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Improving Emergency Response Wayfinding

May 15, 2018

CEE Assistant Professor Qi "Ryan" Wang (PI) and MIE Associate Professor Yingzi Lin (co-PI) were awarded a $200K NSF grant for "Personalized Systems for Wayfinding for First Responders". The grant will be in collaboration with Jing "Eric" Du from Texas A&M.

Abstract Source: NSF

First responders face serious risks when responding to emergencies, and disorientation induced by complex building features is a major cause of injuries. In order to successfully navigate complex, dangerous buildings during a crisis, first responders need to build accurate spatial memories of unfamiliar spaces in a timely manner. This requires retention and processing of a large amount of information such as maps and verbal instructions. An apparent gap between the enormous information processing needs during a mission and the limited processing capacity of people creates a potentially fatal situation in emergency wayfinding. This project will contribute to the NSF's Big Idea "Harnessing Data for 21st Century Science and Engineering" by conducting fundamental research in information processing and engineering in the field of disaster management. This project will test the theoretical foundation of personalized wayfinding information systems that can effectively minimize the cognitive load of first responders on the individual level. This scientific research contribution thus supports NSF's mission to promote the progress of science and to advance our national welfare. In this case, the benefits will be insights to improve emergency response wayfinding, which will save lives and potentially reduce economic losses during disasters.

This project has three interdependent scientific objectives. First, the research quantifies the structured relationship between spatial information and different forms of cognitive load in wayfinding tasks. Spatial information for wayfinding will be categorized and measured using semantic metrics; then a quantitative model of the relationship between spatial information and cognitive load will be examined. Second, the research explores cognitive resilience that helps identify and prevent an abrupt drop in wayfinding performance. Virtual Reality (VR) based multi-mission experiments are performed to examine the hypothetical nonlinearity of the relationship between cognitive load and wayfinding performance. Third, the research evaluates the effectiveness of personalized wayfinding information system in simulated mission tasks. A holistic VR experiment is performed to compare the new personalized system against the current universal spatial information systems. The outcome of the scientific investigation includes an adaptive wayfinding information system that dynamically tailors the way spatial information is presented based on the real-time cognitive load of individual first responders, measured by a set of neurobiological and physiological metrics. The project will immediately impact first responders primarily firefighters for their missions. A number of collaborative outreach activities are planned between two project sites: Texas A&M University and Northeastern University. These include advancing VR technologies for STEM education, integrating the research outcomes to curriculum development at both institutions, and developing a free online course and open-source project for general public access.