Abstract
This paper studies the use of positioning techniques for sensing when pedestrians are at an increased risk of a traffic accident. Such sensing techniques could support augmented reality applications that increase pedestrian safety. We discuss requirements for pedestrian risk detection from rural to urban environments and consider algorithms relying on inertial and positioning sensors for distinguishing safe and unsafe walking locations. We study the limits of this approach through walking trials in different environments.