Abstract
Real-time navigation systems may issue generic hazard alerts, such as "car on shoulder," which may not differentiate between varying risk situations. A system for collecting multidimensional data about a reported event can be used to enhance these alerts. After an initial hazard report, the system can distribute simple prompts, for example, binary-choice questions such as "Are people outside the car? To subsequent passing drivers to gather contextual details. These crowdsourced responses can be aggregated, and an algorithm on a server may assess the data against a set of rules to determine a severity level. Based on this assessment, the system can dynamically generate and deliver a context-aware alert to approaching drivers. This alert can feature tailored text, audio cues, or visual icons that communicate the specific nature and potential urgency of the risk.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Zucker, Chaim, "Generating Dynamic Hazard Alerts via Multidimensional Crowdsourced Data Collection", Technical Disclosure Commons, (May 20, 2026)
https://www.tdcommons.org/dpubs_series/10197