Related papers: Querying Labelled Data with Scenario Programs for …

One of the major impediments in deployment of Autonomous Driving Systems (ADS) is their safety and reliability. The primary reason for the complexity of testing ADS is that it operates in an open world characterized by its…

The safety and reliability of Automated Driving Systems (ADSs) must be validated prior to large-scale deployment. Among existing validation approaches, scenario-based testing has been regarded as a promising method to improve testing…

The concept of scenario and its many qualifications -- specifically logical and abstract scenarios -- have emerged as a foundational element in safeguarding automated driving systems. However, the original linguistic definitions of the…

The development of software components for autonomous driving functions should always include an extensive and rigorous evaluation. Since real-world testing is expensive and safety-critical -- especially when facing dynamic racing scenarios…

Testing and validating Autonomous Vehicle (AV) performance in safety-critical and diverse scenarios is crucial before real-world deployment. However, manually creating such scenarios in simulation remains a significant and time-consuming…

With the increasing safety validation requirements for the release of a self-driving car, alternative approaches, such as simulation-based testing, are emerging in addition to conventional real-world testing. In order to rely on virtual…

In this paper, we present ViSTA, a framework for Virtual Scenario-based Testing of Autonomous Vehicles (AV), developed as part of the 2021 IEEE Autonomous Test Driving AI Test Challenge. Scenario-based virtual testing aims to construct…

Laboratories are prone to severe injuries from minor unsafe actions, yet continuous safety monitoring -- beyond mandatory pre-lab safety training -- is limited by human availability. Vision language models (VLMs) offer promise for…

Existing safety assurance approaches for autonomous vehicles (AVs) perform system-level safety evaluation by placing the AV-under-test in challenging traffic scenarios captured by abstract scenario specifications and investigated in…

When considering the accuracy of sensors in an automated vehicle (AV), it is not sufficient to evaluate the performance of any given sensor in isolation. Rather, the performance of any individual sensor must be considered in the context of…

Safety and mission performance validation of autonomous vehicles (AVs) is a major challenge. In this paper we describe a methodology for constructing and applying assertion checks to validate the behaviour of an AV operating either in…

Many players in the automotive field support scenario-based assessment of automated vehicles (AVs), where individual traffic situations can be tested and, thus, facilitate concluding on the performance of AVs in different situations. Since…

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 autonomous driving systems. However, the term scenario…

The development of Autonomous Vehicles (AVs) has made significant progress in the last years. An important aspect in the development of AVs is the assessment of their safety. New approaches need to be worked out. Among these, real-world…

Before introducing an Automated Driving System (ADS) on the road at scale, the manufacturer must conduct some sort of safety assurance. To structure and harmonize the safety assurance process, the UNECE WP.29 Working Party on…

The selection of relevant test scenarios for the scenario-based testing and safety validation of automated driving systems (ADSs) remains challenging. An important aspect of the relevance of a scenario is the challenge it poses for an ADS.…

Generally capable Spatial AI systems must build persistent scene representations where geometric models are combined with meaningful semantic labels. The many approaches to labelling scenes can be divided into two clear groups: view-based…

In many cyber-physical systems, especially in critical applications such as aeroplanes, data to train anomaly detection and diagnosis algorithms is lacking due to data protection issues and partial observability. To combat this inherent…

The widescale deployment of Autonomous Vehicles (AV) appears to be imminent despite many safety challenges that are yet to be resolved. It is well-known that there are no universally agreed Verification and Validation (VV) methodologies…

Challenges related to automated driving are no longer focused on just the construction of such automated vehicles (AVs), but in assuring the safety of their operation. Recent advances in Level 3 and Level 4 autonomous driving have motivated…