tuning regulator and Linear Quadratic Self-Tuning Regulator (LQSTR) updated through the use of an Auto Regression with eXogenous input (ARX) model that describes the relation between the vehicle steering angle and yaw rate are considered as solutions. The strategies are evaluated by performing a double lane change in simulation using a validated full vehicle model in MSC ADAMS and comparing the maximum stable speed and lateral offset from the required path. It is found that all the adaptive controllers are able to successfully steer the vehicle through the manoeuvre with no prior knowledge of the vehicle parameters. An LQSTR proves to be the best adaptive strategy for driver model applications, delivering a stable response well into the non-linear tyre force regime. This controller is implemented on a fully instrumented Land Rover 110 of the Vehicle Dynamics Group at the University of Pretoria fitted with a semi-active spring-damper suspension that can be switched between two discrete setting representing opposite extremes of the desired response namely: ride mode (soft spring and low damping) and handling mode (stiff spring and high damping). The controller yields a stable response through a severe double lane change (DLC) up to the handling limit of the vehicle, safely completing the DLC at a maximum speed of 90 km/h all suspension configurations. The LQSTR also proves to be robust by following the same path for all suspension configurations through the manoeuvre for vehicle speeds up to 75 km/h. Validation is continued by successfully navigating the Gerotek dynamic handling track, as well as by performing a DLC manoeuvre on an off-road terrain. The study successfully developed and validated a driver model that is robust against variations in vehicle parameters and friction coefficients. / Dissertation (MEng)--University of Pretoria, 2015. / Mechanical and Aeronautical Engineering / Unrestricted

The diploma thesis focuses on impact of construction position and its impact on price of off-road transport. One of the main aims of the thesis is to assess influence of location of construction on its price and cost. Furthermore, the work aims at creating optimal procedure for processing information obtained from the budget. The diploma thesis is divided into two parts. In the theoretical part are described themes related to the given topic and in the practical part the obtained data are analyzed and subsequently processed

Eco-tourism activities specifically, sometimes have very negative environmental impacts. One such activity which has been observed to have severe negative impacts is driving in dirt tracks (ungravelled natural soil) by game drive vehicles in private game reserves and some National Parks (Nortjé 2005; Laker 2009). It has also been observed that the severity of the impacts and the resilience (recovery potential) of the affected areas differ widely between different areas. It is strongly linked to the properties and qualities of different soils. This study has shown that off-road driving (ORD) has the same effects, and to a greater extent, if it is not well managed and judiciously controlled. Wild animals tend to concentrate in areas with the most nutritious en most palatable vegetation. Consequently these are also the areas where predators, e.g. lion, leopard and cheetah are most likely to be found. It can be expected that these will be the areas with the highest frequencies of ORD in order to get close to these animals. In many landscapes these are the areas which are the most vulnerable to negative impacts by actions like ORD and have the lowest resilience. It has also been observed during game drives and personal communications at several occasions that there is tremendous ignorance amongst tourists regarding the negative environmental impacts of certain activities. This study proved that ORD have strong negative impacts on vegetation recovery, soil resilience and root density distribution through soil crusting and sub-soil compaction. An important finding is that these negative impacts are during both dry and wet soil conditions. Game drive vehicles driving off-road damages the surface soil structure, which lead to soil crust formation and sub-surface compaction. A highly significant result is that most crusting and sub-soil compaction occurred during the first pass of the game drive vehicle, irrespective of the soil type and tyre pressure, thus rewriting the current guidelines for ORD of the South African National Parks, SANParks. Furthermore, results of this study indicated that a significant area in the flood plains of the Makuleke Contractual Park is impacted by ORD. The impacts are serious if one looks at the amount of land that an ORD vehicle can disturb. One of the recommendations would thus be to drive in the same tracks when driving off-road, and lower the tyre pressures. Driving in the same tracks is known as "controlled-traffic" in the agricultural industry. Controlled traffic is very important to minimize compaction. Driving in the same University of Pretoria etd Nortjé, G.P. (2013) tracks during off-road incidents does not significantly affect the degree of compaction under the tracks, but greatly reduces the compacted area. Further results indicated a strong lateral effect of the vehicle tracks, in most cases the whole area between the two tyre tracks as well as up to a distance outside of the vehicle tracks, thus increasing the total area disturbed by ORD. Comparing these vehicle impacts with animal path resulted in some important findings. Animals only caused a soil crust with soil strength values much lower than that of vehicles. The effects of animals are also much more vertical than lateral as with vehicles. Another important finding is the role that historical human activities play in such study areas and how it may influence results. The results in this study are aggravated by the historical human activities in this study area, as indicated. These historical activities were the main cause of the surface crusting, and the resultant low vegetation growth in the area. This, therefore, explains partially the relatively high control values and also the soil’s higher susceptibility to compaction due to vehicle ORD. The root density trials had very interesting and important results. Significant differences occurred between mean root density fractions across all tyre pressures at all three trial sites. The trend is that an increase in tyre pressure causes a decrease in root density distribution. These results show clearly that even lower tyre pressures are harmful, but are more environmental friendly than higher tyre pressures. Results of the second part of the study with regards to tourists' perceptions on ORD, and the impact of their activities on the environment, showed that the majority of tourists areignorant when it comes to the impacts of their activities on soil and vegetation. Tourists' had significantly variable demographic characteristics. Tourists' environmental perceptions varied, but a significant majority of tourists agreed that ORD has a negative impact on the environment. Contradictions exist between what they know or perceive as being damaging and what they prefer to act on. Results indicate a need for improved visitor education on the possible negative impacts of demands for ORD, and a need for government intervention with regards to the enforcement of legal measures to control ORD. The results also indicate that game guides and tourism operators can play a major role in educating the tourists. The results demonstrate that both an understanding of the chemical and physical factors influencing soil compaction, as well as tourists' environmental views are important in formulating a management strategy to control and manage these impacts. / Thesis (PhD)--University of Pretoria, 2014. / gm2014 / Animal and Wildlife Sciences / unrestricted

Off-road autonomy is a challenging topic that requires robust systems to both understand and navigate complex environments. While on-road autonomy has seen a major expansion in recent years in the consumer space, off-road systems are mostly relegated to niche applications. However, these applications can provide safety and navigation to dangerous areas that are the most suited for autonomy tasks. Traversability analysis is at the core of many of the algorithms employed in these topics. In this thesis, a Clearpath Robotics Jackal vehicle is equipped with a 3D Ouster laser scanner to define and traverse off-road environments. The Mississippi State University Autonomous Vehicle Simulator (MAVS) and the Navigating All Terrains Using Robotic Exploration (NATURE) autonomy stack are used in conjunction with the small-scale vehicle platform to traverse uneven terrain and collect data. Additionally, the NATURE stack is used as a point of comparison between a MAVS simulated and physical Clearpath Robotics Jackal vehicle in testing.

For autonomous vehicles, 3D, rotating LiDAR sensors are critically important towards the vehicle's ability to sense its environment. Generally, these sensors scan their environment, using multiple laser beams to gather information about the range and the intensity of the reflection from an object. For multi--LiDAR systems, the placement of the sensors determines the density of the combined point cloud. I perform preliminary research on the optimal LiDAR placement strategy for an off--road, autonomous vehicle known as the Halo project. I use simulation to generate large amounts of labeled LiDAR data that can be used to train and evaluate a neural network used to process LiDAR data in the vehicle. The performance metrics of the network are then used to generalize the performance of the sensor pose. I also, describe and evaluate intrinsic and extrinsic calibration methods that are applied in the multi--LiDAR system.

Applications like military, agriculture, and extra-planetary explorations require the successful navigation of vehicles across different types of terrain like soil, mud, and snow. As the properties of the terrain heavily influence the interaction with the tire, it is necessary to characterize the terrain from a tire performance and vehicle mobility perspective. Failure to properly understand the tire-terrain interaction can lead to undesirable conditions like loss of vehicle mobility due to excessive sinkage. As a result, it is essential to understand the tire terrain interaction between an off-road tire and a sandy terrain. This study was done to assess the performance of tires in both pure slip (only traction and braking) and combined slip conditions (steering and acceleration). A single-wheel indoor test rig was used to conduct tests under different conditions and a force transducer was used to capture the forces and moments generated in the tire hub. In addition to this, the tire footprint was captured with the help of a light-based 3-D scanner. Key parameters were defined in the 3D scan, and these parameters were correlated to the input test conditions. Additionally, a grid of force sensors was made, and measurements of the normal force acting at a depth below the undisturbed terrain were taken. Inferences were made about the linear speed of the wheel and the length of the pressure bulb under the tire. / Master of Science / Several applications like military, extra-terrestrial exploration, and motor racing require vehicles to navigate off-road terrains like soil, snow, and ice. The tire interacts with these off-road terrains very differently from the way it interacts with the road. It is important to understand this interaction correctly as this interaction generates all the forces needed by a vehicle to perform various maneuvers like acceleration, braking, and turning. If not accounted for properly, there can be undesirable conditions like loss of vehicle mobility due to excessive sinkage in sand. Tests were performed where an off-road tire ran on a non-cohesive, loose soil under different slip ratios, slip angles, and camber angles in an indoor test rig. The forces and moments acting on the tire during the tests were measured and its variation with input conditions was studied. A light-based 3D scanner was used to capture the tire rut profile on the soil after each test. The important parameters of the tire rut were defined and the variation of these parameters with input parameters were studied. Additionally, the stresses developed below the soil surface were measured with the help of a sensor grid, which was also used to verify the linear speed of the tire and infer the length of the zone inside the soil that is affected by the tire.

This study focuses on developing a better comprehension of the mobility of lightweight autonomous vehicles with varying locomotion platforms on sand. This research involves four segments. The first segment is a review of military criteria for the development of lightweight unmanned ground vehicles, followed by a review a review of current methodologies for evaluating the terramechanic (vehicle-ground interaction) mobility measures of heavyweight wheeled and tracked vehicles, and ending with a review of the defining properties of deformable terrain with specific emphasis on sand. These present a basis for understanding what currently defines mobility and how mobility is quantified for traditional heavyweight wheeled and tracked vehicles, as well as an understanding of the environment of operation (sandy terrain) for the lightweight vehicles in this study. The second segment involves the identification of key properties associated with the mobility and operation of lightweight vehicles on sand as related to given mission criteria, so as to form a quantitative assessment system to compare lightweight vehicles of varying locomotion platforms. A table based on the House of Quality shows the relationships—high, low, or adverse—between mission profile requirements and general performance measures and geometries of vehicles under consideration for use. This table, when combined with known values for vehicle metrics, provides information for an index formula used to quantitatively compare the mobility of a user-chosen set of vehicles, regardless of their methods of locomotion. This table identifies several important or fundamental terramechanics properties that necessitate model development for robots with novel locomotion platforms and testing for lightweight wheeled and tracked vehicles so as to consider the adaptation of counterpart heavyweight terramechanics models for use. The third segment is a study of robots utilizing novel forms of locomotion, emphasizing the kinematics of locomotion (gait and foot placement) and proposed starting points for the development of terramechanics models so as to compare their mobility and performance with more traditional wheeled and tracked vehicles. In this study several new autonomous vehicles—bipedal, self-excited dynamic tripedal, active spoke-wheel—that are currently under development are explored. The final segment involves experimentation of several lightweight vehicles and robots on sand. A preliminary experimentation was performed evaluating a lightweight autonomous tracked vehicle for its performance and operation on sand. A bipedal robot was then tested to study the foot-ground interaction with and sinkage into a medium-grade sand, utilizing a one of the first-developed walking gaits. Finally, a comprehensive set of experiments was performed on a lightweight wheeled vehicle. While the terramechanics properties of wheeled and tracked vehicles, such as the contact patch pressure distribution, have been understood and models have been developed for heavy vehicles, the feasibility of extrapolating them to the analysis of light vehicles is still under analysis. A wheeled all-terrain vehicle was tested for effects of sand gradation, vehicle speed, and vehicle payload on measures of pressure and sinkage in the contact patch, and preliminary analysis is presented on the sinkage of the wheeled all-terrain vehicle. These four segments—review of properties of sandy terrain and measures of and criteria for the mobility of lightweight vehicles operating on sandy terrain, the development of the comparison matrix and indexing function, modeling and development of novel forms of locomotion, and physical experimentation of lightweight tracked and wheeled vehicles as well as a bipedal robot—combine to give an overall picture of mobility that spans across different forms of locomotion. / Master of Science

For realistic predictions of vehicle performance in off-road conditions, it is critical to incorporate in the simulation accurate representations of the variability of the terrain profile. It is not practically feasible to measure the terrain at a sufficiently large number of points, or, if measured, to use such data directly in the simulation. Dedicated modeling techniques and computational methods that realistically and efficiently simulate off-road operating conditions are thus necessary. Many studies have been recently conducted to identify effective and appropriate ways to reduce experimental data in order to preserve only essential information needed to re-create the main terrain characteristics, for future use. This thesis focuses on modeling terrain profiles using the finite difference approach for solving linear second-order stochastic partial differential equations. We currently use this approach to model non-stationary terrain profiles in two dimensions (i.e., surface maps). Certain assumptions are made for the values of the model coefficients to obtain the terrain profile through the fast computational approach described, while preserving the stochastic properties of the original terrain topology. The technique developed is illustrated to recreate the stochastic properties of a sample of terrain profile measured experimentally. To further analyze off-road conditions, stochastic soil properties are incorporated into the terrain topology. Soil models can be developed empirically by measuring soil data at several points, or they can be created by using mathematical relations such as the Bekker's pressure-sinkage equation for homogeneous soils. In this thesis, based on a previously developed stochastic soil model, the polynomial chaos method is incorporated in the soil model. In a virtual proving ground, the wheel and soil interaction has to be simulated in order to analyze vehicle maneuverability over different soil types. Simulations have been created on a surface map for different case studies: stepping with a rigid plate, rigid wheel and flexible wheel, and rolling of a rigid wheel and flexible wheel. These case studies had various combinations of stochastic or deterministic terrain profile, stochastic or deterministic soil model, and an object to run across the surface (e.g., deterministic terrain profile, stochastic soil model, rolling rigid wheel). This thesis develops a comprehensive terrain and soil simulation environment for off-road mobility studies. Moreover, the technique developed to simulate stochastic terrain profile can be employed to simulate other stochastic systems modeled by PDEs. / Master of Science

Due to a recent number of undesired rollovers in the field for the studied vehicle, rollover mitigation strategies have been investigated and developed. This research begins with the study of the tire, as it is the single component on the vehicle responsible for generating all of the non-inertial forces to direct the motion of the vehicle. Tire force and moment behavior has been researched extensively and several accurate tire models exist. However, not much research has been performed on off-road tire models. This research develops an off-road tire model for the studied vehicle by first using data from rolling road testing to develop a Pacejka Magic Formula tire model and then extending it to off-road surfaces through the use of scaling factors. The scaling factors are multipliers in the Magic Formula that describe how different aspects of the force and moment curves scale when the tire is driven on different surfaces. Scaling factors for dirt and gravel driving surfaces were obtained by using an existing portable tire test rig to perform force and moment tests on a passenger tire driven on these surfaces. The off-road tire model was then used as a basis for developing control algorithms to prevent vehicle rollover on off-road terrain. Specifically, a direct yaw control (DYC) algorithm based on Lyapunov direct method and an emergency roll control (ERC) algorithm based on a rollover coefficient were developed. Emergency evasive maneuvers were performed in a simulation environment on the studied vehicle driven on dry asphalt, dirt, and gravel for the controlled and uncontrolled cases. Results show that the proposed control algorithms significantly improve vehicle stability and prevent rollover on a variety of driving surfaces. / Master of Science