Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 29 for “"driving scenarios"”.
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Deidentification of Face Videos in Naturalistic Driving Scenarios
The sharing of data has become integral to advancing scientific research, but it introduces challenges related to safeguarding personally identifiable information (PII). This thesis addresses the specific problem of sharing drivers' face videos for transportation research while ensuring privacy …
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Development and Demonstration of Scalable Methods for Research on Human Factors in Driving
… that sufficient attention is directed to the driving task, our research understanding of detailed relationships between driving task complexity, in-vehicle and off-road distractions, and driving performance remains limited. Part of this limitation is due to inherent challenges of carrying out …
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Radar-based Environment Perception for Pre-Crash Safety Systems
… detection and tracking in dynamic pre-crash scenarios, as well as ghost object identification. The problem of a wandering dominant scatter point on the target surface and corresponding challenge for accurate target tracking in low-range configurations is considered. The proposed method …
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Improving Accessibility of Fully Automated Driving Systems for Blind and Low Vision Riders
… of life. The emergence of levels 4 – 5 automated driving system-dedicated vehicles (L4+ ADS), which will not require human operators to provide any input into the dynamic driving task, could empower the BLV community by providing an independent means of transportation. Yet, the BLV community has …
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Development of eco-driving control system for connected and automated hybrid electric vehicles
… studied. In this study, a bi-level MPC-based eco-driving strategy for CAHEVs is proposed and designed to improve fuel economy, reduce exhaust emissions while ensuring driving safety under the most common driving scenarios. First, the HEV powertrain is modelled, and the real-time data sources are …
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Gaze-Aware Driver Maneuver Prediction Using Object Detection and Sequential Deep Learning Models for Advanced Driver Assistance Systems
… and contextual cues for temporal modeling in driving scenarios and underscores the potential of TCNs for efficient and accurate maneuver prediction in future ADAS systems.
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Online risk-aware conditional planning with qualitative autonomous driving applications
Driving is often stressful and dangerous due to uncertainty in the actions of nearby vehicles. Having the ability to model driving maneuvers qualitatively and guarantee safety bounds in uncertain traffic scenarios are two steps towards building trust in vehicle autonomy. In this thesis, we present …
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Enhancing Perception Systems using V2V Sensor Fusion
… or have low visibility. City and highway driving scenarios and Software-in-the-Loop testing is used to evaluate the proposed fused track list.
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Provident Vehicle Detection at Night in Urban Scenarios
… detection and is crucial to safe and comfortable driving. This thesis investigates for the first time the anticipatory detection of oncoming vehicles at night in urban environments, aiming to bridge the gap between human and computer perception. Through a series of experiments and analyses, this …
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Attentional Control in Young Drivers: Does Training Help or Hinder Bottom-Up Processing in a Dynamic Driving Environment?
… hazards on the road is a critical skill for safe driving, one that many young and novice drivers lack. Training programs are shown to improve hazard anticipation performance in young drivers, but whether these training effects persist in the presence of salient and potentially distracting stimuli …
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Characterizing and Comparing the ADS Maneuver Execution Subsystem Performance of Two Vehicles
Automated driving systems (ADS) are projected to bring a plethora of benefits to society, such as enhanced road safety and heightened quality of life. However, placing one's trust in the hands of an automated system is still a large concern to society. To facilitate the large-scale adoption of …
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Optimal Strategy Imitation Learning from Differential Games
… players and can be used to model adversarial driving scenarios rather than average ones, so that autonomous vehicles will be safer on the road in more situations. Further, discrete approximations of solutions to complex games that are computationally tractable and provably asymptotically …
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State Estimation in Dynamical Robotic System with Non-Gaussian Noise
… datasets ranging from table-top scenes to self-driving scenarios and demonstrate its effectiveness. For state estimation in polynomial systems corrupted by arbitrary noise, we develop a new filtering approach called the Generalized Moment Kalman Filter (GMKF). The GMKF formulates the prediction …
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Motion Planning For Autonomous Vehicles In Non-Signalized Intersections
… including collision checks, is vital in critical driving scenarios such as navigating non-signalized intersections. These intersections lack organized traffic flow, which raises the risk of accidents. Rapidly Exploring Random Trees (RRT) is a widely adopted algorithm in robotics for motion …
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Enhanced Feature Representation in Multi-Modal Learning for Driving Safety Assessment
… dissertation explores innovative approaches in driving safety through the development of multi-modal learning frameworks that leverage high-frequency, high-resolution driving data and videos to detect safety-critical events (SCEs). The research unfolds across four methodologies, each …
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Assessing Alternate Approaches for Conveying Automated Vehicle Intentions
… (i.e., "intentions") and perceptions of the driving environment to the user. Methods: This project developed HMI systems, with a focus on visual and auditory displays, and implemented them into a HAV developed at the Virginia Tech Transportation Institute (VTTI). Volunteer participants were …
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Communication and generalization in multi-agent learning
… in complex environments such as autonomous driving, where humans and AI agents coexist. This dissertation research investigates how agents can be trained to effectively communicate with and generalize to diverse partners (including humans) in simulated real-world scenarios. Towards …
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Visual-Inertial State Estimation With Information Deficiency
… systems such as micro aerial vehicles and self-driving cars, it is a prerequisite for control and motion planning. For AR/VR applications, it is the first step to image rendering. Visual-inertial odometry (VIO) is the de-facto standard algorithm for embedded platforms because it lends itself to …
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Effects of Age-Related Declines in Visual Motion Processing on Older Driver Safety
… PMCT-10 and the shorter PMCT-2—were employed. Driving safety was measured via a high fidelity driving simulator, in addition to several self-report measures and archival data. Study 1 showed that PMCT-2 and PMCT-10 thresholds were associated with number of crashes in the simulator and other …
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Safety of Self-driving Cars: A Case Study on Lane Keeping Systems
… learning is a powerful method to handle the self-driving problem. Researchers use machine learning to construct a neural network and train it to drive the car. A self-driving car is a safety-critical system. However, the neural network is not necessarily reliable. The output of a neural network …
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