Safety Performance Boundary Identification of Highly Automated Vehicles: A Surrogate Model-Based Gradient Descent Searching Approach-Reference-Cited by-同舟云学术

Safety Performance Boundary Identification of Highly Automated Vehicles: A Surrogate Model-Based Gradient Descent Searching Approach

Published:2022-12 Issue:12 Volume:23 Page:23809-23820
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Wang Yiyun¹^ORCID,Yu Rongjie¹,Qiu Shuhan¹,Sun Jian¹^ORCID,Farah Haneen²^ORCID

Affiliation:

1. Key Laboratory of Road and Traffic Engineering, Ministry of Education, and the College of Transportation Engineering, Tongji University, Shanghai, China

2. Department of Transport and Planning, Delft University of Technology, Delft, CD, The Netherlands

Funder

Chinese National Natural Science Foundation

Shanghai Education Development Foundation and Shanghai Municipal Education Commission under the Shanghai Municipal Science and Technology Major Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/9972869/09837787.pdf?arnumber=9837787

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5. Testing of autonomous vehicles using surrogate models and stochastic optimization

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