Department of Industrial and Systems Engineering at the University of Wisconsin–Madison
We are delighted to announce that Professor John D Lee has accepted our invitation to be a keynote speaker at the event. Hailing from the esteemed Department of Industrial and Systems Engineering at the University of Wisconsin–Madison, Professor Lee will undoubtedly enrich the conference with his expertise aligned with the event’s theme. Attendees can anticipate gaining valuable insights and perspectives on industrial and systems engineering from Professor Lee, making this a not-to-be-missed opportunity for all participants.
Title: Driver distraction in the age of increasingly automated vehicles
Abstract
Over the last 50 years, driver distraction has remained a persistent practical and conceptual problem. Despite substantial and sustained research, education, and enforcement efforts distraction is a greater driving safety threat than it was 20 years ago. Why is driver distraction so difficult? This talk addresses this question by framing distraction as a joint property of the driver, road situation, and vehicle technology. This framing helps explain the conceptual challenge–distraction is not a cognitive process or internal state of the driver. This framing also highlights additional challenges as vehicle technology changes what it means to drive. To an increasing degree, distraction depends on drivers’ trust in vehicle automation and awareness of its dynamically varying capability. This framing helps explain why distraction is so difficult for drivers, researchers, and designers. It also offers directions for grappling distraction over the next 50 years.
Bio
John D. Lee is the Emerson Electric Professor at the University of Wisconsin-Madison. He investigates technology-mediated attention, which includes driver distraction and human-automation interaction, particularly trust in automation. His work also involves assessing novel interface and interaction methods to enhance trust calibration, as well as novel statistical approaches to assess trust and driver state estimation. He helped to edit the Handbook of Cognitive Engineering, the APA Handbook of Human Systems Integration, and is also a co-author of a popular textbook: Designing for People: An introduction to human factors engineering. This research has been funded by NSF, ONR, NHTSA, NASA, Nissan, Honda, Toyota, and GM.
Human factors and Transport Systems, Institute for Transport Studies, University of Leeds
Professor Merat is an experimental psychologist, leads the Human Factors and Safety Group, @ITS Leeds and is Director of Virtuocity@Leeds. Her main research interests are in understanding the interaction of road users with new technologies, including how driver distraction/inattention and impairment affect performance. She is an expert in understanding the human factors implications of highly automated vehicles (HAVs), and has conducted research on both drivers’ and pedestrians’ interactions with HAVs. She has been PI to key projects in this area, including AdaptIVe , CityMobil2, InterACT, HumanDrive, L3PILOT and currently leads the User sub-project of the €60M HiDrive project. Professor Merat is Chair of the Transportation Research Board sub-committee on Human Factors in Road Vehicle Automation; and European Chair of the trilateral (EU-US-Japan) Working Group on Human Factors of Automated Vehicles. She has been an advisor to over 15 governmental and industry organisations and has published over 250 peer reviewed articles, collaborating with over 100 industrial and research partners. She is currently leading an ISO Task Force on design guidelines for future Driver Monitoring Systems, and was recently awarded an International Excellence Fellowship by KIT, Germany.
Title: Cognitive load during driving: how do we measure it, and is it protective or disruptive?
Abstract
Driver distraction is caused by any task that takes drivers’ attention away from driving-related activities (Regan et al., 2008; NHTSA, 2023). This distraction may be imposed by tasks that place demand on our auditory, visual, manual, or cognitive resources (or indeed a combination of these). Currently, there is good agreement amongst policy makers and researchers about the dangers associated with tasks that take our eyes and hands away from driving. This visual/manual distraction is also typically identified and mitigated by a range of in-vehicle sensors and driver monitoring technologies. The term “cognitive distraction”, however, is not as well defined, nor as easily or reliably detected by in-vehicle technologies. There is also a longstanding debate amongst researchers about the effects of this type of distraction on driving performance and road safety. This topic has gained recent interest in the UK, in a bid to reduce crashes associated with handsfree mobile phone conversations, which I consider to be one form of cognitive distraction. To mitigate this type of distraction, Euro NCAP recently has included assessment of technologies that monitor drivers’ cognitive distraction in its Vision 2030 roadmap. While I will not pretend there’s an easy and clear path for identifying this driver state, during this talk, I will provide an overview of the methods used to impose cognitive distraction in the lab, also considering why this state is not as easy to identify in the wild. I will highlight how cognitive distraction affects drivers’ response during manual and automated driving, with an aim to providing some food for thought regarding future research in this area.
You can read more about Prof Merat and her research here.
The University of Michigan Transportation Research Institute will be handling secretariat duties for the DDI2024 Conference.
General inquiries E-mail: ddi2024us@umich.edu
Phone: +1 734-936-2070
Abstract submission E-mail: ddiabstracts@meetx.se.
