2 citations · 5 across the 5 of their papers we have counts for
5 papers
LAMBDA: Covering the Multimodal Critical Scenarios for Automated Driving Systems by Search Space Quantization
Xinzheng Wu, Junyi Chen, Xingyu Xing +4
Scenario-based virtual testing is one of the most significant methods to test and evaluate the safety of automated driving systems (ADSs). However, it is impractical to enumerate a…
Hierarchical-level rain image generative model based on GAN
Zhenyuan Liu, Tong Jia, Xingyu Xing +2
Autonomous vehicles are exposed to various weather during operation, which is likely to trigger the performance limitations of the perception system, leading to the safety of the i…
Evolving Testing Scenario Generation Method and Intelligence Evaluation Framework for Automated Vehicles
Yining Ma, Wei Jiang, Lingtong Zhang +5
Interaction between the background vehicles (BVs) and automated vehicles (AVs) in scenario-based testing plays a critical role in evaluating the intelligence of the AVs. Current te…
An Ontology-based Method to Identify Triggering Conditions for Perception Insufficiency of Autonomous Vehicles
Xingyu Xing, Tong Jia, Junyi Chen +2
The autonomous vehicle (AV) is a safety-critical system relying on complex sensors and algorithms. The AV may confront risk conditions if these sensors and algorithms misunderstand…
LAMBDA: Covering the Solution Set of Black-Box Inequality by Search Space Quantization
Lihao Liu, Tianyue Feng, Xingyu Xing +1
Black-box functions are broadly used to model complex problems that provide no explicit information but the input and output. Despite existing studies of black-box function optimiz…