Recent advancements in end-to-end autonomous driving using deep learning: A survey
End-to-End driving is a promising paradigm as it circumvents the drawbacks associated with
modular systems, such as their overwhelming complexity and propensity for error …
modular systems, such as their overwhelming complexity and propensity for error …
Scenario-based test automation for highly automated vehicles: A review and paving the way for systematic safety assurance
Highly Automated Vehicles (HAVs) must undergo strict safety testing before being released
to the public. Mileage-based on-road testing suffers from unaffordable time costs and high …
to the public. Mileage-based on-road testing suffers from unaffordable time costs and high …
A survey on automated driving system testing: Landscapes and trends
Automated Driving Systems (ADS) have made great achievements in recent years thanks to
the efforts from both academia and industry. A typical ADS is composed of multiple modules …
the efforts from both academia and industry. A typical ADS is composed of multiple modules …
A survey on scenario-based testing for automated driving systems in high-fidelity simulation
Automated Driving Systems (ADSs) have seen rapid progress in recent years. To ensure the
safety and reliability of these systems, extensive testings are being conducted before their …
safety and reliability of these systems, extensive testings are being conducted before their …
A survey on data-driven scenario generation for automated vehicle testing
Automated driving is a promising tool for reducing traffic accidents. While some companies
claim that many cutting-edge automated driving functions have been developed, how to …
claim that many cutting-edge automated driving functions have been developed, how to …
Specification-based autonomous driving system testing
Autonomous vehicle (AV) systems must be comprehensively tested and evaluated before
they can be deployed. High-fidelity simulators such as CARLA or LGSVL allow this to be …
they can be deployed. High-fidelity simulators such as CARLA or LGSVL allow this to be …
Behavexplor: Behavior diversity guided testing for autonomous driving systems
Testing Autonomous Driving Systems (ADSs) is a critical task for ensuring the reliability and
safety of autonomous vehicles. Existing methods mainly focus on searching for safety …
safety of autonomous vehicles. Existing methods mainly focus on searching for safety …
Many-objective reinforcement learning for online testing of dnn-enabled systems
Deep Neural Networks (DNNs) have been widely used to perform real-world tasks in cyber-
physical systems such as Autonomous Driving Systems (ADS). Ensuring the correct …
physical systems such as Autonomous Driving Systems (ADS). Ensuring the correct …
Machine learning-based test selection for simulation-based testing of self-driving cars software
Simulation platforms facilitate the development of emerging Cyber-Physical Systems (CPS)
like self-driving cars (SDC) because they are more efficient and less dangerous than field …
like self-driving cars (SDC) because they are more efficient and less dangerous than field …
Drivefuzz: Discovering autonomous driving bugs through driving quality-guided fuzzing
Autonomous driving has become real; semi-autonomous driving vehicles in an affordable
price range are already on the streets, and major automotive vendors are actively …
price range are already on the streets, and major automotive vendors are actively …