DMSOMS

Advancements in Occupant and Driver Monitoring: Leveraging AI/ML in Automotive Safety

Overview

International Workshop & Panel on Driver Monitoring Systems Using Machine Learning

In an era marked by rapid advancements in machine learning, sensor technology, information processing, and control systems, the domain of Intelligent Transport Systems (ITS) has witnessed significant progress. The nascent field of Automated Vehicle Safety(AVS) stands at the brink of deployment, offering a glimpse into the future of automated driving. As we edge closer to realizing high levels of automation in driving, particularly in the intricate web of urban environments, the need for innovative solutions to ensure safety, comfort, and efficiency becomes paramount. Recognizing the symbiotic relationship in automated transport, and the myriad challenges that lie ahead, we are excited to announce the call for papers for the International Workshop on Driver Monitoring Systems Using Machine Learning.

This panel aims to bridge the gap between the potential of machine learning technologies and their application in driver monitoring systems to enhance the safety and efficiency of automated and semi-automated vehicles. As driver monitoring systems become increasingly crucial in the transition towards fully automated driving, this workshop provides a platform for researchers, industry professionals, and stakeholders to converge, share insights, and explore the latest developments in machine learning applications for driver monitoring.

Topics of Interest

We will discuss and invite submissions of original research papers, case studies, and review articles that address, but are not limited to, the following topics:

• Machine learning algorithms for driver behavior analysis and prediction
• Sensor technologies and data fusion for in-vehicle monitoring systems
• Real-time detection of driver distraction and fatigue
• Integration of driver monitoring systems with automated driving technologies
• Impact of driver monitoring on vehicle safety and traffic efficiency
• Ethical considerations and privacy concerns in driver monitoring
• Deployment challenges and solutions for driver monitoring systems
• Case studies on the implementation and effectiveness of driver monitoring systems

Industry discussion

The workshop will also feature an Industry panel talk, bringing together experts from safety, govenmental mandates, AWS and Intel. This panel will facilitate a valuable exchange highlighting practical challenges and opportunities in the deployment of driver monitoring systems.

Submission Guidelines

Prospective authors are invited to submit full papers according to the guidelines provided on our website. Submissions should be original and not previously published or under consideration for publication elsewhere. Papers will be reviewed by a panel of experts in the field based on originality, technical and/or research content, relevance, and clarity.

Join us in advancing the field of driver monitoring systems through the innovative application of machine learning technologies. Together, we can pave the way for safer, more efficient, and intelligent transportation systems. We look forward to your contributions and participation in what promises to be a groundbreaking workshop.

Featured Speakers

Dr. Ignacio Alvarez

• Position: Principal engineer in automated driving at Intel Labs.
• Affiliation: Intel Labs.
• Bio: Dr. Ignacio Alvarez is a Principal engineer atIntel Labs, the research arm of Intel Corporation. He has lead R&D and product development in Europe, Asia and America. A recognized IEEE Senior Member, contributed to standards in the fields of autonomous vehicle safety and connected vehicles. He is an avid inventor with 80+ issued patents and over 130 patents pending. Dr. Alvarez has published over 50 peer-reviewed papers, edited 3 books in Automotive Engineering.

Mr. Andy Shahbazian

• Position: Senior Solution Architect, Autonomous Vehicles.
• Affiliation: Amazon Web Services (AWS), California State Univesity.
• Bio: Andy boasts more than two decades of experience in Information Systems and autonomous technologies, with a specialized focus on leveraging AI and machine learning technologies to improve autonomous vehicle systems. He has authored numerous papers on Big Data and IoT orchestration, featured in leading scientific journals. Furthermore, Andy is a recognized figure on the international conference circuit, where he has frequently delivered keynote speeches on automotive and AI technologies.

Workshop

Introduction to OMS and DMS

• Overview of Occupant and Driver Monitoring in the Automotive Industry.
• The role of AI/ML in enhancing OMS and DMS.