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Studies that explore integration of visual, auditory or vestibular cues, are derived from stimulus detection and discrimination tasks in which stimuli are selective and controlled. Multisensory processing is not as well understood in more dynamic and realistic tasks such as driving. As visual information is the dominant source of information when controlling a vehicle, we were interested in the contribution of auditory and physical motion (vestibular and proprioceptive) information to vehicle control. The simulated environment consisted of a straight, two-lane road and the task was to drive in the center of the right lane and maintain a constant speed, slowing down for occasional speed bumps. We examined differences in driving performance under four sets of sensory cues: visual only, visual and auditory, visual and physical motion, and visual, auditory and physical motion. The quality of visual information was manipulated across two experiments. In Experiment 1, participants drove in daylight in sunny weather, providing excellent visual information. In Experiment 2, visual information was compromised by providing dark and stormy weather conditions. In both experiments we observed an advantage of multisensory information, an effect that was enhanced when visual information was compromised. Auditory cues were especially effective in improving driver control. / Thesis / Master of Science (MSc) / Multisensory processing (combining information from different sensory systems) is not well understood in realistic tasks such as driving. A simulated environment consisted of a straight, two-lane road was used for this study. The task was to drive in the center of the right lane and maintain a constant speed, slowing down for occasional speed bumps. We examined differences in driving performance under four sets of sensory cues: visual only, visual and auditory, visual and physical motion, and visual, auditory and physical motion. The visual information was manipulated across two experiments: first, participants drove in daylight in sunny weather, providing excellent visual information. Next, visual information was compromised by providing dark and stormy weather conditions. In both experiments we observed an advantage of multisensory information, an effect that was enhanced when visual information was compromised. Auditory cues were especially effective in improving driver control.

Altering driver's goals and motives for at-risk driving is likely to reduce the frequency of at-risk driving behaviors and their associated crashes and injuries. However, most driving occurs when people are alone with little supervisions or accountability. Thus, a self-management for safety (SMS) intervention may be the most appropriate technique to decrease at-risk driving behaviors. The current research evaluated an SMS process with college students on a simulated driving task. Participants included 93 university students (41 males, 52 females) randomly assigned to one of three groups (31 participants per group). Participants in the Control group did not receive any of the intervention materials; they were instructed to drive as they normally drive on each trial. Participants in the Self-Monitoring + Objective Feedback group received objective feedback from the experimenter about their actual performance on the target driving behavior as well as personal feedback from their self-monitoring forms. These participants recorded their individual improvement goals on the targeted driving behavior. Participants in the Self-Monitoring group recorded their individual improvement goals on the targeted driving behavior, but received only personal feedback from their self-monitoring forms. Similar to past self-management interventions directed at increasing safety-related driving behavior (Hickman & Geller, in press; Krause, 1997; Olson & Austin, 2001), SMS led to clear improvement in subsequent safety performance. Based on the recorded driving behaviors of 93 participants, SMS was effective in increasing the mean percentage of total driving time traveling below the posted speed limit compared to a Control group that did not receive any of the SMS components. Across the four trials, participants in the SM and SM + OFB group significantly increased the percentage of total driving time traveling below the posted speed limit by 13.4 (18.3%) and 14.5 (19.8%) percentage points, respectively, compared to participants in the Control group. / Ph. D.

This dissertation research explores a reconfigurable hardware-based parallel simulation mechanism that can dramatically improve the speed of simulating the operations of flexible manufacturing systems (FMS). Here reconfigurable hardware-based simulation refers to running simulation on a reconfigurable hardware platform, realized by Field Programmable Gate Array (FPGA). The hardware model, also called simulator, is specifically designed for mimicking a small desktop FMS. It is composed of several micro-emulators, which are capable of mimicking operations of equipment in FMS, such as machine centers, transporters, and load/unload stations. To design possible architectures for the simulator, a mapping technology is applied using the physical layout information of an FMS. Under such a mapping method, the simulation model is decomposed into a cluster of micro emulators on the board where each machine center is represented by one micro emulator. To exploit the advantage of massive parallelism, a kind of star network architecture is proposed, with the robot sitting at the center. As a pilot effort, a prototype simulator has been successfully built. A new simulation modeling technology named synchronous real-time simulation (SRS) is proposed. Instead of running conventional programs on a microprocessor, this new technology adopts several concepts from electronic area, such as using electronic signals to mimic the behavior of entities and using specifically designed circuits to mimic system resources. Besides, a time-scaling simulation method is employed. The method uses an on-board global clock to synchronize all activities performed on different emulators, and by this way tremendous overhead on synchronization can be avoided. Experiments on the prototype simulator demonstrate the validity of the new modeling technology, and also show that tremendous speedup compared to conventional software-based simulation methods can be achieved. / Ph. D.

Virtual Reality (VR) simulators have become popular because of two distinctive merits. One is the capability to transfer data and information to users in an intuitive way by means of 3-D high-quality graphics output and real input devices. The other is the capability to represent physical systems in mathematical models so that meaningful responses of the systems can be predicted. Previous efforts in VR excavating machine simulator development, however, showed a lack of balance between the fidelity of the model of the physics and the visual representation of the simulated equipment. In order to ensure that a VR construction excavator simulator provides convincing operating results to users, the focus of simulator development needs to be shifted to interaction of physically valid soil and the excavator machine. This research aims to contribute to the development of a VR construction excavator simulator system by proposing a mathematical model of excavator digging and a calculation methodology. The mathematical model of excavator digging provides physically meaningful soil-bucket interaction information to a simulator. The calculation methodology provides systematic and efficient computation methods to ensure the seamless integration of the excavator digging model with a VR simulator system as well as adequate system speed. As a result, the simulator is realized as an engineering process tool equipped with real-time interactivity. / Ph. D.

Simulators are important tools for analyzing and evaluating different design options for wireless sensor networks (sensornets) and hence, have been intensively studied in the past decades. However, existing simulators only support evaluations of protocols and software aspects of sensornet design. They cannot accurately capture the significant impacts of various hardware designs on sensornet performance. As a result, the performance/energy benefits of customized hardware designs are difficult to be evaluated in sensornet research. To fill in this technical void, in this thesis, we describe the design and implementation of SUNSHINE, a scalable hardware-software cross-domain simulator for sensornet applications. SUNSHINE is the first sensornet simulator that effectively supports joint evaluation and design of sensor hardware and software performance in a networked context. SUNSHINE captures the performance of network protocols, software and hardware up to cycle-level accuracy through its seamless integration of three existing sensornet simulators: a network simulator TOSSIM, an instruction-set simulator SimulAVR and a hardware simulator GEZEL. SUNSHINE solves challenging design problems, including data exchanges and time synchronizations across different simulation domains and simulation accuracy levels. SUNSHINE also provides hardware specification scheme for simulating flexible and customized hardware designs. Several experiments are given to illustrate SUNSHINE's cross-domain simulation capability, demonstrating that SUNSHINE is an efficient tool for software-hardware codesign in sensornet research. / Master of Science

This research effort aims to create a new car-following model that accounts for the effects of emotion on driver behavior. This research effort is divided into eight research milestones: (1) the development of a segmentation and clustering algorithm to perform new investigations into driver behavior; (2) the finding that driver behavior is different between drivers, between car-following periods, and within a car-following period; (3) the finding that there are patterns in the distribution of driving behaviors; (4) the finding that driving states can result in different driving actions and that the same driving action can be the result of multiple driving states; (5) the finding that the performance of car-following models can be improved by calibration to state-action clusters; (6) the development of a psychophysiological driving simulator study; (7) the finding that the distribution of driving behavior is affected by emotional states; and (8) the development of a car-following model that incorporates the influence of emotions. / Ph. D.

The purpose of this thesis is to develop an existing design of a fully controllable multi-rotor vehicle toward simulating small satellite dynamics, enabling technology development to be accelerated and component failure risks to be mitigated by providing a testing platform with dynamics similar to those of small satellites in orbit. Evaluating dynamics-sensitive software and hardware components for use in small satellite operations has typically been relegated to simulated or physically constrained testing environments. More recently, researchers have begun using multi-rotor aerial vehicles to mimic the orbital motion of such satellites, further increasing simulation fidelity. The dynamical nature of multi-rotor vehicles allows them to accurately simulate the translational dynamics of a small satellite, but they struggle to accurately simulate rotational dynamics, as conventional multi-rotor vehicles' translational and rotational dynamics are coupled. In this thesis, an optimal design for a multi-rotor vehicle independently controllable in all six degrees of freedom is evaluated as a suitable simulation platform. The design of the proposed physical system is discussed and progress toward its construction is demonstrated. To facilitate future research endeavors, a simulation of the vehicle in a software-in-the-loop environment, using the Gazebo dynamics simulator, is developed and its performance evaluated. This simulation is then used to evaluate the vehicle's feasibility as a small-satellite dynamics simulator by tasking it with tracking dynamic position and attitude time histories representative of a small satellite. / Master of Science / When developing a spacecraft, it can be difficult to accurately test software and hardware that are sensitive to the spacecraft's motion. This difficulty arises because the space environment experienced by orbiting spacecraft allows them to move and rotate freely, and recreating this freedom of motion on earth requires large, expensive, and difficult-to-access test equipment. To make this testing more accessible, researchers have begun using quadcopter drones to mimic some aspects of a spacecraft's motion. While quadcopters can move like an orbiting spacecraft can, their designs do not allow them to rotate like an orbiting spacecraft can, thus providing an incomplete recreation of spacecraft motion. To correct this shortcoming, an existing drone design that is able to move and rotate simultaneously without fear of crashing is developed, with progress shown toward its construction. A software simulation of the drone is developed to help future researchers test software and algorithms before flying it on the physical drone. The simulation is then used to see how well the drone design can recreate the motions that a small spacecraft would experience.

Attitude control laws that use control moment gyros (CMGs) and momentum wheels are derived with nonlinear techniques. The control laws command the CMGs to provide rapid angular acceleration and the momentum wheels to reject tracking and initial condition errors. Numerical simulations of derived control laws are compared. A trend analysis is performed to examine the benefits of the derived controllers. We describe the design of a CMG built using commercial off-the-shelf (COTS) equipment. A mixed attitude control strategy is implemented on the spacecraft simulator at Virginia Tech. / Master of Science