Given that sensor-based perception systems are utilized in autonomous vehicle applications, it is essential to validate such systems to ensure their robustness before they are deployed. In this study, we propose a comprehensive simulation-based proce...
With the advancement of autonomous driving technology, scenario-based testing has become the mainstream testing method for intelligent vehicles. However, traditional risk indicators often fail in roundabout scenarios and cannot accurately define dang...
Testing and validation of the functionalities and safety of automated vehicles shifted from a distance-based to a scenario-based method in the past decade. A number of domain-specific languages and systems were developed to support scenario-based tes...
Assuring the safety of automated vehicles is essential for their timely introduction and acceptance by policymakers and the public. To assess their safe design and robust decision making in response to all possible scenarios, new methods that use a s...
Highly automated vehicles are increasingly gaining the public’s attention. To achieve broad acceptance for the deployment of such vehicles, it is necessary to ensure their functionality and safety. One approach that has become popular in research is...
In the past decade, automotive companies have invested significantly in autonomous vehicles (AV), but achieving widespread deployment remains a challenge in part due to the complexities of safety evaluation. Traditional distance-based testing has bee...
High-level Automated Vehicles (HAVs) are expected to improve traffic safety significantly. However, verifying and evaluating HAVs remains an open problem. Scenario-based testing is a promising method for HAV testing. Boundary scenarios exist around t...
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 evaluate the safety of automated vehicles remains an open question, which...
V2X communication plays an important role in the transition towards connected, cooperative, automated driving. Wireless communication enables instant information exchange between vehicles (V2V) to support, e.g., platooning, and between the infrastruc...
Modern Artificial Intelligence (AI) methods can produce a large quantity of accurate and richly described data, in domains such as surveillance or automation. As a result, the need to organize data at a large scale in a semantic structure has arisen...
The validation of autonomous vehicles remains a vexing challenge for the automotive industry’s goal of fully autonomous driving. The systematic hierarchization of the test scenarios would provide valuable insights for the development, testing,...
To address the structural differences between closed-track and open-road testing in terms of scenario coverage, risk controllability, and validation consistency, this study proposes a scenario-driven combined testing method for automated driving syst...
Ensuring the safety of autonomous driving systems (ADS) requires scenario-based testing that reflects the complexity and variability of real-world driving conditions. However, the nondeterministic nature of actual traffic environments makes physical...
New technology always needs validation in terms of stakeholder acceptance and usability. This challenge also applies in the case of technology for reminiscence therapy for people with dementia. We are looking at how to overcome this situation and ide...
As the complexity of automated driving systemss (ADSs) with automation levels above level 3 is rising, virtual testing for such systems is inevitable and necessary. The complexity of testing these levels lies in the modeling and calculation demands f...
This paper proposes a decision-making algorithm based on deep reinforcement learning to support fallback techniques in autonomous vehicles. The fallback technique attempts to mitigate or escape risky driving conditions by responding to appropriate av...
With more goods to be transported oversea, traffic and vessels’ dimensions increase while berthing areas merely remain constant and thus challenge ship masters and pilots to maneuver in small basins with dense traffic even in bad weather situat...
This paper evaluates Advanced Driver Assistance Systems (ADASs) in test scenarios derived from naturalistic driving and crash data, mapped to ISO 26262, ISO/PAS 21448 (SOTIF), and ISO 34502. From eight high-risk scenarios, it is validated for left tu...
The safe and reliable operation of autonomous vehicles is contingent on comprehensive testing. However, the operational scenarios are inexhaustible. Corner cases, which critically influence autonomous vehicle safety, occur at an extremely low probabi...
There is increasing interest in automating train operations of mainline services, e.g., to increase network capacity. Automatic train operation (ATO) is already achieved by several pilot projects, but is still not implemented on a large scale. Functi...
Current testing methods for autonomous driving systems primarily focus on simple traffic scenarios, generating test cases based on traffic accidents, while research on generating edge test cases for complex driving environments by traffic regulations...
Collision avoidance algorithms play a crucial role in ensuring the safety and effectiveness of autonomous ships, which require comprehensive testing in realistic multi-ship encounter scenarios. However, existing scenario generation methods often inad...
In response to the problems of rough modeling and insufficient coverage of edge interaction scenarios in autonomous driving tests, this paper proposes a scene generation method based on interaction coding. The method constructs a hierarchical paramet...
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 selecti...
Polymer-based items may release Volatile Organic Compounds (VOCs) and odors indoors, contributing to the overall VOC inhalation exposure for end users and building occupants. The main objective of the present study is the evaluation of short-term inh...
Naturalistic driving data (NDD) are valuable for testing autonomous driving systems under various driving conditions. Automatically identifying scenes from high-dimensional and unlabeled NDD remains a challenging task. This paper presents a novel app...
The targeted shortening of sensor development requires short and convincing verification tests. The goal of the development of novel verification methods is to avoid or reduce an excessive amount of testing and identify tests that guarantee that the...
Understanding the growth dynamics and ecological constraints of Porphyra spp. is essential for optimizing sustainable seaweed aquaculture. However, most existing models lack physiological detail and exhibit limited performance under variable environm...
Integrated urban water management calls for tools that can analyze and simulate the complete cycle including the physical, technical, and social dimensions. Scientific advances created simulation tools able to simulate the urban water cycle as realis...
Background and Objectives: Clinical ethical judgments are often elicited through scenario-based (vignette-based) dilemmas that guide interpretation, reasoning, and moral judgment. Despite its importance, little is known about how healthcare professio...
Ensuring the safety of Automated Driving Systems (ADSs) requires structured and transparent validation processes. Scenario-based testing has emerged as a widely adopted approach, enabling the targeted assessment of system behavior under diverse and c...
With the rapid development of automated wheeled vehicle technology, complex vehicle functions require extensive safety testing for verification. Compared with real-vehicle testing, scenario-based virtual testing, which constructs virtual environments...
With over 1.6 million traffic deaths in 2016, automated vehicles equipped with automated driving systems (ADSs) have the potential to increase traffic safety by assuming human driving tasks within the operational design domain (ODD). However, safety...
The nominal group technique (NGT) was developed in the 1970s as a structured brainstorming and multi-stage consensus-building process to solicit feedback from a group of stakeholders on a given topic. The approach was intended as an evaluation method...
Smart energy products and services (SEPS) have a key role in the development of smart grids, and testing methods such as co-simulation and scenario-based simulations can be useful tools for evaluating the potential of new SEPS concepts during their e...
For consumers to have confidence in the safety of automated vehicles (AVs), AVs must be assessed using systematically developed scenarios to verify driving safety and reliability. In particular, verification using scenarios has been widely performed...
System perception of the environment becomes more important as the level of automation increases, especially at the higher levels of automation (L3+) of Automated Driving Systems. As a consequence, scenario-based validation becomes more important in...
With continuous advancements in autonomous driving technology, systematic and reliable safety verification is becoming increasingly important. However, despite the active development of various X-in-the-loop simulation (XILS) platforms to validate au...
Across their lifespans, and in many clinical settings, patients have spiritual care needs. Many nurses lack competence related to providing spiritual care. Popular educational strategies, such as simulated educational programs and objective structure...
The on-board sensors of connected autonomous vehicles (CAVs) are limited by their range and inability to see around corners or blind spots, otherwise known as non-line of sight scenarios (NLOS). These scenarios have the potential to be fatal (critica...
Comprehensive safety evaluation methodologies for automated driving systems that account for the large complexity real traffic are currently being developed. This work adopts a scenario-based safety evaluation approach and aims at investigating an ad...
Maritime Autonomous Surface Ship (MASS) is promoted as the future of intelligent shipping. While autonomy technologies offer a solution for MASS, they have also resulted in new challenges for performance validation. To address this, a scenario-based...
Around the world, human populations and their supporting infrastructures are concentrated in coastal areas. With rising sea levels, these settlements and urban infrastructures are at risk of service interruptions, lasting damage and frequent climate-...
The collision avoidance system is one of the core systems of MASS (Maritime Autonomous Surface Ships). The collision avoidance system was validated using scenario-based experiments. However, the scenarios for the validation were designed based on COL...
Scenario-based testing is a mainstream approach for evaluating the safety of automated driving systems (ADS). However, logical scenarios are defined through parameter spaces, and performance differences among systems under test make it difficult to e...
While autonomous vehicles have the potential to mitigate risks associated with dangerous driving behaviors, the safety and stability of autonomous driving technology in real-world applications still require comprehensive tests. Scenario-based virtual...
Accurate short- and medium-term forecasting of photovoltaic (PV) power generation is vital for grid stability and renewable energy integration. This study presents a comparative scenario-based approach using Long Short-Term Memory (LSTM), Convolution...
Non-destructive concrete strength prediction faces limitations in validation scope, methodological comparison, and interpretability that constrain deployment in safety-critical construction applications. This study presents a machine learning framewo...
Complexity is a key measure of driving scenario significance for scenario-based autonomous driving tests. However, current methods for quantifying scenario complexity primarily focus on static scenes rather than dynamic scenarios and fail to represen...
Validating the safety and reliability of automated driving systems is a critical challenge in the development of autonomous driving technology. Such systems must reliably replicate human driving behavior across scenarios of varying complexity and cri...
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