The core value of simulation-based autonomy tests is to create densely extreme traffic
scenarios to test the performance and robustness of the algorithms and systems. Test …

Sampling, generation, and evaluation of scenarios are essential steps for intelligent testing
of autonomous vehicles. Since uncertainty in driving behavior always leads to different …

Recent accidents involving self-driving cars call for extensive testing efforts to improve the
safety and robustness of autonomous driving. However, constructing test scenarios for …

Scenario generation is one of the essential steps in scenario-based testing and, therefore, a
significant part of the verification and validation of driver assistance functions and …

The enormous efforts spent on collecting naturalistic driving data in the recent years has
resulted in an expansion of publicly available traffic datasets, which has the potential to …

Scenario-based testing is already a well-known test approach to the automotive industry for
the Validation, Verification and Testing of Connected and Automated Vehicles. How to …

Behavior prediction remains one of the most challenging tasks in the autonomous vehicle
(AV) software stack. Forecasting the future trajectories of nearby agents plays a critical role …

Automated Driving Systems (ADS) require extensive evaluation to assure acceptable levels
of safety before they can operate in real-world traffic. Although many tools are available to …

Assuring the safety of automated and autonomous driving functions is crucial for a safe
deployment of self-driving vehicles on public roads. This includes the need for automated …

Autonomous Driving Systems (ADSs), which replace humans to drive vehicles, are complex
software systems deployed in autonomous vehicles (AVs). Since the execution of ADSs …