Related papers: Defining an Evaluation Method for External Human-M…
The application of external human-machine interface (EHMI) on autonomous vehicles (AVs) facilitates information exchange. Existing research fails to consider the impact of the sequence of actions, as well as the effects of EHMI applications…
As emotion plays a growing role in robotic research it is crucial to develop methods to analyze and compare among the wide range of approaches. To this end we present a survey of 1427 IEEE and ACM publications that include robotics and…
The authors present a cyber-physical systems study on the estimation of driver behavior in autonomous vehicles and vehicle safety systems. Extending upon previous work, the approach described is suitable for the long term estimation and…
Empathetic Conversational Systems (ECS) are built to respond empathetically to the user's emotions and sentiments, regardless of the application domain. Current ECS studies evaluation approaches are restricted to offline evaluation…
In this study, we investigated the effectiveness and user acceptance of three external interaction modalities (i.e., visual, auditory, and visual+auditory) in promoting communications between automated vehicle systems (AVS) and pedestrians…
Ambiguity and noise in natural language instructions create a significant barrier towards adopting autonomous systems into safety critical workflows involving humans and machines. In this paper, we propose to build on recent advances in…
Human computer interaction is shifting from screen-based systems to multimodal interfaces where artificial intelligence powered systems increasingly interpret user intent through speech, gesture, and gaze. Yet users rarely understand how…
Automated UI evaluation can be beneficial for the design process; for example, to compare different UI designs, or conduct automated heuristic evaluation. LLM-based UI evaluation, in particular, holds the promise of generalizability to a…
The capability of Unified Multimodal Models (UMMs) to apply world knowledge across diverse tasks remains a critical, unresolved challenge. Existing benchmarks fall short, offering only siloed, single-task evaluations with limited diagnostic…
In comparison to conventional traffic designs, shared spaces promote a more pleasant urban environment with slower motorized movement, smoother traffic, and less congestion. In the foreseeable future, shared spaces will be populated with a…
Purpose: Human-machine collaboration is a promising strategy to improve hazard inspection. However, research on the effective integration of opinions from humans with machines for optimal group decision making is lacking. Hence, considering…
Ultrasound (US) has emerged as a promising modality for Human-Machine Interfaces (HMIs), with recent research efforts exploring its potential for Hand Pose Estimation (HPE). A reliable solution to this problem could introduce interfaces…
EXplainable Artificial Intelligence (XAI) aims to help users to grasp the reasoning behind the predictions of an Artificial Intelligence (AI) system. Many XAI approaches have emerged in recent years. Consequently, a subfield related to the…
Recent engineering developments in specialised computational hardware, data-acquisition and storage technology have seen the emergence of Machine Learning (ML) as a powerful form of data analysis with widespread applicability beyond its…
Human motion prediction is non-trivial in modern industrial settings. Accurate prediction of human motion can not only improve efficiency in human robot collaboration, but also enhance human safety in close proximity to robots. Among…
Human-Machine Interaction (HMI) systems have gained huge interest in recent years, with reference expression comprehension being one of the main challenges. Traditionally human-machine interaction has been mostly limited to speech and…
At the heart of improving conversational AI is the open problem of how to evaluate conversations. Issues with automatic metrics are well known (Liu et al., 2016, arXiv:1603.08023), with human evaluations still considered the gold standard.…
We introduce EMMA, an End-to-end Multimodal Model for Autonomous driving. Built upon a multi-modal large language model foundation like Gemini, EMMA directly maps raw camera sensor data into various driving-specific outputs, including…
Understanding user interface (UI) functionality is a useful yet challenging task for both machines and people. In this paper, we investigate a machine learning approach for screen correspondence, which allows reasoning about UIs by mapping…
Vehicle performance metrics analyze data sets consisting of subject vehicle's interactions with other road users in a nominal driving environment and provide certain performance measures as outputs. To the best of the authors' knowledge,…