The Mobility Monitoring Program (http://mobility.tamu.edu/mmp/) provides valuable insights with respect to using archived traffic detector data for monitoring highway performance (e.g., traffic congestion and travel reliability). The Mobility Monitoring Program was initiated in 2000 using archived freeway detector data from 10 cities. By 2004, the Program had grown to include nearly 30 cities with about 3,000 miles of freeway. Over the first four years of the Program, the project team gained valuable experience in the course of gathering archived data from State and local agencies. These experiences were captured in the report "Lessons Learned: Monitoring Highway Congestion and Reliability Using Archived Traffic Detector Data." The lessons documented in this report focus on three general areas: analytical methods, data quality, and institutional issues. They are useful to the Federal Highway Administration (FHWA) as it expands the national congestion monitoring program and to State and local agencies as they develop their congestion monitoring capabilities.
Any conditions affecting traffic should be part of performance monitoring. In the past, many public agencies have struggled to collect credible data about transportation system performance. Traffic management centers are beginning to help fill the data gap for performance monitoring; however, many agencies still have inadequate resources to consider collecting data other than speeds or travel times that are directly related to system performance.
- Collect information on activities and events that can affect system performance. A few agencies, have recognized that there are numerous activities and events (some beyond their agency's control) that affect system performance. Thus, despite their best efforts and significant resource expenditure, some agencies may see a decline in the measured system performance. To be effective, performance monitoring must also gather information on activities and events that can affect system performance. Examples of these activities include:
- System usage
- Traffic incidents
- Work zones
- Severe or inclement weather
- Special events
- Economic conditions
- Data quality
- Consider the information included in performance-monitoring reports. By tracking these influential factors, performance-monitoring programs could better target why performance changes at certain times and what solutions are most appropriate. The data can also be used to demonstrate the benefits of operations strategies. As an example, the Urban Congestion Reporting (UCR) Program performed for the FHWA reports several mobility and reliability performance measures on a monthly basis. The performance reports include these contributing factors:
- Data quality (number of usable days of data)
- Monthly precipitation compared to normal
- Number of days with bad weather (low visibility, heavy or freezing precipitation)
- Monthly incident rate compared to normal
- Consider what is included in ITIP performance reports. Performance reports in FHWA's Intelligent Transportation Infrastructure Program (ITIP) provide another example of reporting transportation performance in the context of possible explanatory measures. In addition to several mobility and reliability performance measures, the following are included:
- System usage (peak period and total vehicle-miles of travel [VMT])
- Number of bad weather days (significant rainfall, freezing precipitation, or low visibility)
- Total number of traffic incidents reported
- Data quality (completeness, validity, and coverage of archived traffic data)
As shown in this experience, it is not always enough to just collect speed or travel time data when conducting performance-monitoring analyses. It is also important to consider and collect information on any activities or events that affect traffic conditions. Some examples of these experiences are shown above.
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