ANTI-CARLA: An Adversarial Testing Framework for Autonomous Vehicles in CARLA
Author:
Affiliation:
1. Institute for Software Integrated Systems, Vanderbilt University,Nashville,TN,USA,37212
2. Technical University of Munich,Department of Electrical and Computer Engineering,Munich,Germany,80333
Funder
DARPA
Air Force Research Laboratory
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9921415/9921739/09921776.pdf?arnumber=9921776
Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Dance of the ADS: Orchestrating Failures through Historically-Informed Scenario Fuzzing;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11
2. CARLOS: An Open, Modular, and Scalable Simulation Framework for the Development and Testing of Software for C-ITS;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02
3. Evaluation and Optimization of Adaptive Cruise Control in Autonomous Vehicles using the CARLA Simulator: A Study on Performance under Wet and Dry Weather Conditions;2024 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET);2024-04-27
4. Learning to Verify and Assure Cyber-Physical Systems;AIAA SCITECH 2024 Forum;2024-01-04
5. Discovery and Analysis of Rare High-Impact Failure Modes Using Adversarial RL-Informed Sampling;Lecture Notes in Computer Science;2024
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