Roadway Hazard Alert System for Motorcycles

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 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, Charles River Analytics proposes to design and demonstrate the feasibility of a system for Bayesian Assessments and Real-Time Rider Alerting and Cueing for Upcoming Danger Avoidance (BARRACUDA). BARRACUDA captures and integrates relevant information from an array of public databases and on-motorcycle and environmental sensors. It fuses this information and applies advanced probabilistic models and reasoning techniques to generate route-based risk assessments and real-time hazard alerts, even when operating on uncertain or incomplete information. This information is then presented to riders through a web-based interface tailored for mobile devices to illustrate the hazards and overall risk of traversing a planned route. We also employ a heads-up display symbology, designed using proven techniques to minimize rider distraction and facilitate direct perception and action, to provide riders with real-time cues and alerts for potential upcoming roadway hazards