Leveraging Ubiquitous Computing for Empathetic Routing: A Naturalistic Data-driven Approach

Although we extensively use routing services in our daily commutes, such systems are yet to be personalized around the user. It often happens that different routes are close in their estimated time of arrival (ETA) while being very different in how they affect the driver’s states. Using traces of a user’s physiological measures, different candidate routes can be ranked based on how they affect users’ well-being. In this research, we introduce the “empathetic routing” framework for providing human-centered routing based on historical biomarkers of the drivers collected through naturalistic settings and by using smart wearable devices. Through this framework, we rank three specific routes between two points in the city of Charlottesville, based on historical driver heart rate data collected through a three-month naturalistic driving study. Additionally, we demonstrate that the proposed framework is capable of finding infrastructural elements in a route that can potentially affect a driver’s well-being.