Volpe developed a COVID-19 Waze Traffic Alert Dashboard in March 2020 to track relative changes in weekly traffic jam alerts for all U.S. metropolitan areas. The SDC enabled the team to leverage existing crowdsourced traffic incident activity and rapidly developed a dashboard using existing code. The team has continued to provide weekly updates through 2022. The Waze dashboard provides a rapid indicator of traffic jams covering all U.S. metropolitan areas, increasing accessibility to state, metropolitan, and county-level time trends. This ongoing project aims to enhance the dashboards for broader use by U.S. DOT.

Crowdsourced mobile applications such as Waze can provide real-time and historical data about roadway conditions, when and where users are active. Analytical methods were used to test an application of Waze traffic alerts to a crash prediction model used to guide Tennessee law enforcement resource allocation. To target locations and times more accurately with a high crash propensity, the potential for Waze alerts to improve the temporal and spatial resolution of the model was assessed.  Using the Waze data, the spatial resolution of crash estimates was refined from 42 to 1 square miles, and the temporal resolution was refined from 4 to 1-hour time windows, while improving accuracy. The model’s incorporation of crowdsourced data has shown potential for similar types of data-driven safety approaches elsewhere. SDC enabled the integration of public and private data sources to support these analytical approaches. 

1. Flynn DFB, Gilmore MM, Dolan JP, Teicher P, Sudderth EA. Using Crowdsourced Data to Improve Models of Traffic Crash Propensity: Tennessee Highway Patrol Case Study. Transportation Research Record. March 2022. doi:10.1177/03611981221083305
https://journals.sagepub.com/doi/10.1177/03611981221083305

2. Flynn, D. F. B., M. M. Gilmore, and E. A. Sudderth. Estimating Traffic Crash Counts Using Crowdsourced Data: Pilot analysis of 2017 Waze data and Police Accident Reports in Maryland. November 2018. Report Number : DOT-VNTSC-BTS-19-01 https://rosap.ntl.bts.gov/view/dot/37256

SDC can provide a way for external researchers to access and conduct analytical research on another DOT Cloud Platform. SDC data sharing service provides Research Teams with seamless access through a Virtual Private Cloud  Peering solution. This enables external SDC Users to read and copy data from a Research Cloud into the SDC workstation.

Research Teams can learn new advanced analytical methods in an isolated platform. SDC provides services to enable Research Teams to learn and pilot cloud native technologies on different data types, such as live streaming video. The new advanced analytical methods and technologies facilitates new insights on their study. 

SDC services were leveraged by integrating with an existing DOT database system and providing a data export feature into DOT Reporting Visualization Services. Research Programs are enabled to focus on building powerful data products, and less on building a secure analytical platform. SDC provided services to streamline data imports and connect to enterprise visualization services to allow Research Teams to effectively build dashboards accessible to a broader organization.

SDC services enables Research Programs to focus on their critical program initiatives by modernizing labor intensive  data quality checks and data requests.  Our services allows Research Programs to become more efficient with daily operational tasks. Research Programs are able to direct their resources on supporting quality data and data collection. SDC will tailor existing capabilities to automate data exports using trusted status functionality and leveraging cloud native services to execute data ingest quality checks.

Technical Requirements

Security

Access to SDC Web Portal