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Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles.

紀錄類型:	書目-電子資源 : 單行本
正題名/作者:	Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles./
作者:	Porcel Magnusson, Cristina.
面頁冊數:	1 online resource ;cm.
附註:	The authors of this document together with the SAE Team responsible for its creation join in expressing our deepest appreciation to all of the individuals who contributed.
標題:	Automated Vehicles. -
電子資源:	點擊此處連結全文 ( Full Text )

Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles.
Porcel Magnusson, Cristina.

Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles. - 1 online resource ;cm.

The authors of this document together with the SAE Team responsible for its creation join in expressing our deepest appreciation to all of the individuals who contributed.

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 instrumentsthe light detection and ranging (LiDAR) sensorfunctions 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 objects 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 objects 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.Subjects--Topical Terms:

1000138172
Automated Vehicles.

Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles.
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520 3 $a 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 instrumentsthe light detection and ranging (LiDAR) sensorfunctions 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 objects 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 objects 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.
520 2 $a SAE EDGE Research Reports provide state-of-the-art and state-of-industry examinations of the most significant topics in mobility engineering. SAE EDGE contributors are experts from research, academia, and industry who have come together to explore and define the most critical advancements, challenges, and future direction in areas such as vehicle automation, unmanned aircraft, IoT and connectivity, cybersecurity, advanced propulsion, and advanced manufacturing.
542 $d SAE International $f � 2021 SAE International. All Rights Reserved.
650 4 $a Automated Vehicles. $3 1000138172
650 4 $a Lidar. $3 1000138271
650 4 $a Sensors and actuators. $3 1000138175
650 4 $a Autonomous vehicles. $3 1000138179
650 4 $a Imaging and visualization. $3 1000138272
650 4 $a Computer software and hardware. $3 1000138221
650 4 $a Coatings, colorants, and finishes. $3 1000138207
772 0 0 $k SAE EDGE Research Report
856 4 0 $z 點擊此處連結全文 ( Full Text ) $u https://doi.org/10.4271/EPR2021002