The text discusses how Mapbox utilizes data and technology to enhance the accuracy of travel time estimates during challenging weather conditions, especially in Denver where winters and heavy snowfall impact traffic dynamics. By analyzing 200 million miles of anonymous telemetry data collected between November 2018 and April 2019, Mapbox was able to improve the prediction of Estimated Travel Times (ETAs) by combining historical and live-traffic data, which proved particularly beneficial during storms and other atypical conditions. The analysis highlighted the limitations of relying solely on typical data, as predictions were often overly optimistic during extreme weather, while live-data integration significantly improved both accuracy and symmetry of ETAs. The insights derived from a small fraction of the data underline the potential for enhancing navigation and logistics services, emphasizing the importance of incorporating dynamic traffic information into routing systems to better handle unpredictable traffic patterns caused by weather and other events.