相关论文: Moral Testing of Autonomous Driving Systems

Autonomous driving systems (ADS) have been an active area of research, with the potential to deliver significant benefits to society. However, before large-scale deployment on public roads, extensive testing is necessary to validate their…

Autonomous driving systems (ADS) are increasingly deployed in real traffic, yet testing remains fundamentally challenging due to open environments, complex scenarios, and the lack of established processes and metrics. Despite extensive…

Ethical dilemmas are a common challenge in everyday driving, requiring human drivers to balance competing priorities such as safety, efficiency, and rule compliance. However, much of the existing research in automated vehicles (AVs) has…

Simulation is essential to validate autonomous driving systems. However, a simple simulation, even for an extremely high number of simulated miles or hours, is not sufficient. We need well-founded criteria showing that simulation does…

Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of…

Autonomous Vehicles (AVs) raise important social and ethical concerns, especially about accountability, dignity, and justice. We focus on the specific concerns arising from how AV technology will affect the lives and livelihoods of…

Autonomous systems are becoming increasingly prevalent in new vehicles. Due to their environmental friendliness and their remarkable capability to significantly enhance road safety, these vehicles have gained widespread recognition and…

Background/Context. The use of automated driving systems (ADSs) in the real world requires rigorous testing to ensure safety. To increase trust, ADSs should be tested on a large set of diverse road scenarios. Literature suggests that if a…

As vehicles transition toward higher levels of automation, Driver Monitoring Systems (DMS) have become essential for ensuring human oversight, safety, and regulatory compliance in a vehicle. These systems rely on multimodal sensing and…

Autonomous Driving Systems (ADS) are safety-critical, where failures can be severe. While Metamorphic Testing (MT) is effective for fault detection in ADS, existing methods rely heavily on manual effort and lack automation. We present…

Automated Decision-Making Systems (ADS) have become pervasive across various fields, activities, and occupations, to enhance performance. However, this widespread adoption introduces potential risks, including the misuse of ADS. Such misuse…

Evaluating and ensuring the adversarial robustness of autonomous driving (AD) systems is a critical and unresolved challenge. This paper introduces MetAdv, a novel adversarial testing platform that enables realistic, dynamic, and…

With the growing technological advances in autonomous driving, the transport industry and research community seek to determine the impact that autonomous vehicles (AV) will have on consumers, as well as identify the different factors that…

Autonomous Driving Systems (ADS) are critical dynamic reconfigurable agent systems whose specification and validation raises extremely challenging problems. The paper presents a multilevel semantic framework for the specification of ADS and…

Simulation-based testing is a cornerstone of Autonomous Driving System (ADS) development, offering safe and scalable evaluation across diverse driving scenarios. However, discrepancies between simulated and real-world behavior, known as the…

Autonomous Driving Systems (ADSs) are complex Cyber-Physical Systems (CPSs) that must ensure safety even in uncertain conditions. Modern ADSs often employ Deep Neural Networks (DNNs), which may not produce correct results in every possible…

Ensuring the safety and reliability of Automated Driving Systems (ADS) remains a critical challenge, as traditional verification methods such as large-scale on-road testing are prohibitively costly and time-consuming.To address…

Modern AI and robotic systems are characterized by a high and ever-increasing level of autonomy. At the same time, their applications in fields such as autonomous driving, service robotics and digital personal assistants move closer to…

As a part of the digital transformation, we interact with more and more intelligent gadgets. Today, these gadgets are often mobile devices, but in the advent of smart cities, more and more infrastructure---such as traffic and buildings---in…

Automated Driving Systems (ADSs) are being manufactured at an accelerated rate, leading to improvements in traffic safety, reduced energy consumption, pollution, and congestion. ADS relies on various data streams from onboard sensors,…