A Quantitative Approach of Generating Challenging Testing Scenarios Based on Functional Safety Standard
With the rapid development of intelligent vehicle safety verification, scenario-based testing methods have received increasing attention. As the space of driving scenarios is vast, the challenge in scenario-based testing is the generation and selection of high-value testing scenarios to reduce the d...
Main Authors: | Kang Meng, Rui Zhou, Zhiheng Li, Kai Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-03-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/6/3494 |
Similar Items
-
Review on Functional Testing Scenario Library Generation for Connected and Automated Vehicles
by: Yu Zhu, et al.
Published: (2022-10-01) -
A Survey on Data-Driven Scenario Generation for Automated Vehicle Testing
by: Jinkang Cai, et al.
Published: (2022-11-01) -
Boundary Scenario Generation for HAVs Based on Classification and Local Sampling
by: Jinkang Cai, et al.
Published: (2023-03-01) -
Scenario Generation for Autonomous Vehicles with Deep-Learning-Based Heterogeneous Driver Models: Implementation and Verification
by: Li Gao , et al.
Published: (2023-05-01) -
Automatic Generation System for Autonomous Driving Simulation Scenarios Based on PreScan
by: Liling Cao, et al.
Published: (2024-02-01)