Presented at the 2016 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), San Diego, CA (March 2016)

Motorcyclists face a unique set of challenges when operating on public streets and highways. In addition to hazards relevant to automobiles, motorcycle riders must remain vigilant for hazards that pose significant danger uniquely to motorcycles (e.g., uneven terrain, sand/gravel, potholes); however, there is currently no motorcycle-specific hazard tracking or alerting system available for riders. To address this need, we are designing a system for Bayesian Assessments and Real-Time Rider Alerting and Cueing for Upcoming Danger Avoidance (BARRACUDA). BARRACUDA will capture and integrate relevant information from an array of public databases and on-motorcycle and environmental sensors. It will fuse this information and apply advanced probabilistic models and reasoning techniques to generate route-based real-time hazard alerts even when operating on uncertain or incomplete information, to increase rider situation awareness. This paper provides an overview of the BARRACUDA system and early design concepts for an augmented reality (AR) display symbology aimed at providing real-time hazard alerts and while en route to facilitate hazard perception and appropriate rider response.