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Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes./
Author:	Khalkhali, Mohsen.
other author:	Khalighi, Yaser.
Description:	1 online resource ;cm.
Notes:	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.
Subject:	Research and development. -
Online resource:	點擊此處連結全文 ( Full Text )

Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes.
Khalkhali, Mohsen.

Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes. - 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.

Includes bibliographical references.

Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes discusses the unsettled issue of sharing the terabytes of driving data generated by Automated Vehicles (AVs) on a daily basis. Perception engineers use these large datasets to analyze and model the automated driving systems (ADS) that will eventually be integrated into future "self-driving" vehicles. However, the current industry practices of collecting data by driving on public roads to understand real-world scenarios is not practical and will be unlikely to lead to safe deployment of this technology anytime soon. Estimates show that it could take 400 years for a fleet of 100 AVs to drive enough miles to prove that they are as safe as human drivers. Yet, data-sharing can be developed as a technology, culture, and business and allow for rapid generation and testing of the billions of possible scenarios that are needed to prove practicality and safety of an ADS resulting in lower research and development costs to the industry. Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes explores how this could lead to better regulation, insurance, public acceptance and finally, shorter technology development cycles. Finding a business case and changing to an open data culture are not going to be easy tasks, but data sharing is the only way forward for the whole industry to move to the next phase of deployment after nearly a decade of intense research.Subjects--Topical Terms:

1000138173
Research and development.

Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes.
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504 1 $a Includes bibliographical references.
520 3 $a Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes discusses the unsettled issue of sharing the terabytes of driving data generated by Automated Vehicles (AVs) on a daily basis. Perception engineers use these large datasets to analyze and model the automated driving systems (ADS) that will eventually be integrated into future "self-driving" vehicles. However, the current industry practices of collecting data by driving on public roads to understand real-world scenarios is not practical and will be unlikely to lead to safe deployment of this technology anytime soon. Estimates show that it could take 400 years for a fleet of 100 AVs to drive enough miles to prove that they are as safe as human drivers. Yet, data-sharing can be developed as a technology, culture, and business and allow for rapid generation and testing of the billions of possible scenarios that are needed to prove practicality and safety of an ADS resulting in lower research and development costs to the industry. Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes explores how this could lead to better regulation, insurance, public acceptance and finally, shorter technology development cycles. Finding a business case and changing to an open data culture are not going to be easy tasks, but data sharing is the only way forward for the whole industry to move to the next phase of deployment after nearly a decade of intense research.
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 Research and development. $3 1000138173
650 4 $a Automated Vehicles. $3 1000138172
650 4 $a Data acquisition and handling. $3 1000138288
650 4 $a Fleets. $3 1000138193
650 4 $a Regulations. $3 1000138219
650 4 $a Mobility. $3 1000138177
700 1 $a Khalighi, Yaser. $3 1000138287
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856 4 0 $z 點擊此處連結全文 ( Full Text ) $u https://doi.org/10.4271/EPR2020007