Latest Index of Traffic Congestion Shows Risk of Uneven Recovery in the U.S. Economy
INRIX Gridlock Index Shows Mixed Regional Performances Underlying Overall Rise in National Traffic Congestion
Kirkland, Washington – June 4, 2013 – Data from the most recent INRIX Gridlock Index (IGI) shows overall levels of U.S. traffic jumped by more than nine percent during April – the second largest year-over-year increase recorded by the IGI. While more commuters and shoppers took to the roads on a nationwide basis, regional measures differed sharply. Midwestern metro areas saw gridlock shoot up while gridlock in the southern metro areas lagged behind, raising questions of a two-speed recovery.
“The latest IGI shows the U.S. economy is getting back to business,” said Bryan Mistele, CEO of INRIX. “However, the pattern we’re seeing in our data shows that the economies in some regions – like the Midwest – are accelerating while others are stuck in a lower gear.”
Overall U.S. gridlock levels grew by 9.4 percent from April 2012 to April 2013 to reach a composite IGI score of 6.9. This means the average trip took drivers in the 100 most populated metro areas nearly seven percent longer because of increased traffic congestion, a side-effect of better economic times. Yet a regional view showed that year-over-year traffic declined in metro areas like Baton Rouge (-38%), Oklahoma City (-32%), Louisville (-26%) and New Orleans (-21%), consistent with a pattern for the South that emerged late last year. The economies in the nation’s other regions fared much better, with traffic growing in northeastern metro areas by 10 percent and in western metro areas by 13 percent. With 14 percent year-over-year growth, metro areas in the Midwest showed the strongest regional performance.
The mixed performance seen in the latest IGI data is reflected in other recent economic news. Data through March 2013 from the S&P/Case-Shiller Home Price Indices showed the highest increase in U.S. house prices since 2007 (1), while the Conference Board’s gauge of economic sentiment hit a five-year high in May (2). April’s Fed Beige Book, however, showed economic observers were more cautious in southern districts like Atlanta and Richmond, as they reported mixed sales activity, lower expectations for manufacturing activity and hiring restrained by uncertainty over fiscal and healthcare policies (3).
INRIX Gridlock Index (IGI) Methodology
The IGI draws data from the INRIX Traffic Data Archive http://scorecard.inrix.com/scorecard/, a historical traffic information database comprised of data collected from hundreds of public and private sources, including a crowd-sourced network of millions of vehicles and mobile devices.
Drawing on almost three years of trend data, INRIX has developed methods to interpret real-time traffic data to establish monthly and annual averages of traffic patterns in all major U.S. metropolitan areas. These same methods can aggregate data over periods of time to provide reliable information on speeds and congestion levels for given segments of roads. Using this proprietary data collected from INRIX’s extensive network, the IGI analyzes and measures traffic trends in 100 of the top metropolitan areas in the U.S. The metropolitan areas used in the IGI are defined by the Core-Based Statistical Areas (CBSA), as determined by the United States Census Bureau.
There are two key building blocks for the analysis used in the IGI:
• Reference Speed (RS): An uncongested “free-flow” speed is determined for each road segment using the INRIX Traffic Data Archive.
• Calculated Speed (CS): Speed data from the INRIX Traffic Data Archive is analyzed to determine the “calculated speed” for each 15-minute period of each day, for each road segment every month (e.g. Monday from 06:00 to 06:15 for April 2012). Thus, each road segment has 672 corresponding calculated speed values per week – representing four 15-minute time windows for each hour of the day, multiplied by seven days in a week.
To assess congestion across a metropolitan area, INRIX utilizes and adapts several concepts that have been used in similar studies and previous INRIX analyses.
The IGI represents the barometer of congestion intensity. For a road segment with no congestion, the IGI would be zero. Each additional point in the IGI represents a percentage point increase in the average travel time of a commute above free-flow conditions during peak hours. An IGI of 30, for example, indicates a 20-minute free-flow trip will take 26 minutes during the peak travel time periods, which is a 6-minute (30 percent) increase over the free-flow travel time. For each road segment, an IGI Score is calculated for each 15-minute period of the week, using the formula IGI= (RS/CS) – 1.
“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 06:00 to 10:00 a.m. and 3:00 to 7:00 p.m., 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 computed as follows, once the IGI is calculated for each road segment:
• STEP 1: For each of the 40 peak hours, all road segments analyzed in the CBSA are checked. Each road segment where the IGI is greater than 0 is contributing congestion and is analyzed further.
• STEP 2: For each road segment contributing congestion, the amount the IGI is greater than 1 is multiplied by the length of the road segment, resulting in a congestion factor.
• STEP 3: For each 15-minute period, the overall metropolitan area congestion factor is the sum of the congestion factors calculated in STEP 2.
• STEP 4: To establish the metropolitan IGI for a given 15-minute period, the metropolitan congestion factor from STEP 3 is divided by the number of road miles analyzed.
• STEP 5: A peak period IGI is determined by averaging the 15-minute indices from STEP 4.
1) Standard and Poor, “Home Prices See Strong Gains in the First Quarter of 2013
According to the S&P/Case-Shiller Home Price Indices,” May 28, 2013,
2) The Conference Board, “The Conference Board Consumer Confidence Index® Improves in May,” May 28, 2013,
3) Board of Governors of the Federal Reserve System, “Summary of Commentary on Current Economic Conditions by Federal Reserve District,” April 17, 2013, http://www.federalreserve.gov/monetarypolicy/beigebook/files/Beigebook_20130417.pdf.
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Media ContactJim Bak