Lesson
Ensure compatibility of data format of the field-weather monitoring sensors with the central software in the transportation management center.
Statewide systems implementation experience from iFlorida Model Deployment
01/30/2009
Florida,United States
Background (Show)
Lesson Learned
One of the features of the iFlorida deployment was the integration of weather data into the traffic management system at the District 5 Regional Transportation Management Center (D5 RTMC). This weather data was provided in several forms. FDOT deployed a number of Road Weather Information System (RWIS) stations to collect new weather data. FDOT also contracted with a third party provider to supply the RTMC with weather data, including current and forecast weather data specific to iFlorida road segments and severe weather alerts tied to specific locations. FDOT planned to use this data in a number of ways, including identifying appropriate speed limits for setting variable speed limits (VSL) and warning travelers of adverse weather conditions.
However, the weather data was little used during the period considered in the iFlorida evaluation report. In large part, this was due to limitations in the CRS, such as not including appropriate filtering of the weather data so that FDOT could select the types of weather conditions that generated alerts for the operators. These limitations were likely compounded by the fact that FDOT was focused on correcting other problems with the CRS, problems that included incorrect computations of travel times, rather than correcting problems with CRS use of weather data. With problems existing with the primary types of information needed to support traffic management (e.g., travel times), there was little advantage to improving sources of secondary information, like weather data. In retrospect, it might have been better to introduce weather data into the transportation management process at FDOT after the primary transportation management tools (e.g., travel time measurements, travel time forecasts, traveler information) were more stable. While deploying and operating these weather systems, FDOT did identify a number of lessons learned that it might use to improve future operations and that other locales may find useful. A summary follows:
However, the weather data was little used during the period considered in the iFlorida evaluation report. In large part, this was due to limitations in the CRS, such as not including appropriate filtering of the weather data so that FDOT could select the types of weather conditions that generated alerts for the operators. These limitations were likely compounded by the fact that FDOT was focused on correcting other problems with the CRS, problems that included incorrect computations of travel times, rather than correcting problems with CRS use of weather data. With problems existing with the primary types of information needed to support traffic management (e.g., travel times), there was little advantage to improving sources of secondary information, like weather data. In retrospect, it might have been better to introduce weather data into the transportation management process at FDOT after the primary transportation management tools (e.g., travel time measurements, travel time forecasts, traveler information) were more stable. While deploying and operating these weather systems, FDOT did identify a number of lessons learned that it might use to improve future operations and that other locales may find useful. A summary follows:
- Explore the potential for use of the National Weather Service microwave tower sites as a cost-effective approach for deploying RWIS stations at remote sites. Deployment costs were reduced because utilities were already available at those sites and the microwave network could be used to transmit the collected data. However, the National Weather Service (NWS) indicated that locating some weather observation equipment on a microwave tower could violate NWS equipment siting and exposure standards. For example, a temperature sensor should be at least 100 feet from any paved or concrete surface and precipitation gauges should not be located close to isolated obstructions such as trees and buildings.
- Beware of limitations in receiving the RWIS data through National Weather Service. FDOT D5 established a method to receive the RWIS data through the National Weather Service Meteorological Assimilation Data Ingest System (MADIS). This method of providing the data to the D5 RTMC introduced a 15-minute lag between the time the data was measured and when it reached the RTMC, which could have reduced its effectiveness in supporting real-time decision making. FDOT also successfully contracted with a third-party provider of weather data to supply road-specific weather condition and forecast data to FDOT. However, the CRS software that was to help integrate this weather data into FDOT's transportation management decision making process did not perform as expected. Simultaneously introducing new traffic data collection methods, transportation management software, and weather data into the transportation management process is difficult. One may want to wait until the primary transportation management tools and practices are stable before introducing weather data into the process.
- Ensure that the contract with the vendor requires establishing compatibility of the RWIS data format with the RTMC’s central software. The interface between the software that compiled and disseminated data from the RWIS stations and the CRS software, which was to use this data, was a problem, and the contractual language between the two contractors involved did not make it clear who was responsible for fixing the problem. When systems developed by different contractors must interact, the contract should clearly define the interface that will be used and the responsibilities of the contractors in developing that interface.
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Systems Engineering
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Software / Hardware Development Field Installation
Keywords
RWIS, ESS, Environmental Sensor Station, RWIS Station, road monitoring, weather station, environmental sensing station, VSL
Lesson ID: 2010-00538
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