Ignacio Alvarez

Ignacio Alvarez

Professor and Principal Engineer in Intelligent Systems

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

patents

Driver monitoring system (dms) data management

Published:

Driver monitoring system (dms) data management

Recommended citation: Ignacio J Alvarez et al.. (2021). Driver monitoring system (dms) data management. Patent Office. #

Rogue vehicle detection and avoidance

Published:

Rogue vehicle detection and avoidance

Recommended citation: Ignacio Alvarez et al.. (2021). Rogue vehicle detection and avoidance. Patent Office. #

portfolio

publications

Designing driver-centric natural voice user interfaces

Published in Adjunct Proceedings of the 3rd International Conference on Automotive User Interfaces and Interactive Vehicular Applications. online, 2011

Designing driver-centric natural voice user interfaces

Recommended citation: Ignacio Alvarez et al.. (2011). Designing driver-centric natural voice user interfaces. Adjunct Proceedings of the 3rd International Conference on Automotive User Interfaces and Interactive Vehicular Applications. online. https://www.researchgate.net/profile/Ignacio-Alvarez-22/publication/266589727_Designing_Driver-centric_Natural_Voice_User_Interfaces/links/56018ccb08aeb30ba735028f/Designing-Driver-centric-Natural-Voice-User-Interfaces.pdf

Driver in the loop: Best practices in automotive sensing and feedback mechanisms

Published in Automotive user interfaces: creating interactive experiences in the car, 2017

Driver in the loop: Best practices in automotive sensing and feedback mechanisms

Recommended citation: Andreas Riener et al.. (2017). Driver in the loop: Best practices in automotive sensing and feedback mechanisms. Automotive user interfaces: creating interactive experiences in the car. https://link.springer.com/chapter/10.1007/978-3-319-49448-7_11

Towards Adaptive Ambient In-Vehicle Displays and Interactions: Insights and Design Guidelines from the 2015 AutomotiveUI Dedicated Workshop

Published in Automotive User Interfaces: Creating Interactive Experiences in the Car, 2017

Towards Adaptive Ambient In-Vehicle Displays and Interactions: Insights and Design Guidelines from the 2015 AutomotiveUI Dedicated Workshop

Recommended citation: Andreas Löcken et al.. (2017). Towards Adaptive Ambient In-Vehicle Displays and Interactions: Insights and Design Guidelines from the 2015 AutomotiveUI Dedicated Workshop. Automotive User Interfaces: Creating Interactive Experiences in the Car. https://link.springer.com/chapter/10.1007/978-3-319-49448-7_12

Agents, environments, scenarios: A framework for examining models and simulations of human-vehicle interaction

Published in Transportation research interdisciplinary perspectives, 2020

Agents, environments, scenarios: A framework for examining models and simulations of human-vehicle interaction

Recommended citation: Christian P Janssen et al.. (2020). Agents, environments, scenarios: A framework for examining models and simulations of human-vehicle interaction. Transportation research interdisciplinary perspectives. #

User experience design in the era of automated driving

Published in No venue listed, 2022

User experience design in the era of automated driving

Recommended citation: Andreas Riener, Myounghoon Jeon, Ignacio Alvarez. (2022). User experience design in the era of automated driving. No venue listed. #

talks

teaching

Project Natural User Interfaces: Enhancing Autonomous Vehicle Safety Awareness through Gamification

User Experience Design Master of Science, Technische Hochschule Ingolstadt, Computer Science, 2025

Description

Educating vehicle passengers and drivers about safety in autonomous vehicles (AVs) can be a challenge, especially when technical concepts like the Responsibility Sensitive Safety (RSS) model are involved. Gamification offers an innovative way to enhance user engagement and increase awareness of AV safety principles through the more natural interfaces of games by transforming complex concepts into interactive and enjoyable experiences. Integrating a safety model like RSS into a game can provide users with real-time feedback on safe driving practices and decision-making in various scenarios, as well as improve overall situational awareness during non-driving tasks.

Project Artificial Intelligence: LLM-based Agent for Driver Sleepiness Detection and Mitigation in Automotive Systems

AI Engineering of Autonomous Systems Master of Science, Technische Hochschule Ingolstadt, Computer Engineering, 2025

Description

Ensuring driver alertness is a cornerstone of automotive safety, and Large Language Models (LLMs) offer a unique opportunity to create intelligent systems capable of detecting and mitigating sleepiness. By integrating multimodal inputs such as audio cues, video streams, and driving context signals, LLMs can process complex, real-time data to assess driver state and trigger appropriate actions to maintain alertness. In this project, students will design and prototype an automotive agent powered by LLMs to detect and respond to driver sleepiness. The system will utilize multimodal inputs, such as facial expressions, voice tone, and driving behavior, to compute a sleepiness likelihood metric. Based on the metric and additional contextual awareness signals (e.g., time of day, driving duration), the agent will propose tailored interventions, such as adjusting cabin temperature, suggesting a rest stop, or initiating engaging conversations. Students will evaluate the system’s usability, effectiveness, and user satisfaction, exploring the interplay between AI decision-making and driver interaction.

Study design and implementation of UX tests: AV harrassment

User Experience Design Bachelor of Science, Technische Hochschule Ingolstadt, Computer Science, 2025

Description

This course is designed to prepare students for their final thesis. It provides fundamental knowledge to develop a study design based on a problem definition, conduct the study, evaluate it, and interpret the results. Thematic clusters in the area of ​​human-computer interaction (e.g., productivity, automated driving, sports, and digitalization) are offered, from which student groups can choose and propose a specific topic. This topic will be developed iteratively in close professional coordination with the respective supervising lecturers. • Basics of user studies (possible applications, definition of research hypothesis) • Study design (dependent/independent variables, laboratory vs. field studies, within-groups/between-groups design) • Planning of experiments (different methods, “fidelity” of an experiment, software/hardware prototypes, Wizard of Oz studies, qualitative surveys/quantitative measurements, ethical aspects, role of an institutional review board (IRB)) • Study implementation (preparation, briefing/debriefing, finding and inviting test subjects, determining group size, learning effects, measuring variables/data collection) • Qualitative data analysis (content analysis, evaluation with MAXQDA/NVIVO, preparation and presentation of results, revision/fine-tuning in Illustrator) • Quantitative data analysis (reflection on the research hypothesis, use of SPSS for statistical evaluations, parametric/nonparametric statistics, correct choice of method, presentation and interpretation of results) • Written/oral presentation of the results (preparation of results, peer review process, final conference-style presentation)

Study design and implementation of UX tests: Emphatic Car

User Experience Design Bachelor of Science, Technische Hochschule Ingolstadt, Computer Science, 2025

Description

This course is designed to prepare students for their final thesis. It provides fundamental knowledge to develop a study design based on a problem definition, conduct the study, evaluate it, and interpret the results. Thematic clusters in the area of ​​human-computer interaction (e.g., productivity, automated driving, sports, and digitalization) are offered, from which student groups can choose and propose a specific topic. This topic will be developed iteratively in close professional coordination with the respective supervising lecturers. • Basics of user studies (possible applications, definition of research hypothesis) • Study design (dependent/independent variables, laboratory vs. field studies, within-groups/between-groups design) • Planning of experiments (different methods, “fidelity” of an experiment, software/hardware prototypes, Wizard of Oz studies, qualitative surveys/quantitative measurements, ethical aspects, role of an institutional review board (IRB)) • Study implementation (preparation, briefing/debriefing, finding and inviting test subjects, determining group size, learning effects, measuring variables/data collection) • Qualitative data analysis (content analysis, evaluation with MAXQDA/NVIVO, preparation and presentation of results, revision/fine-tuning in Illustrator) • Quantitative data analysis (reflection on the research hypothesis, use of SPSS for statistical evaluations, parametric/nonparametric statistics, correct choice of method, presentation and interpretation of results) • Written/oral presentation of the results (preparation of results, peer review process, final conference-style presentation)