The Use of Data in Planning for Operations: State-Of-The-Practice Review

Chapter 2. Use of Data in Monitoring Transportation Operational Performance and Tracking Performance Objectives

Data Needs for Monitoring Performance—Perspective from National Literature

Monitoring the operational performance of elements of the transportation system is becoming more prevalent, particularly in large metropolitan areas on freeways. Transportation agencies in major metropolitan areas often have large amounts of archived or real-time data collected through road sensors and their central control systems, although there are significant limitations to the use of this data for performance monitoring.⁽²⁾ Typically, the sensors cover a limited portion of the freeway network, and the failure rate for in-pavement and roadside traffic sensors is high (e.g., 35 percent for the California Freeway PeMS loop detectors). In addition, arterial roads are either not covered by these sensors or the data collected is not useful for travel-time analysis.⁽²⁾

The recent emergence of probe data is creating more opportunities for transportation operating agencies and MPOs to monitor and analyze travel times according to elements of the network and routes and to aggregate origin-destination (O-D) travel times geographically. In 2013, FHWA made a national set of average travel time probe data freely available to States and MPOs to use for their performance management activities. This data set is referred to as the National Performance Management Research Data Set. There are also several commercial probe data systems available based on cell phone location, Global Positioning System (GPS)-equipped vehicles (usually fleets), and cell phones or other personal devices with GPS systems.⁽²⁾ Prior to the release of the National Performance Management Research Data Set, data from these systems were typically only available for purchase through the private sector. Instead of purchasing this data, one of the MPOs interviewed for this state-of-the-practice review found it much more cost effective to deploy its own sensors.

As outlined in SHRP2 L05 Incorporating Reliability in the Transportation Planning Process – Technical Guidance, data used to monitor current travel time reliability conditions and examine past reliability trends by planning and operating agency departments include the following:⁽³⁾

• Automated spot traffic data (e.g., loop, acoustic, radar traffic detectors) including volume, speed, occupancy and other data[.]
  
  
• Travel time data (probe data)[.]
  
  
• Incident logs[.]
  
  
• Crash data[.]
  
  
• Operational data (e.g., logs of messages displayed on variable message signs, 511 calls or alerts)[.]
  
  
• Weather data.

On the national level, the Texas Transportation Institute (TTI) produces the Urban Congestion Report for FHWA on a quarterly basis to disseminate congestion and reliability trends for the United States as a whole and for cities with freeways instrumented with traffic sensors.⁽⁴⁾ The report provides results for three primary operations performance measures: congested hours, travel time index, and planning time index. Table 1 contains the definitions of these key performance measures and the input data for the measures.

The National Transportation Operations Coalition developed a set of 12 key operations performance measures in 2005, and in 2007, those measures were pilot tested and refined for National Cooperative Highway Research Project 20-7, Guide to Benchmarking Operations Performance Measures.⁽⁵⁾ The report was developed by the University of Maryland in 2008 and documents the pilot testing and review by State transportation departments, cities, and MPOs and the resulting set of performance measures. The refined set of operations performance measures include the following:⁽⁵⁾

• Customer satisfaction.
  
  
• Extent of congestion—spatial.
  
  
• Extent of congestion—temporal.
  
  
• Incident duration (i.e., the time elapsed from the notification of an incident until all evidence of the incident has been removed from the incident scene).
  
  
• Recurring delay vehicle.
  
  
• Speed.
  
  
• Throughput.
  
  
• Travel time.
  
  
• Travel time—reliability.
  
  
• Travel time—trip.

The pilot test sites also tested data collection and compilation procedures, and the report contains a pertinent table showing the data collection method, basic data obtained from the data collection method, and the performance measure that the data collection supported. The table from this report is presented in figure 1.

View long description of this figure

The data needed to support key traffic incident management (TIM) performance measures—including roadway clearance time, incident clearance time, and secondary crashes, as well as the data needed to support TIM modeling and analysis as defined in the 2012 FHWA report, Analysis, Modeling, and Simulation for Traffic Incident Management Applications—is listed as follows:⁽⁶⁾

• Incident type (crash, disabled vehicle, fire, debris, abandoned vehicle).
  
  
• Incident collision type (fixed object, overturn, vehicle/side, vehicle/head-on, vehicle/rear-end).
  
  
• Incident “timeline” data (time stamps for start of incident, detection, verification, on-scene arrival, lane/shoulder open, all clear).
  
  
• Incident severity (KABCO injury scale).
  
  
• Incident location (route, travel direction, milepost or GPS coordinates).
  
  
• Incident blockage.
  
  
  • Cross section feature affected (lane, partial lane, right shoulder, left shoulder, median, off maintained way)[.]
    
    
  • Lane type (through/general purpose, through/high-occupancy vehicle (HOV), auxiliary, on-ramp, off-ramp)[.]
    
    
  • Begin/end time.
  
  
  
• Number of involved vehicles.