Online Adaptive Generation of Critical Boundary Scenarios for Evaluation of Autonomous Vehicles
Author:
Affiliation:
1. Department of Automation, Shanghai Jiao Tong University, Shanghai, China
Funder
National Natural Science Foundation of China
Automotive Industry Science and Technology Development Foundation of Shanghai
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/10139322/10056393.pdf?arnumber=10056393
Reference49 articles.
1. Failure-Scenario Maker for Rule-Based Agent using Multi-agent Adversarial Reinforcement Learning and its Application to Autonomous Driving
2. Automated generation of diverse and challenging scenarios for test and evaluation of autonomous vehicles
3. Adversarial Attack Against Urban Scene Segmentation for Autonomous Vehicles
4. Multi-Source Adversarial Sample Attack on Autonomous Vehicles
5. Adaptive generation of challenging scenarios for testing and evaluation of autonomous vehicles
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