Browsing by Author "Taheri, Saied"

Now showing 1 - 20 of 142
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    3D printed graphene-based self-powered strain sensors for smart tires in autonomous vehicles
    Maurya, Deepam; Khaleghian, Seyedmeysam; Sriramdas, Rammohan; Kumar, Prashant; Kishore, Ravi Anant; Kang, Min-Gyu; Kumar, Vireshwar; Song, Hyun-Cheol; Lee, Seul-Yi; Yan, Yongke; Park, Jung-Min (Jerry); Taheri, Saied; Priya, Shashank (2020-10-26)
    The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability. Designing efficient sensors for smart tires for autonomous vehicles remains a challenge. Here, the authors present a tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis.
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    Accelerometer Based Method for Tire Load and Slip Angle Estimation
    Singh, Kanwar Bharat; Taheri, Saied (MDPI, 2019-04-28)
    Tire mounted sensors are emerging as a promising technology, capable of providing information about important tire states. This paper presents a survey of the state-of-the-art in the field of smart tire technology, with a special focus on the different signal processing techniques proposed by researchers to estimate the tire load and slip angle using tire mounted accelerometers. Next, details about the research activities undertaken as part of this study to develop a smart tire are presented. Finally, novel algorithms for estimating the tire load and slip angle are presented. Experimental results demonstrate the effectiveness of the proposed algorithms.
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    Adaptive control of a DDMR with a Robotic Arm
    Chaure, Rishabh Subhash (Virginia Tech, 2021-11-30)
    Robotic arms are essential in a variety of industrial processes. However, the dexterous workspace of a robotic arm is limited. This limitation can be overcome by making the robotic arm mobile. Such robots, which comprise a robotic manipulator installed on a wheeled mobile platform, are called mobile robots. A mobile manipulator can attain a position in space which a robotic arm with fixed base may not be able to reach otherwise. To be applicable to a variety of scenarios, these robots need to meet user-defined margins on their trajectory tracking error, irrespective of the payload transported, faults, and failures. In this thesis, we study the dynamics of mobile manipulator comprising both a differential-drive mobile robot (DDMR) and a robotic arm. Thus, we design a model reference adaptive controller (MRAC) for this mobile manipulator to regulate this vehicle and guarantee robustness to uncertainties in the robot's inertial properties such as the mass of the payload transported and friction coefficients.
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    Adaptive Rollover Control Algorithm Based on an Off-Road Tire Model
    Hopkins, Brad Michael (Virginia Tech, 2009-11-30)
    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.
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    Algorithm to enable intelligent rail break detection
    Bhaduri, Sreyoshi (Virginia Tech, 2013-12-11)
    Wavelet intensity based algorithm developed previously at VirginiaTech has been furthered and paired with an SVM based classifier. The wavelet intensity algorithm acts as a feature extraction algorithm. The wavelet transform is an effective tool as it allows one to narrow down upon the transient, high frequency events and is able to tell their exact location in time. According to prior work done in the field of signal processing, the local regularities of a signal can be estimated using a Lipchitz exponent at each time step of the signal. The local Lipchitz exponent can then be used to generate the wavelet intensity factor values. For each vertical acceleration value, corresponding to a specific location on the track, we now have a corresponding intensity factor. The intensity factor corresponds to break-no break information and can now be used as a feature to classify the vertical acceleration as a fault or no fault. Support Vector Machines (SVM) is used for this binary classification task. SVM is chosen as it is a well-studied topic with efficient implementations available. SVM instead of hard threshold of the data is expected to do a better job of classification without increasing the complexity of the system appreciably.
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    Analysis and Development of Control Methodologies for Semi-active Suspensions
    Ghasemalizadeh, Omid (Virginia Tech, 2016-11-14)
    Semi-active suspensions have drawn particular attention due to their superior performance over the other types of suspensions. One of their advantages is that their damping coefficient can be controlled without the need for any external source of power. In this study, a handful of control approaches are implemented on a car models using MATLAB/Simulink. The investigated control methodologies are skyhook, groundhook, hybrid skyhook-groundhook, Acceleration Driven Damper, Power Driven Damper, H∞ Robust Control, Fuzzy Logic Controller, and Inverse ANFIS. H∞ Robust Control is an advanced method that guarantees transient performance and rejects external disturbances. It is shown that H∞ with the proposed modification, has the best performance although its relatively high cost of computation could be potentially considered as a drawback. Also, the proposed Inverse ANFIS controller uses the power of fuzzy systems along with neural networks to help improve vehicle ride metrics significantly. In this study, a novel approach is introduced to analyze and fine-tune semi-active suspension control algorithms. In some cases, such as military trucks moving on off-road terrains, it is critical to keep the vehicle ride quality in an acceptable range. Semi-active suspensions are used to have more control over the ride metrics compared to passive suspensions and also, be more cost-effective compared to active suspensions. The proposed methodology will investigate the skyhook-groundhook hybrid controller. This is accomplished by conducting sensitivity analysis of the controller performance to varying vehicle/road parameters. This approach utilizes sensitivity analysis and one-at-a-time methodology to find and reach the optimum point of vehicle suspensions. Furthermore, real-time tuning of the mentioned controller will be studied. The online tuning will help keep the ride quality of the vehicle close to its optimum point while the vehicle parameters are changing. A quarter-car model is used for all simulations and analyses.
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    Analysis of Transient and Steady State Vehicle Handling with Torque Vectoring
    Jose, Jobin (Virginia Tech, 2021-10-07)
    Advanced Driver Assistance Systems (ADAS) and Autonomous Ground Vehicles (AGV) have the potential to increase road transportation safety, environmental gains, and passenger comfort. The advent of Electric Vehicles has also facilitated greater flexibility in powertrain architectures and control capabilities. Path Tracking controllers that provide steering input are used to execute lateral maneuvers or model the response of a vehicle during cornering. Direct Yaw Control using Torque Vectoring has the potential to improve vehicle's transient cornering stability and modify its steady state handling characteristics during lateral maneuvers. In the first part of this thesis, the transient dynamics of an existing baseline Path Tracking controller is improved using a transient Torque Vectoring algorithm. The existing baseline Path Tracking controller is evaluated, using a linearized system, for a range of vehicle and controller parameters. The effect of implementing transient Torque Vectoring along with the baseline Path Tracking controller is then studied for the same parameter range. The linear analysis shows, in both time and frequency domain, that the transient Torque Vectoring improves vehicle response and stability during cornering. A Torque Vectoring controller is developed in Linear Adaptive Model Predictive Control framework and it's performance is verified in simulation using Simulink and CarSim. The second part of the thesis analyzes the tradeoff enabled by steady state Torque Vectoring between improved limit handling capability through optimal tire force allocation and drivability demonstrated by understeer gradient. Optimal tire force allocation prescribes equal usage in all four tires during maneuvers. This is enabled using steering and Torque Vectoring. An analytical proof is presented which demonstrates that implementation of this optimal tire force allocation results in neutralsteering handling characteristics for the vehicle. The optimal tire force allocation strategy is formulated as a minimax optimization problem. A two-track vehicle model is simulated for this strategy, and it verified the analytical proof by displaying neutralsteering behavior.
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    Analytical Evaluation of the Accuracy of Roller Rig Data for Studying Creepage in Rail Vehicles
    Keylin, Alexander (Virginia Tech, 2013-01-23)
    The primary purpose of this research is to investigate the effectiveness of a scaled roller rig for accurately assessing the contact mechanics and dynamics between a profiled steel wheel and rail, as is commonly used in rail vehicles. The established creep models of Kalker and Johnson and Vermeulen are used to establish correction factors, scaling factors, and transformation factors that allow us to relate the results from a scaled rig to those of a tangent track. �Correction factors, which are defined as the ratios of a given quantity (such as creep coefficient) between a roller rig and a track, are derived and used to relate the results between a full-size rig and a full-size track. Scaling factors are derived to relate the same quantities between roller rigs of different scales. Finally, transformation factors are derived by combining scaling factors with correction factors in order to relate the results from a scaled roller rig to a full-size tangent track. Close-end formulae for creep force correction, scaling, and transformation factors are provided in the thesis, along with their full derivation and an explanation of their limitations; these formulae can be used to calculate the correction factors for any wheel-rail geometry and scaling. For Kalker's theory, it is shown that the correction factor for creep coefficients is strictly a function of wheel and rail geometry, primarily the wheel and roller diameter ratio. For Johnson and Vermeulen's theory, the effects of creepage, scale, and load on the creep force correction factor are demonstrated. �It is shown that INRETS' scaling strategy causes the normalized creep curve to be identical for both a full-size and a scaled roller rig. �It is also shown that the creep force correction factors for Johnson and Vermeulen's model increase linearly with creepage, starting with the values predicted by Kalker's theory. �Therefore, Kalker's theory provides a conservative estimate for creep force correction factors. �A case study is presented to demonstrate the creep curves, as well as the correction and transformation factors, for a typical wheel-rail configuration. �Additionally, two studies by other authors that calculate the correction factor for Kalker's creep coefficients for specific wheel-rail geometries are reviewed and show full agreement with the results that are predicted by the formulae derived in this study. �Based on a review of existing and past roller rigs, as well as the findings of this thesis, a number of recommendations are given for the design of a roller rig for the purpose of assessing the wheel-rail contact mechanics. �A scaling strategy (INRETS') is suggested, and equations for power consumption of a roller rig are derived. Recommendations for sensors and actuators necessary for such a rig are also given. Special attention is given to the resolution and accuracy of velocity sensors, which are required to properly measure and plot the creep curves.
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    Analytical Modeling for Sliding Friction of Rubber-Road Contact
    Vadakkeveetil, Sunish (Virginia Tech, 2017-04-21)
    Rubber friction is an important aspect to tire engineers, material developers and pavement engineers because of its importance in the estimation of forces generated at the contact, which further helps in optimizing tire and vehicle performances, and to estimate tire wear. It mainly depends on the material properties, contact mechanics and operating condition. There are two major contributions to rubber friction, due to repeated viscoelastic deformation from undulations of surface called hysteresis and due to Vander Waals interaction of the molecules called adhesion. The study focuses on analytical modeling of friction for stationary sliding of rubber block on rough surfaces. Two novel approaches are discussed and compared. Frictional shear stress is obtained from the energy dissipated at the contact interface due to the elastic deformations of rubber block at different length scales. Contact mechanics theories based on continuity approach combined with stochastic processes to estimate the real contact area, mean penetration depth and true stresses at contact depending on operating conditions. Rubber properties are highly temperature dependent. Temperature model developed based on heat diffusion relation is integrated to consider the effects of temperature rise due to frictional heating. Model results are validated with theoretical results of literature. Simulation results of friction model is obtained for Compound A sliding on rough surface. Material properties are obtained using Dynamic Mechanical Analysis and Time temperature superposition. Influence of the friction models under different conditions are discussed. Model results are validated with experimental data from Dynamic friction tester on a 120-grit surface followed by future works.
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    The Application of Intelligent Tires and Model Base Estimation Algorithms in Tire-road Contact Characterization
    Khaleghian, Seyedmeysam (Virginia Tech, 2017-02-13)
    Lack of drivers knowledge about the abrupt changes in pavement friction and poor performance of the vehicle stability, traction and ABS controllers on the low friction surfaces are the most important factors affecting car crashes. Due to its direct relation to vehicle stability, accurate estimation of tire-road characteristics is of interest to all vehicle and tire companies. Many studies have been conducted in this field and researchers have used different tools and have proposed different algorithms. One such concept is the Intelligent Tire. The application of intelligent tire in tire-road characterization is investigated in this study. Three different test setups were used in this research to study the application of the intelligent tires to improve mobility; first, a wheeled ground robot was designed and built. A Fuzzy Logic algorithm was developed and validated using the robot for classifying different road surfaces such as asphalt, concrete, grass, and soil. The second test setup is a portable tire testing trailer, which is a quarter car test rig installed in a trailer and towed by a truck. The trailer was equipped with different sensors including an accelerometer attached to the center of the tire inner-liner. Using the trailer, acceleration data was collected under varying conditions and a Neural Network (NN) algorithm was developed and trained to estimate the contact patch length, effective tire rolling radius and tire normal load. The third test setup developed for this study was an instrumented Volkswagen Jetta. Different sensors were installed to measure vehicle dynamic response. Additionally, one front and one rear tire was instrumented with an accelerometer attached to their inner-liner. Two intelligent tire based algorithms, a tire pressure estimation algorithm and a road condition monitoring algorithm, were developed and trained using the experimental data from the instrumented VW Jetta. The two-step pressure monitoring algorithm uses the acceleration signal from the intelligent tire and the wheel angular velocity to monitor the tire pressure. Also, wet and dry surfaces are distinguished using the acceleration signal from the intelligent tire and the wheel angular velocity through the surface monitoring algorithm. Some of the model based tire-road friction estimation algorithms, which are widely used for tire-road friction estimation, were also introduced in this study and the performance of each algorithm was evaluated in high slip and low slip maneuvers. Finally a new friction estimation algorithm was developed, which is a combination of experiment based and vehicle dynamic based approaches and its performance was also investigated.
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    Application of Multifunctional Doppler LIDAR for Non-contact Track Speed, Distance, and Curvature Assessment
    Munoz, Joshua (Virginia Tech, 2015-12-08)
    The primary focus of this research is evaluation of feasibility, applicability, and accuracy of Doppler Light Detection And Ranging (LIDAR) sensors as non-contact means for measuring track speed, distance traveled, and curvature. Speed histories, currently measured with a rotary, wheel-mounted encoder, serve a number of useful purposes, one significant use involving derailment investigations. Distance calculation provides a spatial reference system for operators to locate track sections of interest. Railroad curves, using an IMU to measure curvature, are monitored to maintain track infrastructure within regulations. Speed measured with high accuracy leads to high-fidelity distance and curvature data through utilization of processor clock rate and left-and right-rail speed differentials during curve navigation, respectively. Wheel-mounted encoders, or tachometers, provide a relatively low-resolution speed profile, exhibit increased noise with increasing speed, and are subject to the inertial behavior of the rail car which affects output data. The IMU used to measure curvature is dependent on acceleration and yaw rate sensitivity and experiences difficulty in low-speed conditions. Preliminary system tests onboard a 'Hy-Rail' utility vehicle capable of traveling on rail show speed capture is possible using the rails as the reference moving target and furthermore, obtaining speed profiles from both rails allows for the calculation of speed differentials in curves to estimate degrees curvature. Ground truth distance calibration and curve measurement were also carried out. Distance calibration involved placement of spatial landmarks detected by a sensor to synchronize distance measurements as a pre-processing procedure. Curvature ground truth measurements provided a reference system to confirm measurement results and observe alignment variation throughout a curve. Primary testing occurred onboard a track geometry rail car, measuring rail speed over substantial mileage in various weather conditions, providing high-accuracy data to further calculate distance and curvature along the test routes. Tests results indicate the LIDAR system measures speed at higher accuracy than the encoder, absent of noise influenced by increasing speed. Distance calculation is also high in accuracy, results showing high correlation with encoder and ground truth data. Finally, curvature calculation using speed data is shown to have good correlation with IMU measurements and a resolution capable of revealing localized track alignments. Further investigations involve a curve measurement algorithm and speed calibration method independent from external reference systems, namely encoder and ground truth data. The speed calibration results show a high correlation with speed data from the track geometry vehicle. It is recommended that the study be extended to provide assessment of the LIDAR's sensitivity to car body motion in order to better isolate the embedded behavior in the speed and curvature profiles. Furthermore, in the interest of progressing the system toward a commercially viable unit, methods for self-calibration and pre-processing to allow for fully independent operation is highly encouraged.
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    Application of Recursive Least Square Algorithm on Estimation of Vehicle Sideslip Angle and Road Friction
    Ding, Nenggen; Taheri, Saied (Hindawi Publishing Corporation, 2010)
    A recursive least square (RLS) algorithm for estimation of vehicle sideslip angle and road friction coefficient is proposed. The algorithm uses the information from sensors onboard vehicle and control inputs from the control logic and is intended to provide the essential information for active safety systems such as active steering, direct yaw moment control, or their combination. Based on a simple two-degree-of-freedom (DOF) vehicle model, the algorithm minimizes the squared errors between estimated lateral acceleration and yaw acceleration of the vehicle and their measured values. The algorithm also utilizes available control inputs such as active steering angle and wheel brake torques. The proposed algorithm is evaluated using an 8-DOF full vehicle simulation model including all essential nonlinearities and an integrated active front steering and direct yaw moment control on dry and slippery roads.
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    Approximations for Nonlinear Differential Algebraic Equations to Increase Real-time Simulation Efficiency
    Kwong, Gordon Houng (Virginia Tech, 2010-05-05)
    Full-motion driving simulators require efficient real-time high fidelity vehicle models in order to provide a more realistic vehicle response. Typically, multi-body models are used to represent the vehicle dynamics, but these have the unfortunate drawback of requiring the solution of a set of coupled differential algebraic equations (DAE). DAE's are not conducive to real-time implementation such as in a driving simulator, without a very expensive processing capability. The primary objective of this thesis is to show that multi-body models constructed from DAE's can be reasonably approximated with linear models using suspension elements that have nonlinear constitutive relationships. Three models were compared in this research, an experimental quarter-car test rig, a multi-body dynamics differential algebraic equation model, and a linear model with nonlinear suspension elements. Models constructed from differential algebraic equations are computationally expensive to compute and are difficult to realize for real-time simulations. Instead, a linear model with nonlinear elements was proposed for a more computationally efficient solution that would retain the nonlinearities of the suspension. Simplifications were made to the linear model with nonlinear elements to further reduce computation time for real-time simulation. The development process of each model is fully described in this thesis. Each model was excited with the same input and their outputs were compared. It was found that the linear model with nonlinear elements provides a reasonably good approximation of actual model with the differential algebraic equations.
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    Artificial Neural Networks based Modeling and Analysis of Semi-Active Damper System
    Bhanot, Nishant (Virginia Tech, 2017-06-30)
    The suspension system is one of the most sensitive systems of a vehicle as it affects the dynamic behavior of the vehicle with even minor changes. These systems are designed to carry out multiple tasks such as isolating the vehicle body from the road/tire vibrations as well as achieving desired ride and handling performance levels in both steady state and limit handling conditions. The damping coefficient of the damper plays a crucial role in determining the overall frequency response of the suspension system. Considerable research has been carried out on semi active damper systems as the damping coefficient can be varied without the system requiring significant external power giving them advantages over both passive and fully active suspension systems. Dampers behave as non-linear systems at higher frequencies and hence it has been difficult to develop accurate models for its full range of motion. This study aims to develop a velocity sensitive damper model using artificial neural networks and essentially provide a 'black-box' model which encapsulates the non-linear behavior of the damper. A feed-forward neural network was developed by testing a semi active damper on a shock dynamometer at CenTiRe for multiple frequencies and damping ratios. This data was used for supervised training of the network using MATLAB Neural Network Toolbox. The developed NN model was evaluated for its prediction accuracy. Further, the developed damper model was analyzed for feasibility of use for simulations and controls by integrating it in a Simulink based quarter car model and applying the well-known skyhook control strategy. Finally, effects on ride and handling dynamics were evaluated in Carsim by replacing the default damper model with the proposed model. It was established that this damper modeling technique can be used to help evaluate the behavior of the damper on both component as well as vehicle level without needing to develop a complex physics based model. This can be especially beneficial in the earlier stages of vehicle development.
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    Asperity-based modification on theory of contact mechanics and rubber friction for self-affine fractal surfaces
    Emami, Anahita; Khaleghian, Seyedmeysam; Taheri, Saied (2021-05-15)
    Abstract Modeling the real contact area plays a key role in every tribological process, such as friction, adhesion, and wear. Contact between two solids does not necessarily occur everywhere within the apparent contact area. Considering the multiscale nature of roughness, Persson proposed a theory of contact mechanics for a soft and smooth solid in contact with a rigid rough surface. In this theory, he assumed that the vertical displacement on the soft surface could be approximated by the height profile of the substrate surface. Although this assumption gives an accurate pressure distribution at the interface for complete contact, when no gap exists between two surfaces, it results in an overestimation of elastic energy stored in the material for partial contact, which typically occurs in many practical applications. This issue was later addressed by Persson by including a correction factor obtained from the comparison of the theoretical results with molecular dynamics simulation. This paper proposes a different approach to correct the overestimation of vertical displacement in Persson’s contact theory for rough surfaces with self-affine fractal properties. The results are compared with the correction factor proposed by Persson. The main advantage of the proposed method is that it uses physical parameters such as the surface roughness characteristics, material properties, sliding velocity, and normal load to correct the model. This method is also implemented in the theory of rubber friction. The results of the corrected friction model are compared with experiments. The results confirm that the modified model predicts the friction coefficient as a function of sliding velocity more accurately than the original model.
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    Characterization of Structure-Borne Tire Noise Using Virtual Sensing
    Nouri, Arash (Virginia Tech, 2021-01-27)
    Various improvements which have been made to the vehicle (reduced engine noise, reducedaerodynamic related NVH), have resulted in tire road noise as the dominant source of thevehicle interior noise. Generally, vehicle interior noise has two main sources, 1) travellinglow frequency excitation below 800 Hz from road surface through a structure- borne pathand 2) the high frequency (above 800 Hz) air-borne noise that is caused by air- pumpingnoise caused by tread pattern.The structure-borne waves of the circumference of the tire are generated by excitation atthe contact patch due to the road surface texture and characteristics. These vibrations arethen transferred from the sidewalls of the tire to the rim and then are transmitted throughthe spindle-wheel interface, resulting in high frequency vibration of vehicle body panels andwindows.The focus of this study is to develop several statistical-based models for analyzing the roadsurface and using them to predict the tire-road noise structure-borne component. In order todo this, a new methodology for sensing the road characteristics, such as asperities and roadsurface condition, were developed using virtual sensing and intelligent tire technology. In ad-dition, the spindle forces were used as an indicator to the structure-borne noise of the vehicle.Several data mining and multivariate analysis-based methods were developed to extractfeatures and to develop an empirical model to predict the power of structure-borne noiseunder different operational and road conditions. Finally, multiple data driven models-basedmodels were developed to classify the road types, and conditions and use them for the noisefrequency spectrum prediction.
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    Compacted Snow Testing Methodology and Instrumentation
    Shenvi, Mohit Nitin (Virginia Tech, 2024-03-05)
    Snow is a complex material that is difficult to characterize especially due to its high compressibility and temperature-sensitive nonlinear viscoelasticity. Snow mechanics has been intensively investigated by avalanche and army researchers for decades. However, fewer research studies have been published for compacted snow, commonly defined as snow with a density in the range of 370-560 kg/m3. From a mobility perspective, the tires are the primary point of force and motion generation and their interaction with the terrain causes an increased reliance on the skill of the driver for safer mobility. Thus, standards like ASTM F1805 are implemented for the evaluation of winter tires which can be used in harsh conditions like ice and snow. This work focuses on evaluating the prior efforts performed for the measurement of snow properties. In addition, analysis using regression models and principal component analysis is performed to understand the extent to which specific measurements related to snow affect the traction of the tire. It was found that the compressive and shear properties of snow contribute more than 90% to the variation in the traction coefficient of a tire when evaluated on a compacted snow domain per ASTM F1805. Identification of this phenomenon allowed the enhancement of an existing device that can be used for measuring the compaction and shear properties of snow. The device hence conceptualized was manufactured in-house and tested at the Smithers Winter Test Center to benchmark against existing devices available commercially. Further, a more analytical method for evaluating the resistive pressure for the penetration of the device was formulated. Based on this, a possible framework for the determination of the bevameter parameters using measurements of the new device has been proposed which needs to be validated experimentally and computationally.
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    Comparative Study of the Effect of Tread Rubber Compound on Tire Performance on Ice
    Shenvi, Mohit Nitin (Virginia Tech, 2020-08-20)
    The tire-terrain interaction is complex and tremendously important; it impacts the performance and safety of the vehicle and its occupants. Icy roads further enhance these complexities and adversely affect the handling of the vehicle. The analysis of the tire-ice contact focusing on individual aspects of tire construction and operation is imperative for tire industry's future. This study investigates the effects of the tread rubber compound on the drawbar pull performance of tires in contact with an ice layer near its melting point. A set of sixteen tires of eight different rubber compounds were considered. The tires were identical in design and tread patterns but have different tread rubber compounds. To study the effect of the tread rubber compound, all operational parameters were kept constant during the testing conducted on the Terramechanics Rig at the Terramechanics, Multibody, and Vehicle Systems laboratory. The tests led to conclusive evidence of the effect of the tread rubber compound on the drawbar performance (found to be most prominent in the linear region of the drawbar-slip curve) and on the resistive forces of free-rolling tires. Modeling of the tire-ice contact for estimation of temperature rise and water film height was performed using ATIIM 2.0. The performance of this in-house model was compared against three classical tire-ice friction models. A parametrization of the Magic Formula tire model was performed using experimental data and a Genetic Algorithm. The dependence of individual factors of the Magic Formula on the ambient temperature, tire age, and tread rubber compounds was investigated.
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    Cooperative Perception for Connected Vehicles
    Mehr, Goodarz (Virginia Tech, 2024-05-31)
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    Cooperative Perception in Autonomous Ground Vehicles using a Mobile Robot Testbed
    Sridhar, Srivatsan (Virginia Tech, 2017-10-03)
    With connected and autonomous vehicles, no optimal standard or framework currently exists, outlining the right level of information sharing for cooperative autonomous driving. Cooperative Perception is proposed among vehicles, where every vehicle is transformed into a moving sensor platform that is capable of sharing information collected using its on-board sensors. This helps extend the line of sight and field of view of autonomous vehicles, which otherwise suffer from blind spots and occlusions. This increase in situational awareness promotes safe driving over a short range and improves traffic flow efficiency over a long range. This thesis proposes a methodology for cooperative perception for autonomous vehicles over a short range. The problem of cooperative perception is broken down into sub-tasks of cooperative relative localization and map merging. Cooperative relative localization is achieved using visual and inertial sensors, where a computer-vision based camera relative pose estimation technique, augmented with position information, is used to provide a pose-fix that is subsequently updated by dead reckoning using an inertial sensor. Prior to map merging, a technique for object localization using a monocular camera is proposed that is based on the Inverse Perspective Mapping technique. A mobile multi-robot testbed was developed to emulate autonomous vehicles and the proposed method was implemented on the testbed to detect pedestrians and also to respond to the perceived hazard. Potential traffic scenarios where cooperative perception could prove crucial were tested and the results are presented in this thesis.