Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles

Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles
Author: Cristina P. Magnusson
Publisher:
Total Pages: 42
Release: 2021-01-18
Genre:
ISBN: 9781468602838

Autonomous vehicles (AVs) utilize multiple devices, like high-resolution cameras and radar sensors, to interpret the driving environment and achieve full autonomy. One of these instruments-the light detection and ranging (LiDAR) sensor-functions like radar, but utilizes pulsed infrared (IR) light, typically at wavelengths of 905 nm or 1,550 nm. The LiDAR sensor receives the reflected light from objects and calculates each object's distance and position. In current vehicles, the exterior automotive paint system covers an area larger than any other exterior material. Therefore, understanding how LiDAR wavelengths interact with other vehicles' coatings is extremely important for the safety of future automated driving technologies. Some coatings are more easily detected by LiDAR than others. In general, dark colors can absorb as much as 95% of the incident LiDAR intensity, reducing the amount of signal reflected toward the sensor. White cars are more easily detected as they exhibit high IR reflectivity. Many other factors like gloss level, effect pigments, and refinishes can affect reflectivity and even blind LiDAR sensors. On the other hand, several variables define overall LiDAR and perception system performance, including IR reflectivity of paint but also the target object's geometry, the type of LiDAR technology employed, angle of the target surface, environmental conditions, and sensor fusion software architecture. Sensing Technologies and Materials are two different industries that have not directly interacted in the perception and system sense. With the new applications in the AV industry, approaches need to be taken in a multidisciplinary way to ensure a reliable and safe technology for the future. This report provides a transversal view of the different industry segments from pigment and coating manufacturers to LiDAR component and vehicle system development and integration, and a structured decomposition of the different variables and technologies involved. NOTE: SAE EDGE Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. These reports are not intended to resolve the challenges they identify or close any topic to further scrutiny.

Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles

Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles
Author: Cristina Porcel Magnusson
Publisher: SAE International
Total Pages: 40
Release: 2021-01-18
Genre: Technology & Engineering
ISBN: 1468603744

Autonomous vehicles (AVs) utilize multiple devices, like high-resolution cameras and radar sensors, to interpret the driving environment and achieve full autonomy. One of these instruments—the light detection and ranging (LiDAR) sensor—functions like radar, but utilizes pulsed infrared (IR) light, typically at wavelengths of 905 nm or 1,550 nm. The LiDAR sensor receives the reflected light from objects and calculates each object’s distance and position. In current vehicles, the exterior automotive paint system covers an area larger than any other exterior material. Therefore, understanding how LiDAR wavelengths interact with other vehicles’ coatings is extremely important for the safety of future automated driving technologies. Some coatings are more easily detected by LiDAR than others. In general, dark colors can absorb as much as 95% of the incident LiDAR intensity, reducing the amount of signal reflected toward the sensor. White cars are more easily detected as they exhibit high IR reflectivity. Many other factors like gloss level, effect pigments, and refinishes can affect reflectivity and even blind LiDAR sensors. On the other hand, several variables define overall LiDAR and perception system performance, including IR reflectivity of paint but also the target object’s geometry, the type of LiDAR technology employed, angle of the target surface, environmental conditions, and sensor fusion software architecture. Sensing Technologies and Materials are two different industries that have not directly interacted in the perception and system sense. With the new applications in the AV industry, approaches need to be taken in a multidisciplinary way to ensure a reliable and safe technology for the future. This report provides a transversal view of the different industry segments from pigment and coating manufacturers to LiDAR component and vehicle system development and integration, and a structured decomposition of the different variables and technologies involved. NOTE: SAE EDGE Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. These reports are not intended to resolve the challenges they identify or close any topic to further scrutiny. https://doi.org/10.4271/EPR2021002

Next-generation Sensors for Automated Road Vehicles

Next-generation Sensors for Automated Road Vehicles
Author: Sven Beiker
Publisher: SAE International
Total Pages: 26
Release: 2023-02-20
Genre: Technology & Engineering
ISBN: 1468605615

This follow-up report to the inaugural SAE EDGE Research Report on “Unsettled Topics Concerning Sensors for Automated Road Vehicles” reviews the progress made in automated vehicle (AV) sensors over the past four to five years. Additionally, it addresses persistent disagreement and confusion regarding certain terms for describing sensors, the different strengths and shortcomings of particular sensors, and procedures regarding how to specify and evaluate them. Next-gen Automated Road Vehicle Sensors summarizes current trends and debates (e.g., sensor fusion, embedded AI, simulation) as well as future directions and needs. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2023003

Hexagon (KH-9) Mapping Camera Program and Evolution

Hexagon (KH-9) Mapping Camera Program and Evolution
Author: Maurice G. Burnett
Publisher:
Total Pages: 386
Release: 2012
Genre: Artificial satellites, American
ISBN:

The United States developed the Gambit and Hexagon programs to improve the nation's means for peering over the iron curtain that separated western democracies from east European and Asian communist countries. The inability to gain insight into vast "denied areas" required exceptional systems to understand threats posed by US adversaries. Corona was the first imagery satellite system to help see into those areas. Hexagon began as a Central Intelligence Agency (CIA) program with the first concepts proposed in 1964. The CIA's primary goal was to develop an imagery system with Corona-like ability to image wide swaths of the earth, but with resolution equivalent to Gambit. Such a system would afford the United States even greater advantages monitoring the arms race that had developed with the nation's adversaries. The Hexagon mapping camera flew on 12 of the 20 Hexagon missions. It proved to be a remarkably efficient and prodigious producer of imagery for mapping purposes. The mapping camera system was successful by every standard including technical capabilities, reliability, and capacity.

Interpreting Archaeological Topography

Interpreting Archaeological Topography
Author: David Cowley
Publisher: Oxbow Books Limited
Total Pages: 0
Release: 2013
Genre: Archaeological surveying
ISBN: 9781842175163

Airborne Laser Scanning (ALS), or lidar, is an enormously important innovation for data collection and interpretation in archaeology. The application of archaeological 3D data deriving from sources including ALS, close-range photogrammetry and terrestrial and photogrammetric scanners has grown exponentially over the last decade. Such data present numerous possibilities and challenges, from ensuring that applications remain archaeologically relevant, to developing practices that integrate the manipulation and interrogation of complex digital datasets with the skills of archaeological observation and interpretation. This volume addresses the implications of multi-scaled topographic data for contemporary archaeological practice in a rapidly developing field, drawing on examples of ongoing projects and reflections on best practice. Twenty papers from across Europe explore the implications of these digital 3D datasets for the recording and interpretation of archaeological topography, whether at the landscape, site or artifact scale. The papers illustrate the variety of ways in which we engage with archaeological topography through 3D data, from discussions of its role in landscape archaeology, to issues of context and integration, and to the methodological challenges of processing, visualization and manipulation. Critical reflection on developing practice and implications for cultural resource management and research contextualize the case studies and applications, illustrating the diverse and evolving roles played by multi-scalar topographic data in contemporary archaeology.

Machine Learning for Decision Makers

Machine Learning for Decision Makers
Author: Patanjali Kashyap
Publisher: Apress
Total Pages: 381
Release: 2018-01-04
Genre: Computers
ISBN: 1484229886

Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other. This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making. The book uses case studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business. What You Will Learn Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learning Absorb machine-learning best practices Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.

Forensic Archaeology

Forensic Archaeology
Author: Kimberlee Sue Moran
Publisher: Springer
Total Pages: 338
Release: 2019-01-24
Genre: Social Science
ISBN: 3030032914

This book presents the multidisciplinary field of forensic archaeology as complementary but distinct from forensic anthropology. By looking beyond basic excavation methods and skeletal analyses, this book presents the theoretical foundations of forensic archaeology, novel contexts and applications, and demonstrative case studies from practitioners active in the field. Many of the chapters present new approaches and methods not previously covered in other forensic archaeology books, some of which may be of direct use to those conducting criminal investigations.