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Recent research at Clemson University has focused on the development of an advanced non-pneumatic, non-elastomeric lunar wheel for NASA with superior traction. This paper reports on several concepts for tread materials and geometries that have been explored for tire-on-sand use. Specifically, fourteen concepts, involving the use of metal meshes, textile carpet materials, soft grousers, foams, and screens, were physically tested in an on-vehicle environment. Prototypes for each concept and formal test procedures to quantify traction were developed. This paper presents the results of the tests for several different concepts and the comparison between the concepts that were developed. Students developed their own testing environment through which these test procedures are implemented, an inclined hill 45 ft. in length and 8 ft. wide will approximately 6 inches deep filled with sand.

To facilitate the design of a non-pneumatic tire for NASA's new Moon mission, the authors used the Finite Element Method (FEM) to investigate the interaction between soil and non-pneumatic tire made of different cellular shear bands. Cellular shear bands, made of an aluminum alloy (AL7075-T6), are designed to have the same effective shear modulus of 6.5E+6 Pa, which is the shear modulus of an elastomer. The Lebanon sand of New Hampshire is used in the model. This sand has a complete set of material properties in the literature and Drucker-Prager/Cap plasticity constitutive law with hardening is employed to model the sand. The tires are treated as deformable bodies, and the authors used the penalty contact algorithm to model the tangential behavior of the contact. The friction between tire and sand is considered by using Coulomb's law. Numerical results show deformation of sand and tire.

The research objective was to measure and understand the preferred seat position of older drivers and younger drivers within their personal vehicles to influence recommended practices and meet the increased safety needs of all drivers. Improper selection of driver’s seat position may impact safety during a crash event and affect one’s capacity to see the roadway and reach the vehicle’s controls, such as steering wheel, accelerator, brake, clutch, and gear selector lever. Because of the stature changes associated with ageing and the fact that stature is normally distributed for both males and females, it was hypothesized that the SAE J4004 linear regression would be improved with the inclusion of gender and age terms that would provide a more accurate model to predict the seat track position of older drivers. Participants included 97 older drivers over the age of 60 and 20 younger drivers between the ages of 30 to 39.

Motor vehicle crashes involving novice drivers are significantly higher than matured driver incidents as reported by the National Highway Traffic Safety Administration Fatality Analysis Reporting System (NHTSA-FARS). Researchers around the world and the United States are focused on how to decrease crashes for this driver demographic. Novice drivers usually complete driver education classes as a pre-requisite for full licensure to improve overall knowledge and safety. However, compiled statistics still indicate a need for more in-depth training after full licensure. An opportunity exists to supplement in-vehicle driving with focused learning modules using automotive simulators. In this paper, a training program for “Following Etiquette” and “Situational Awareness” was developed to introduce these key driving techniques and to complete a feasibility study using a driving simulator as the training tool.

This paper proposes a new vehicle stability control method that quantifies and uses the level of lateral force saturation on each axle/wheel of a vehicle. The magnitude of the saturation, which can be interpreted as a slip-angle deficiency, is determined from on-line estimated nonlinear tire lateral forces and their linear projections that use estimates of the cornering stiffness. Once known, the saturation levels are employed in a saturation balancing control structure that biases the drive torque to either the front or rear axles/wheels with the goal of minimizing excessive under- or over-steer, thereby stabilizing the vehicle. The method is particularly suited for a vehicle with an independent wheel drive system. Furthermore, the method can be used in conjunction with a direct yaw-moment controller to obtain enhanced stability and responsiveness.

A simulation of the vertical response of a nonlinear 1/4 car model consisting of a sprung and an unsprung mass was developed. It is being used for preliminary evaluation of various suspension configurations and control algorithms. Nonlinearities include hysteretic shock damping and switchable damping characteristics. Road inputs include discrete events such as bumps and potholes as well as randomly irregular roads having specified power spectral densities (PSDs). Fast Fourier transform data analysis procedures are used to process data from the simulation to obtain PSDs, rms values, and histograms of various response quantities. To aid in assessing ride comfort, the 1/3 octave band rms acceleration of the sprung mass is calculated and compared with specifications suggested by the International Standards Organization (ISO). Cross plots of the rms values of acceleration, suspension travel, and the force of the road on the tire are used to compare the performance of various suspensions.

According to the National Highway Traffic Safety Administration (NHTSA), motor collisions account for nearly 2.4 million injuries and 37 thousand fatalities each year in the United States. A great deal of research has been done in the area of vehicular safety, but very little has been completed to ensure licensed drivers are properly trained. Given the inherent risks in driving itself, the test for licensure should be uniform and consistent. To address this issue, an inexpensive, portable data acquisition and analysis system has been developed for the evaluation of driver performance. A study was performed to evaluate the system, and each participant was given a normalized driver rating. The average driver rating was μ=55.6, with a standard deviation of σ=12.3. All but 3 drivers fell into the so-called “Target Zone”, defined by a Driver Rating of μ± 1σ.

Driver modeling is essential to both vehicle design and control unit development. It can improve the understanding of human driving behavior and decrease the cost and risk of vehicle system verification and validation. In this paper, three driver models were implemented to simulate the behavior of drivers subject to a run-off-road recovery event. Target path planning, pursuit behavior, compensate behavior, physical limitations, and neuromuscular modeling were taken into consideration in the feedforward/feedback driver model. A transfer function driver model and a cost function based driver model from a popular vehicle simulation software were also simulated and a comparison of these three models was made. The feedforward/feedback driver model exhibited the best balance of performance with smallest overshoot (0.226m), medium settling time (1.20s) and recovery time (4.30s).

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).