A Study on Scenario Generalization and Optimization for ADS

2022-01-7007

3/31/2022

Authors
Abstract
Content
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.
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DOI
https://doi.org/10.4271/2022-01-7007
Citation
Zhou, B., Chen, C., Zhai, Y., and Zhao, S., "A Study on Scenario Generalization and Optimization for ADS," SAE 2021 Intelligent and Connected Vehicles Symposium Part II, Chongqing, China, November 4, 2021, https://doi.org/10.4271/2022-01-7007.
Additional Details
Publisher
Published
3/31/2022
Product Code
2022-01-7007
Content Type
Technical Paper
Language
English