Towards Realistic, Safety-Critical and Complete Test Case Catalogs for Safe Automated Driving in Urban Scenarios
Author:
Affiliation:
1. the Research Under a JSPS Fellowship for Research in Japan
2. Technische Universität Braunschweig,the Institute of Automotive Engineering,Braunschweig,Germany,38106
3. the Japan Automobile Research Institute,Ibaraki,Japan,305-0822
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10186382/10186383/10186595.pdf?arnumber=10186595
Reference17 articles.
1. An Optimization and Validation Method to Detect the Collision Scenarios and Identifying the Safety Specification of Highly Automated Driving Vehicle
2. Automatic Generation of Safety-Critical Test Scenarios for Collision Avoidance of Road Vehicles
3. Scenario Parameter Generation Method and Scenario Representativeness Metric for Scenario-Based Assessment of Automated Vehicles
4. A Risk-index based Sampling Method to Generate Scenarios for the Evaluation of Automated Driving Vehicle Safety*
5. Interpretable Safety Validation for Autonomous Vehicles
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1. Augmenting Scenario Description Languages for Intelligence Testing of Automated Driving Systems;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02
2. Generation of Ego-Liable Hazardous-Test-Cases for Validating Automated Driving Systems in Junction-Scenes;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02
3. Identification of Critical Scenario Components Based on Driving Database Analysis for Safety Assessment of Automated Driving Systems;Applied Sciences;2023-09-27
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