Increase access to and usability of your data through smarter storage
Increase access to and usability of your data through smarter storage
Data collection and analysis in one streamlined platform
See how Metropia uncovered and delivered powerful data sets to support regional agency decisions
TxDOT El Paso
A multi-agency collaborative improves their approach to data
With a goal of drastically improving the efficiency of its regional transportation systems, the Texas Department of Transportation (TxDOT) El Paso District has undertaken a proactive role to leverage technological advances, manage available capacity and demand on shorter time-frames and expand collaboration among agencies. Working in partnership with the City of El Paso, Camino Real Regional Mobility Authority and El Paso Metropolitan Planning Organization, TxDOT, under a shared vision, sought out the latest technological solutions and deployed Metropia’s Active Traffic and Mobility Management platform.
In addition, Metropia's platform and data analytics were leveraged to collect and process a vast-array of data pertaining to the region’s performance and operations as part of an initiative to explore the feasibility of using the platform to supplement existing conventional data collection practices to support regional transportation modeling, provide real-time and predictive future roadway segment traveler information (i.e., travel times, delay, reliability, speeds, etc.) and calculate system performance measures among others.
Supporting Technologies
Published Reports & Papers
The Approach
To collect the quantity of data needed to support this project as efficiently and cost-effectively as possible, Metropia’s trip planner (GoEzy) users data was mined and analyzed to provide metrics that meet the needs and efforts undertaken by the regional agencies. As users planned their trips and were navigated to their destinations by Metropia’s app, GoEzy captured pertinent information, formed by available GPS points. That anonymized data were processed to identify, among other things, travel time and speeds, ODs on specific corridors or facilities, arterial delays and daily activity patterns.
In addition, Metropia’s behavior modification engine, INDUCE, provided auxiliary data while adding a layer of operational management support. Through the strategic offering of incentives through INDUCE, Metropia asked travellers micro-survey questions about their trip specifics (nature of trip, drive alone or carpooling, etc) to provide additional data points to the agency. Further incentives were leveraged to increase usage of the app, shift users out of peak traffic travel times, and encourage carpooling.
Finally, Metropia’s platform system evaluation tool, DynusT, was utilized to evaluate future roadway operational improvements.
Project Accomplishments
At the conclusion of this project in June 2017, Metropia’s cost-effective data were mined and analyzed to support transportation planning, design, construction, and operations in the El Paso region. The outcomes of that analysis included:
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Trip departure diurnal curves that can be used to identify peak travel periods as well as serve as input into other transportation models
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Mobility and reliability performance metrics that can be used to identify corridor and regional to regional and corridor specific congestion patterns
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Depiction of aggregate Origin and Destination regional and corridor patterns
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Development of a real-time dashboard for the I-10 corridor that included predictive travel time information as well as performance metrics to support response analysis