GIS Data Based Automatic High-Fidelity 3D Road Network Modeling

3D road models are widely used in many computer applications such as racing games and driving simulations_ However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially those existing in the real world. This paper presents a novel approach thai can automatically produce 3D high-fidelity road network models from real 2D road GIS data that mainly contain road. centerline in formation. The proposed method first builds parametric representations of the road centerlines through segmentation and fitting . A basic set of civil engineering rules (e.g., cross slope, superelevation, grade) for road design are then selected in order to generate realistic road surfaces in compliance with these rules. While the proposed method applies to any types of roads, this paper mainly addresses automatic generation of complex traffic interchanges and intersections which are the most sophisticated elements in the road network

Automatic High-Fidelity 3D Road Network Modeling

Many computer applications such as racing games and driving simulations frequently make use of 3D high-fidelity road network models for a variety of purposes. However, there are very few existing methods for automatic generation of 3D realistic road networks, especially for those in the real world. On the other hand, vast road network GIS data have been collected in the past and used by a wide range of applications, such as navigation and evaluation. A method that can automatically produce 3D high-fidelity road network models from 2D real road GIS data will significantly reduce both the labor and time needed to generate these models, and greatly benefit numerous applications involving road networks. Based on a set of selected civil engineering rules for road design, this dissertation research addresses this problem with a novel approach which transforms existing road GIS data that contain only 2D road centerline information into 3D road network models. The proposed method consists of several components, mainly including road GIS data preprocessing, 3D centerline modeling and 3D geometry modeling. During road data preprocessing, topology of the road network is extracted from raw road data as a graph composed of road nodes and road links; road link information is simplified and classified. In the 3D centerline modeling part, the missing height information of the road centerline is inferred based on 2D road GIS data, intersections are extracted from road nodes and the whole road network is represented as road intersections and road segments in parametric forms. Finally, the 3D road centerline models are converted into various 3D road geometry models consisting of triangles and textures in the 3D geometry modeling phase. With this approach, basic road elements such as road segments, road intersections and traffic interchanges are generated automatically to compose sophisticated road networks. Results show that this approach provides a rapid and efficient 3D road modeling method for applications that have stringent requirements on high-fidelity road models

Simulation and Learning for Urban Mobility: City-scale Traffic Reconstruction and Autonomous Driving

Traffic congestion has become one of the most critical issues worldwide. The costs due to traffic gridlock and jams are approximately $160 billion in the United States, more than £13 billion in the United Kingdom, and over one trillion dollars across the globe annually. As more metropolitan areas will experience increasingly severe traffic conditions, the ability to analyze, understand, and improve traffic dynamics becomes critical. This dissertation is an effort towards achieving such an ability. I propose various techniques combining simulation and machine learning to tackle the problem of traffic from two perspectives: city-scale traffic reconstruction and autonomous driving. Traffic, by its definition, appears in an aggregate form. In order to study it, we have to take a holistic approach. I address the problem of efficient and accurate estimation and reconstruction of city-scale traffic. The reconstructed traffic can be used to analyze congestion causes, identify network bottlenecks, and experiment with novel transport policies. City-scale traffic estimation and reconstruction have proven to be challenging for two particular reasons: first, traffic conditions that depend on individual drivers are intrinsically stochastic; second, the availability and quality of traffic data are limited. Traditional traffic monitoring systems that exist on highways and major roads can not produce sufficient data to recover traffic at scale. GPS data, in contrast, provide much broader coverage of a city thus are more promising sources for traffic estimation and reconstruction. However, GPS data are limited by their spatial-temporal sparsity in practice. I develop a framework to statically estimate and dynamically reconstruct traffic over a city-scale road network by addressing the limitations of GPS data. Traffic is also formed of individual vehicles propagating through space and time. If we can improve the efficiency of them, collectively, we can improve traffic dynamics as a whole. Recent advancements in automation and its implication for improving the safety and efficiency of the traffic system have prompted widespread research of autonomous driving. While exciting, autonomous driving is a complex task, consider the dynamics of an environment and the lack of accurate descriptions of a desired driving behavior. Learning a robust control policy for driving remains challenging as it requires an effective policy architecture, an efficient learning mechanism, and substantial training data covering a variety of scenarios, including rare cases such as accidents. I develop a framework, named ADAPS (Autonomous Driving via Principled Simulations), for producing robust control policies for autonomous driving. ADAPS consists of two simulation platforms which are used to generate and analyze simulated accidents while automatically generating labeled training data, and a hierarchical control policy which takes into account the features of driving behaviors and road conditions. ADAPS also represents a more efficient online learning mechanism compared to previous techniques, in which the number of iterations required to learn a robust control policy is reduced.Doctor of Philosoph

SIMULATING, RECONSTRUCTING, AND ROUTING METROPOLITAN-SCALE TRAFFIC

Few phenomena are more ubiquitous than traffic, and few are more significant economically, socially, or environmentally. The vast, world-spanning road network enables the daily commutes of billions of people and makes us mobile in a way our ancestors would have envied. And yet, few systems perform so poorly so often. Gridlock and traffic jams cost 2.9 billion gallons of wasted fuel and costs over 121 billion dollars every year in the U.S. alone. One promising approach to improving the reliability and efficiency of traffic systems is to fully incorporate computational techniques into the system, transforming the traffic systems of today into cyber-physical systems. However, creating a truly cyber-physical traffic system will require overcoming many substantial challenges. The state of traffic at any given time is unknown for the majority of the road network. The dynamics of traffic are complex, noisy, and dependent on drivers' decisions. The domain of the system, the real-world road network, has no suitable representation for high-detail simulation. And there is no known solution for improving the efficiency and reliability of the system. In this dissertation, I propose techniques that combine simulation and data to solve these challenges and enable large-scale traffic state estimation, simulation, and route planning. First, to create and represent road networks, I propose an efficient method for enhancing noisy GIS road maps to create geometrically and topologically consistent 3D models for high-detail, real-time traffic simulation, interactive visualization, traffic state estimation, and vehicle routing. The resulting representation provides important road features for traffic simulations, including ramps, highways, overpasses, merge zones, and intersections with arbitrary states. Second, to estimate and communicate traffic conditions, I propose a fast technique to reconstruct traffic flows from in-road sensor measurements or user-specified control points for interactive 3D visualization and communication. My algorithm estimates the full state of the traffic flow from sparse sensor measurements using a statistical inference method and a continuum traffic model. This estimated state then drives an agent-based traffic simulator to produce a 3D animation of traffic that statistically matches the sensed traffic conditions. Third, to improve real-world traffic system efficiency, I propose a novel approach that takes advantage of mobile devices, such as cellular phones or embedded systems in cars, to form an interactive, participatory network of vehicles that plan their travel routes based on the current, sensed traffic conditions and the future, projected traffic conditions, which are estimated from the routes planned by all the participants. The premise of this approach is that a route, or plan, for a vehicle is also a prediction of where the car will travel. If routes are planned for a sizable percentage of the vehicles using the road network, an estimate for the overall traffic pattern is attainable. If fewer cars are being coordinated, their impact on the traffic conditions can be combined with sensor-based estimations. Taking planned routes into account as predictions allows the entire traffic route planning system to better distribute vehicles and to minimize traffic congestion. For each of these challenges, my work is motivated by the idea of fully integrating traffic simulation, as a model for the complex dynamics of real world traffic, with emerging data sources, including real-time sensor and public survey data.Doctor of Philosoph

Complex Adaptive Systems & Urban Morphogenesis:

This thesis looks at how cities operate as Complex Adaptive Systems (CAS). It focuses on how certain characteristics of urban form can support an urban environment's capacity to self-organize, enabling emergent features to appear that, while unplanned, remain highly functional. The research is predicated on the notion that CAS processes operate across diverse domains: that they are ‘generalized' or ‘universal'. The goal of the dissertation is then to determine how such generalized principles might ‘play out' within the urban fabric. The main thrust of the work is to unpack how elements of the urban fabric might be considered as elements of a complex system and then identify how one might design these elements in a more deliberate manner, such that they hold a greater embedded capacity to respond to changing urban forces. The research is further predicated on the notion that, while such responses are both imbricated with, and stewarded by human actors, the specificities of the material characteristics themselves matter. Some forms of material environments hold greater intrinsic physical capacities (or affordances) to enact the kinds of dynamic processes observed in complex systems than others (and can, therefore, be designed with these affordances in mind). The primary research question is thus:   What physical and morphological conditions need to be in place within an urban environment in order for Complex Adaptive Systems dynamics arise - such that the physical components (or ‘building blocks') of the urban environment have an enhanced capacity to discover functional configurations in space and time as a response to unfolding contextual conditions?   To answer this question, the dissertation unfolds in a series of parts. It begins by attempting to distill the fundamental dynamics of a Complex Adaptive System. It does so by means of an extensive literature review that examines a variety of highly cited ‘defining principles' or ‘key attributes' of CAS. These are cross-referenced so as to extract common features and distilled down into six major principles that are considered as the generalized features of any complex system, regardless of domain. In addition, this section considers previous urban research that engages complexity principles in order to better position the distinctive perspective of this thesis. This rests primarily on the dissertation's focus on complex urban processes that occur by means of materially enabled in situ processes. Such processes have, it is argued, remained largely under-theorized. The opening section presents introductory examples of what might be meant by a ‘materially enabling' environment.   The core section of the research then undertakes a more detailed unpacking of how complex processes can be understood as having a morphological dimension. This section begins by discussing, in broad terms, the potential ‘phase space' of a physical environment and how this can be expanded or limited according to a variety of factors. Drawing insights from related inquiries in the field of Evolutionary Economic Geography, the research argues that, while emergent capacity is often explored in social, economic, or political terms, it is under-theorized in terms of the concrete physical sub-strata that can also act to ‘carry' or ‘moor' CAS dynamics. This theme is advanced in the next article, where a general framework for speaking about CAS within urban environments is introduced. This framework borrows from the terms for ‘imageability' that were popularized by Kevin Lynch: paths, edges, districts, landmarks, and nodes. These terms are typically associated with physical or ‘object-like features' of the urban environment – that is to say, their image. The terminology is then co-opted such that it makes reference not simply to physical attributes, but rather to the complex processes these attributes enable. To advance this argument, the article contrasts the static and ‘imageable' qualities of New Urbanism projects with the ‘unfolding' and dynamic qualities of complex systems - critiquing NU proponents as failing to appreciate the underlying forces that generate the environments they wish to emulate. Following this, the efficacy of the re-purposed ‘Lynchian' framework is tested using the case study of Istanbul's Grand Bazaar. Here, specific elements of the Bazaar's urban fabric are positioned as holding material agency that enables particular emergent spatial phenomena to manifest. In addition, comparisons are drawn between physical dynamics unfolding within the Bazaar's morphological setting (leading to emergent merchant districts) and parallel dynamics explored within Evolutionary Economic Geography).   The last section of the research extends this research to consider digitally augmented urban elements that hold an enhanced ability to receive and convey information. A series of speculative thought-experiments highlight how augmented urban entities could employ CAS dynamics to ‘solve for' different kinds of urban optimization scenarios, leading these material entities to self-organize (with their users) and discover fit regimes. The final paper flips the perspective, considering how, not only material agency, but also human agency is being augmented by new information processing technologies (smartphones), and how this can lead to new dances of agency that in turn generate novel emergent outcomes.   The dissertation is based on a compilation of articles that have, for the most part, been published in academic journals and all the research has been presented at peer-reviewed academic conferences. An introduction, conclusion, and explanatory transitions between sections are provided in order to clarify the narrative thread between the sections and the articles. Finally, a brief ‘coda' on the spatial dynamics afforded by Turkish Tea Gardens is offered

Unmanned Vehicle Systems & Operations on Air, Sea, Land

Unmanned Vehicle Systems & Operations On Air, Sea, Land is our fourth textbook in a series covering the world of Unmanned Aircraft Systems (UAS) and Counter Unmanned Aircraft Systems (CUAS). (Nichols R. K., 2018) (Nichols R. K., et al., 2019) (Nichols R. , et al., 2020)The authors have expanded their purview beyond UAS / CUAS systems. Our title shows our concern for growth and unique cyber security unmanned vehicle technology and operations for unmanned vehicles in all theaters: Air, Sea and Land – especially maritime cybersecurity and China proliferation issues. Topics include: Information Advances, Remote ID, and Extreme Persistence ISR; Unmanned Aerial Vehicles & How They Can Augment Mesonet Weather Tower Data Collection; Tour de Drones for the Discerning Palate; Underwater Autonomous Navigation & other UUV Advances; Autonomous Maritime Asymmetric Systems; UUV Integrated Autonomous Missions & Drone Management; Principles of Naval Architecture Applied to UUV’s; Unmanned Logistics Operating Safely and Efficiently Across Multiple Domains; Chinese Advances in Stealth UAV Penetration Path Planning in Combat Environment; UAS, the Fourth Amendment and Privacy; UV & Disinformation / Misinformation Channels; Chinese UAS Proliferation along New Silk Road Sea / Land Routes; Automaton, AI, Law, Ethics, Crossing the Machine – Human Barrier and Maritime Cybersecurity.Unmanned Vehicle Systems are an integral part of the US national critical infrastructure The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. Unmanned Vehicle (UV) Systems & Operations On Air, Sea, Land discusses state-of-the-art technology / issues facing U.S. UV system researchers / designers / manufacturers / testers. We trust our newest look at Unmanned Vehicles in Air, Sea, and Land will enrich our students and readers understanding of the purview of this wonderful technology we call UV.https://newprairiepress.org/ebooks/1035/thumbnail.jp

Scenography and new media technologies: history, educational applications and visualization techniques

The endemic presence of digital technology is responsible for numerous changes in contemporary Western societies. This study examines the role of multimedia within the field of theatre studies, with particular focus on the theory and practice of theatre design and education. In the cross-disciplinary literature review, I investigate such primary elements of contemporary media as interactivity, immersion, integration and hyper-textuality, and explore their characteristics in the performing arts before and during the digital epoch. I also discuss various IT applications that transformed the way we experience, learn and co-create our cultural heritage. In order to illustrate how computer-generated environments could change the way we perceive and deliver cultural values, I explore a suite of rapidly-developing communication and computer-visualization techniques, which enable reciprocal exchange between viewers, theatre performances and artefacts. I analyze novel technology-mediated teaching techniques that attempt to provide a new media platform for visually-enhanced information transfer. My findings indicate that the recent changes towards the personalization of knowledge delivery and also towards student-centered study and e-learning necessitated the transformation of the learners from passive consumers of digital products to active and creative participants in the learning experience. The analysis of questionnaires and two case studies (the THEATRON and the VA projects) demonstrate the need for further development of digital-visualization techniques, especially for studying and researching scenographic artefacts. As a practical component of this thesis, I have designed and developed the Set-SPECTRUM educational project, which aims to strengthen the visual skills of the students, ultimately enabling them to use imagery as a creative tool, and as a means to analyze theatrical performances and artefacts. The 3D reconstruction of Norman Bel Geddes' set for The Divine Comedy, first of all, enables academic research of the artefact, exposing some hitherto unknown design-limitations in the original set-model, and revealing some construction inconsistencies; secondly, it contributes to educational and creative practices, offering an innovative way to learn about scenography. And, thirdly, it fills a gap in the history of the Western theatre design. This study attempts to show that when translated into digital language, scenographic artefacts become easily retrievable and highly accessible for learning and research purposes. Therefore, the development of such digital products should be encouraged, but care should also be taken to provide the necessary training for users, in order to realize the applications' full potential

The state of the art of practice in Tom Kovac's architecture of the real and virtual

This PhD by Publication project is based on research examining reflectively my practice. It includes a summary of my practice, its themes of inquiry and modes of production. The invitation has generated an investigation into my way of practicing and into its concerns. The research explores key areas of interest: Virtual Architecture, Object Architecture and the spatialisation of information. This research investigation the operations and processes of my practice to date. The development of my practice has been mapped and this catalogue illustrates the disparate parts and associations that frame each project. The evolution of the practice through three key periods of change is documented revealing the transitions through various stages of practice. The work is presented through an interactive tool that captures the concerns that informed the core systems, that informed the projects. The PhD closely scrutinises the makings of projects and their concerns and reveals the makings of the practice. To structure these processes I have created a series of categorisations and strategic associations and have assembled projects into networks of cells. These categories can be read as connections linking five primary functions as the tools for a web based app or application. This app was instigated as data visualisation tool and as a system for analytically referencing networks of projects that make up the structure of the practice: past, present and future