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A Study on Scenario Generalization and Optimization for ADS
Technical Paper
2022-01-7007
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
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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Citation
Zhou, B., Chen, C., Zhai, Y., and Zhao, S., "A Study on Scenario Generalization and Optimization for ADS," SAE Technical Paper 2022-01-7007, 2022, https://doi.org/10.4271/2022-01-7007.Also In
References
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