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A Study on Scenario Generalization and Optimization for ADS Automotive Data of China (Tianjin) Company, Limited

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Zhou, Bolin, author.
Contributor:
Chen, Chen
Zhai, Yang
Zhao, Shuai
Conference Name:
SAE 2021 Intelligent and Connected Vehicles Symposium Part II (2021-11-04 : Chongqing, China)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2022
Summary:
The development of automated driving systems and functions requires a tremendous amount of testing. The function oriented and data driven approaches made a huge leap forward in the field. As one of the major markets for the automotive industry, China is also evolving as a major player. Any company in any country can benefit from simulation testing with a free standard-suite focusing on simulation and beyond. The complexity of scenarios across the globe with their divergence road users and wide-ranging parameters creates the need for powerful and broadly-applied standards in the future. In this paper, it provided a method with the given cut in examples on how this procedure could be implemented and used in a broader manner
Notes:
Vendor supplied data
Publisher Number:
2022-01-7007
Access Restriction:
Restricted for use by site license

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