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.
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Showing 1 to 20 of 82 for “"Self-driving Cars"”.
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High resolution millimeter wave imaging for self-driving cars
… wave (mmWave) technology for imaging in self-driving cars. Specifically, the use of mmWave in 5G has led to the creation of compact phased arrays with hundreds of antenna elements that can be electronically steered. Such phased arrays can expand the use of mmWave beyond vehicular …
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Procedural synthetic data for self-driving cars using 3D graphics
… for procedurally generating synthetic data for self-driving vehicles. To address the problem of data hungry vision-based learning algorithms used in self-driving vehicles, we develop a system that generates synthetic images, including class level annotations, of street scenes. To give …
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Accurate detection for self driving cars using multi-resolution MIMO radar
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
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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 …
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Developing a simulator to aid in the design of a safety interlock for self-driving cars
Self-driving cars have tremendous potential to be safer than human drivers, but are complex systems for which evaluating safety is challenging: using a statistical approach requires self-driving cars to have clocked on the order of billions of miles of driving to present convincing evidence. Thus …
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Towards a transparency-based, value-sensitive design solution for bias in self-driving cars: An ethical violation assessment and risk analysis framework on consumer-held values
… and artificial intelligence (AI), particularly, self-driving cars (SDCs), has attracted significant investments and can potentially contribute to humanity’s flourishing. However, before widespread adoption, it is important to address ethical violations such as bias in AI, highlighted by many …
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Attacking Computer Vision Models Using Occlusion Analysis to Create Physically Robust Adversarial Images
<p>Self-driving cars rely on their sense of sight to function effectively in chaotic and uncontrolled environments. Thanks to recent developments in computer vision, specifically convolutional neural networks, autonomous vehicles have developed the ability to see at or above human-level …
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Free Market on the Free Way
<p>Self-driving cars have the potential to decrease congestion and will probably become the future of efficient transportation. This dissertation presents a unique approach to implement sharing lanes on a freeway using the idea of option pricing. A macroscopic physical model (LWR) is implemented by …
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Towards efficient, on-demand and automated deep learning
… energy efficiency are critical -- for example, self-driving cars, AR/VR kits, internet-of-things devices and mobile phones. This thesis presents a series of in-depth research towards efficient, on-demand and automated deep learning.
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Efficient computing for autonomous navigation using algorithm-and-hardware co-design
… the backbone of many robotic systems, such as self-driving cars and drones. However, state-of-the-art autonomous navigation algorithms are computationally expensive, requiring powerful CPUs and GPUs to enable them to run in real time. As a result, it is prohibitive to deploy them on miniature …
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Efficient nearest-neighbor search algorithms for sub-Riemannian geometries
… academia with the rise of commercial interest in self-driving cars and autonomous aerial vehicles. Among the leading algorithms to tackle the problem are sampling-based planners, such as Probabilistic Road Maps (PRMs), Rapidly-exploring Random Trees (RRTs) and a large number of variants thereof. …
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Cooperative Perception for Connected Vehicles
Self-driving cars promise a future with safer roads and reduced traffic incidents and fatalities. This future hinges on the car's accurate understanding of its surrounding environment; however, the reliability of the algorithms that form this perception is not always guaranteed and adverse traffic …
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Learning from Experience: An Interactive and Ethical Curriculum for Teaching Reinforcement Learning
… in many systems, including online advertising, self-driving cars, and personalized tutoring. There is a corresponding need for education of RL. In my thesis work, I developed activities and materials that teach RL to middle and high school students who don’t necessarily have backgrounds in …
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Affordable autonomous lightweight personal mobility
Self-driving cars and micro-mobility services are among the most important trends in the mobility landscape. While robo-taxi services are still in the pilot phase, residents in many cities today are adopting micro-mobility services as a more affordable and energy-efficient last-mile alternative to …
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Anomalous Motion Detection of Vehicles on Highway using Deep Learning
… anomalies in crowded environments. The advent of self-driving cars provides an opportunity to apply visual anomaly detection in a more dynamic application yet no data set exists to evaluate anomaly detection models in this setting. This thesis presents a novel anomaly detection data set for the …
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PATIENT CLASSIFICATION USING DEEP LEARNING
… has been used in many new technologies such as self-driving cars, natural language processing, and many other automated systems. This research came up with a method that makes use of a deep learning approach and found that it is indeed effective in classifying patients.
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Utilizing GPU tensor cores for algorithmic acceleration
… speech recognition, in healthcare, self-driving cars etc. Matrix Multiplication acceleration has been a popular design choice when creating these specialized units to boost deep learning training and inference. Nvidia's Volta architecture introduced Tensor Cores which promised a 3 …
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Performance evaluation of deep learning on smartphones
… Learning powers a variety of applications from self driving cars and autonomous robotics to web search and voice assistants. It is fair to say that it is omnipresent and here to stay. It is deployed in all sorts of devices ranging from consumer electronics to Internet of Things (IoT). Such a …
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Current and future trends in object detection
… objects is useful in many applications: from self-driving cars, where it allows the car to detect pedestrians, bicyclists, road signs, and other vehicles, to security, where intruding persons can be detected. Though a lot of progress has been made since the conception of the field of Computer …
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