A Study on Scenario Generalization and Optimization for ADS
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.
- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/01487191
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Supplemental Notes:
- Abstract reprinted with permission of SAE International.
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Authors:
- Zhou, Bolin
- Chen, Chen
- Zhai, Yang
- Zhao, Shuai
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Conference:
- SAE 2021 Intelligent and Connected Vehicles Symposium Part II
- Location: Chongqing , China
- Date: 2021-11-4
- Publication Date: 2022-3-31
Language
- English
Media Info
- Media Type: Web
- Features: References;
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Serial:
- SAE Technical Paper
- Publisher: Society of Automotive Engineers (SAE)
- ISSN: 0148-7191
- EISSN: 2688-3627
- Serial URL: http://papers.sae.org/
Subject/Index Terms
- TRT Terms: Cutting; Intelligent vehicles; Optimization; Roads; Simulation
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01842772
- Record Type: Publication
- Source Agency: SAE International
- Report/Paper Numbers: 2022-01-7007
- Files: TRIS, SAE
- Created Date: Apr 19 2022 4:18PM