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The expansion of deployed traffic monitoring systems and information transmission is a crucial step towards increasing the efficiency, reliability and safety of vehicular transportation. Under the current context in terrestrial transportation, the implementation of real-time traffic analysis mechanisms can provide more insight into the network, leading to better informed decisions on how to direct traffic and plan roadways. In the future, as we move towards the integration of fully autonomous vehicles to a transportation network with human drivers, the extraction and processing of real time data will become even more crucial to ensure safe transition. In this paper we present a real time data analysis system for in-flight vehicle detection as an option for the expansion of traffic monitoring. The presented solution is able to perform typical post-flight processing in real time, with minimal computational and power requirements, which allows its implementation on light-weight UAS. It utilizes adaptive segmentation and 3D convolutions that take advantage of the structure of the LiDAR point cloud, to identify vehicles and their respective positions within 3D point cloud segments that may include background clutter. All the necessary positioning information required to run the algorithm are introduced along with a detailed description for the computational steps extracting the desired features from the raw data. We provide the timing constraints for the system and evaluate its performance while considering different optimization variables and computation capabilities.
LiDAR (or airborne laser scanning) systems became a dominant player in high-precision spatial data acquisition to efficiently create DEM/DSM in the late 90's. With increasing point density, new systems are now able to support object extraction, such as extracting building and roads, from LiDAR data. The novel concept of this project was to use LiDAR data for traffic flow estimates. In a sense, extracting vehicles over transportation corridors represents the next step in complexity by adding the temporal component to the LiDAR data feature extraction process. The facts are that vehicles are moving at highway speeds and the scanning acquisition mode of the LiDAR certainly poses a serious challenge for the data extraction process. The OSU developed method and its implementation, the I FLOW program, have demonstrated that LiDAR data contain valuable information to support vehicle extraction, including vehicle grouping and localizations. The classification performance showed strong evidence that the major vehicle categories can be efficiently separated. The I FLOW program is ready for deployment.
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.
The growing market penetration of Internet mapping, satellite imaging and personal navigation has opened up great research and business opportunities to geospatial communities. Multi-platform and multi-sensor integrated mapping technology has clearly established a trend towards fast geospatial data acquisition. Sensors can be mounted on various pla
" TRB's National Cooperative Highway Research Program (NCHRP) Report 748: Guidelines for the Use of Mobile LIDAR in Transportation Applications presents guidelines for the application of mobile 3D light detection and ranging (LIDAR) technology to the operations of state departments of transportation. Mobile LIDAR uses laser scanning equipment mounted on vehicles in combination with global positioning systems (GPS) and inertial measurement units (IMU) to rapidly and safely capture large datasets necessary to create highly accurate, high resolution digital representations of roadways and their surroundings. " -- Publisher's description.
The fusion of drones and Industry 5.0 has emerged as a transformative force, redefining the landscape of industrial progress. Drone Applications for Industry 5.0 reveals the strong connection between drones and Industry 5.0, exploring how they come together to blend human skills with automated precision. As we stand on the horizon of the fifth industrial revolution, Industry 5.0 uniquely celebrates the return of the human touch, harmonizing the strengths of machines with human intuition and empathy. Drones play a pivotal role in shaping this evolutionary transition. The narrative unfolds against the backdrop of historical industrial revolutions, each marked by radical transformations. Unlike its predecessors, Industry 5.0 places humans at the center, emphasizing collaboration with machines. Drones have matured into invaluable instruments with applications spanning manufacturing, agriculture, transportation, and emergency services. Drone Applications for Industry 5.0 embarks on a journey, guiding scholars, researchers, and students through the foundations of Industry 5.0 and the mechanics of drones. It explores practical uses in various fields, offering both theory and practical insights which empowers professionals to fully utilize drones.
IAG Symposium, Cairns, Australia, 22-26 August, 2005
These proceedings summarize the highlights from the Conference on Remote Sensing for Transportation--Products and Results: Foundations for the Future. This was the second in a series of three conferences on the subject of remote sensing in transportation. The objectives of this conference were: (1) Enhancing communication between the transportation and remote sensing communities; (2) Developing a common understanding of current successful applications of remote sensing to transportation; and (3) Crafting strategies for implementation of remote sensing in transportation. More than 150 people attended the conference, with representation from state departments of transportation, metropolitan planning organizations, local government, the U.S. Department of Transportation, other federal agencies, universities, the private sector, and other organizations. The proceedings consist of a Foreward and Introduction to the Proceedings, comments on the structure of the 2001 conference and proceedings, summaries of the 7 sessions, and the following appendices: (A) Summary of Roundtable for States and Metropolitan Planning Organizations; (B) Conference Workshop Information; (C) Listing of Technology Buffet Displays; (D) Abbreviations and Acronyms; and (E) Conference Participants.