Methodology

Source Data

The raw data comes from the historical traffic data warehouse of the INRIX Smart DriverNetwork. Since 2006, INRIX has acquired tens of billions of discrete “GPS-enabled probe vehicle” reports from vehicles traveling the nation’s roads – including taxis, airport shuttles, service delivery vans, long haul trucks, and consumer vehicles.

INRIX has developed efficient methods for interpreting probe vehicle reports that are provided in real-time to establish a current estimate of travel patterns in all major cities in the United States. These same methods can aggregate data over periods of time (annually in this report) to provide reliable information on speeds and congestion levels for segments of roads. With the nation’s largest probe vehicle network, INRIX generates the most comprehensive congestion analysis to date, covering the nation's 100 largest metropolitan areas and essentially all of the nation's major roadways.

Metropolitan Area

The US Census Bureau definition of Core Based Statistical Areas is used to define metropolitan areas. This report uses the latest 2008 census estimates to identify the top 100 areas. Note that previous reports used 2007 population estimates, and in 2008 data, the Daytona Beach, Florida area CBSA dropped from the top 100 and the Provo-Orem, Utah area CBSA moved up to the top 100. This report includes the Provo-Orem CBSA and has adjusted data accordingly.

Roads/Segments Analyzed

This report focuses on the major limited access roads in the United States. In all of its products, INRIX utilizes an emerging industry convention known as “TMC location codes” developed and maintained by the nation’s leading electronic map databases vendors to uniquely define road segments. The typical road segment is the interchange and the portion of linear road leading up to the interchange across all lanes in a single direction of travel. The length of a segment will depend upon the length of the distance between interchanges. For this report, over 110,000 road miles in over 48,000 discrete road segments have been analyzed.

Analysis Time Period

The focus of this report is the calendar year 2009. In some cases, calendar year 2006, 2007 and 2008 data is utilized to enable year over year comparisons.

Road Segment Data

• Reference speed (RS): For each road segment, all probe vehicle reports obtained in overnight hours (where congestion is usually unlikely) in 2009 are analyzed.
• Hourly average speed (HS): All probe vehicle reports for each road segment are grouped by hour of day, day of week (e.g. Monday from 3 to 4pm) and an “average speed” for each time slot is established for each road segment. Thus, each segment has 168 corresponding hourly average speed values – representing 24 hours of each day times the seven days in a week.

Overall Congestion by Metropolitan Area

• Travel Time Index (TTI): TTI is the ratio of peak period travel time to free flow travel time. The TTI expresses the average amount of extra time it takes to travel in the peak relative to free-flow travel. A TTI of 1.3, for example, indicates a 20-minute free-flow trip will take 26 minutes during the peak travel time periods, 6-minute (30 percent) travel time tax (T³). For each road segment, a TTI is calculated for each hour of the week, using the formula TTI = RS/HS.
• “Drive Time" Congestion: To assess and compare congestion levels year to year and between metropolitan areas, only “peak hours” are analyzed. Consistent with similar studies, peak hours are defined as the hours from 6 to 10 am and 3 to 7 pm, Monday through Friday – 40 of the 168 hours of a week.
• For each Metropolitan Area, an overall level of congestion is determined for each of the 40 peak hours by determining the extent and amount of average congestion on the analyzed road network. This is easy to compute once TTI’s are calculated for each segment:
  • STEP 1: For each of the 40 peak hours, all road segments analyzed in the CBSA are checked. Each segment where the TTI > 1 is contributing congestion, and it is analyzed further.
  • STEP 2: For each segment contributing congestion, the amount the TTI is greater than 1 is multiplied by the length of the segment, resulting in a congestion factor.
  • STEP 3: For a given hour, the overall metropolitan congestion factor is the sum of the congestion factors calculated in STEP 2.
  • STEP 4: To establish the Metropolitan Travel Time Index for a given hour, the metropolitan congestion factor from STEP 3 is divided by the number of road miles analyzed.
  • STEP 5: A peak period Metropolitan Travel Time Index is determined by averaging the hourly Metropolitan Travel Time Indices from STEP 4.

New for this report, INRIX is introducing a variant of the Travel Time Index in this 2009 Annual Update as a means of communicating more directly the impact of congestion – the Travel Time TaxTM. While all calculations driving the Scorecard continue unchanged as described above, the Travel Time Tax, or T³, takes the portion of the TTI above 1.00 and turns it into a percentage. For example, a TTI of 1.25 equates to a T³ of 25%. Much like a sales tax, T³ can be considered that additional cost of travel above uncongested conditions. Throughout the report, T³ is being utilized where TTI was utilized in the past. The methodology is the same; communications of the results is what has changed.

Bottlenecks

Each road segment’s bottleneck factor can be compared with others in a metropolitan area and against all bottlenecks nationally. It can also be compared year-to-year, as we have in this Scorecard.

Congestion – and how to measure it – can be in the eye of the beholder. Is congestion defined as how bad a road segment is at its worst or is it how often the segment gets “congested” (and what is the threshold for “congestion” anyways – tapping the brakes, stop and go conditions, etc.)? INRIX has developed a method that combines both the amount of time a road segment is congested with the intensity of congestion during those periods.

• The same RS and HS values are utilized as in the overall congestion by metropolitan area portion of the study;
• All 168 hours of the week are considered, not just the 40 “peak hours.” As will be evident in the data, severe bottlenecks aren’t just limited to peak hours;
• For each hour of the week that the average speed is less than 50% of the reference speed, the hour is considered “congested;”
• For all “congested” hours, the average intensity of the congestion is determined by establishing an average travel time ratio;
• The total Bottleneck factor equals the number of hours of congested by the average travel time ratio.
• Each road segment’s Bottleneck factor can be compared with others in a metropolitan area and against all Bottlenecks nationally. It can also be compared year-to-year, as we will do going forward.