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Secure Data Commons - ProjSpotlightFraARDS

Agile Railroad Data Science Programs (ARDS)

 

Integrate railroad data with external datasets, from other DOT modes and other government agencies

Agile Railroad Data Science (ARDS) project integration into SDC continues to help accomplish Federal Railroad Administration (FRA) Safety Data objectives using the SDC to modernize FRA’s analytical capabilities, and to establish a reliable “hub.” The SDC supports FRA’s vision to integrate railroad data with external datasets to facilitate greater understanding and improvement of railroad safety. The FRA has already made Railroad Accident and Incident, Highway Rail Grade Crossing Incident, Activation Failure and False Proceed and Positive Train Control data available in SDC and is currently working to ingest external datasets, such as population data from the 2020 Decennial Census. Additionally, the SDC is working on developing a data visualization service to make it easier for users to export data into a data visualization tool.
 

Sponsor: Federal Railroad Administration

Last updated April 2022

Secure Data Commons - ProjSpotlightOSS4ITS

Open-Source Software for Intelligent Transportation Systems (OSS4ITS)

 

OSS4ITS advances the deployment of interoperable transportation systems

USDOT has several development projects underway that are using Agile Development practices to create open-source software with robust Communities of Practice. These include, but are not limited to, the Secure Data Commons (SDC), the Operational Data Environment (ODE), CARMA, and the V2X Hub. Each of these projects support different parts of an overall US DOT Intelligent Transportation Systems (ITS) deployment architecture and are managed separately, with individual development teams. OSS4ITS is an ecosystem that promotes the deployment of interoperable transportation systems.

Architecture Reference for Cooperative and Intelligent Transportation (ARC-IT)

OSS4ITS ecosystem promotes development of open-source code that ensures code reuse and shared architecture. The software suite provides a common framework for planners and engineers to design and implement interoperable systems to support research teams in DOT, software companies, and device manufactures.

Upcoming OSS4ITS Reference Implementation

Research teams in DOT, academics, and the private sector are looking for the latest Work Zone data technologies in progress. The full functionality of OSS4ITS software suite (including SDC) enabled data exchanges for the Work Zone use case. The team prepared and informed transportation agencies and companies on how OSS4ITS software tools work seamlessly for this use case. Also the TFHRC cloud solution established the connection between CARMA analytics and SDC so that CARMA data can be transferred via AWS.

Last updated December 2022

Secure Data Commons - ProjSpotLightWazeAlerts

Highlights from the Waze Alerts User Community

 

Compiled SDC Crowdsourced Traffic Data on Traffic Jams, Hazardous Roadside Parking, Crashes, and Reported Road Closures

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. SDC enabled the team to leverage existing crowdsourced traffic incident activity, and rapidly developed 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.

Adirondack hot spots and daily trends

Waze alerts showed how traffic jams, crashes, and hazardous parking fluctuated through the Adirondack park’s main road during hiking days. These informed options for a shuttle route, planned to start in summer 2022.

Regional crash monitoring

Waze alerts are providing crash analyses to 31 parks in the Inter-Mountain Region. Waze can supplement current NPS crash data, or in cases where NPS crash data is not available, Waze can act as the major source of crash trends.

Mount Rainier entrance congestion

Waze alerts are giving information about how popular park entrances fill up and create traffic jams. These can be related to the gateway communities and roadways used to enter the park from visitor home locations (e.g. Seattle, Portland, Spokane).

Last updated July 2022

Secure Data Commons - ProjSpotLightWazeCovid

COVID-19 Waze Traffic Alert Dashboard

Waze COVID-19 Traffic Alert Dashboard

 

Visualizing Changes in Roadway Transportation Activity with the COVID-19 Waze Traffic Alert Dashboard

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.

Sponsor: Volpe Center
Last updated July 2022

Secure Data Commons - ProjSpotLightWazePilot

Waze Pilot: Explore the Possibilities of Using Data for Safety Applications

 

Better Understand and Mitigate Crash Risk by Integrating Public and Private Data Sources

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

Sponsor: OST-P Safety Data Initiative
Last updated July 2022