Related papers: Automating eHMI Action Design with LLMs for Automa…
Automated vehicles lack natural communication channels with other road users, making external Human-Machine Interfaces (eHMIs) essential for conveying intent and maintaining trust in shared environments. However, most eHMI studies rely on…
Automated vehicles (AVs) must communicate their yielding intentions to pedestrians at crossings. External Human-Machine Interfaces (eHMIs, on-vehicle displays) are promising solutions, but were primarily tested with walking pedestrians.…
As the number of fatalities involving Autonomous Vehicles increase, the need for a universal method of communicating between vehicles and other agents on the road has also increased. Over the past decade, numerous proposals of external…
The absence of a human operator in automated vehicles (AVs) may require external Human-Machine Interfaces (eHMIs) to facilitate communication with other road users in uncertain scenarios, for example, regarding the right of way. Given the…
We claim that LLMs can be paired with formal analysis methods to provide accessible, relevant feedback for HRI tasks. While logic specifications are useful for defining and assessing a task, these representations are not easily interpreted…
The pursuit of human-level artificial intelligence (AI) has significantly advanced the development of autonomous agents and Large Language Models (LLMs). LLMs are now widely utilized as decision-making agents for their ability to interpret…
External Human-Machine Interfaces (eHMIs) are key to facilitating interaction between autonomous vehicles and external road actors, yet most remain reactive and do not account for scalability and inclusivity. This paper introduces a…
Recent advancements in Large Language Models (LLMs) offer new opportunities to create natural language interfaces for Autonomous Driving Systems (ADSs), moving beyond rigid inputs. This paper addresses the challenge of mapping the…
Each year, over half of global traffic fatalities involve vulnerable road users (e.g. pedestrians), often due to human error. Level-5 automated driving systems (ADSs) could reduce driver errors contributing to pedestrian accidents, though…
The fusion of human-centric design and artificial intelligence (AI) capabilities has opened up new possibilities for next-generation autonomous vehicles that go beyond transportation. These vehicles can dynamically interact with passengers…
Human behavior models are essential as behavior references and for simulating human agents in virtual safety assessment of automated vehicles (AVs), yet current models face a trade-off between interpretability and flexibility.…
We aim to evaluate Large Language Models (LLMs) for embodied decision making. While a significant body of work has been leveraging LLMs for decision making in embodied environments, we still lack a systematic understanding of their…
Large-language models (LLMs) hold significant promise in improving human-robot interaction, offering advanced conversational skills and versatility in managing diverse, open-ended user requests in various tasks and domains. Despite the…
Recent large language models (LLMs) are capable of planning robot actions. In this paper, we explore how LLMs can be used for planning actions with tasks involving situational human-robot interaction (HRI). A key problem of applying LLMs in…
Large language models (LLMs) have demonstrated remarkable capabilities across a range of text-generation tasks. However, LLMs still struggle with problems requiring multi-step decision-making and environmental feedback, such as online…
With automated vehicles (AVs), the absence of a human operator could necessitate external Human-Machine Interfaces (eHMIs) to communicate with other road users. Existing research primarily focuses on pedestrian-AV interactions, with limited…
Autonomous Vehicles (AVs) have entered the commercialization stage, but their limited ability to interact and express intentions still poses challenges in interactions with Human-driven Vehicles (HVs). Recent advances in large language…
As autonomous vehicles become more integrated into shared human environments, effective communication with road users is essential for ensuring safety. While previous research has focused on developing external Human-Machine Interfaces…
Vehicle API testing verifies whether the interactions between a vehicle's internal systems and external applications meet expectations, ensuring that users can access and control various vehicle functions and data. However, this task is…
Foundation models, including large language models (LLMs) and vision-language models (VLMs), have recently enabled novel approaches to robot autonomy and human-robot interfaces. In parallel, vision-language-action models (VLAs) or large…