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INRIX Gridlock Index for May 2013 Shows U.S. Traffic Congestion Continues to Rise, Signaling Good News for the Economy

Kirkland, Washington – June 26, 2013 – Data from the most recent INRIX Gridlock Index (IGI) shows traffic congestion rose nationally more than nine percent in May, signaling the continued strengthening of the national economy as retail sales increased 0.6 percent month-over-month in the U.S., led by a 1.8 percent jump in auto sales, the biggest increase since November. However, regional traffic measures continue to suggest an uneven economic recovery in certain areas of the country.

Traffic congestion increased 9.3 percent from May 2012 to May 2013 to reach a composite IGI score of 7.2. This means the average trip took drivers in the 100 most populated metro areas just over seven percent longer due to increased traffic. Metropolitan areas in the Western U.S. experienced the largest increases (15.7% YoY) followed by the Northeast (11.2% YOY) and Midwest metro areas (9.1% YoY). The Southern region continued to display the most modest increase in traffic levels (2.4% YoY).

“The overall rise in traffic in the first five months of the year is indicative of increased confidence in the direction of the economy,” commented Bryan Mistele, CEO of INRIX. “Renewed consumer spending, especially on new vehicles, means more shoppers at stores, more cars on the road and more traffic on our streets.”

The rise in traffic levels continued to be uneven not only across regions, but also within regions as well. For example, in April 2013, traffic congestion in Midwestern metro areas in April 2013 increased more than any other region on a year-over-year basis. However, the Midwest was only the third most important contributor to the rise in traffic congestion nationwide in May 2013.The monthly Creighton University Mid-America Business Condition Index, a leading economic indicator for a nine-state region, reflects this decline in its May report. The Creighton Index, which measures the strength of the Midwest economy on a scale from 0-100, shows a decline to 56.2 in May from 56.8 in April, with components of the Creighton Index including employment, wholesale prices, confidence, new orders and production each lower than their April readings.

The rise in national traffic congestion recorded by IGI is also aligned with the Federal Reserve’s recent pronouncement on June 19 that economic activity has been expanding at a moderate pace. Fed officials said the economy is expected to grow at an annual rate of 2.3 to 2.6 percent in 2013, slightly below the top end of the 2.3 to 2.8 percent growth previously forecast, and that the unemployment rate in 2013 is expected to fall to a range of 7.2 to 7.3 percent, which is below the 7.3 to 7.5 percent previously forecast. The Fed also boosted its outlook for gross domestic product and projections for falling unemployment in 2014 and now expects GDP to grow 3.0 to 3.5 percent in 2014, above a previous estimate of 2.9 to 3.4 percent, and expects unemployment to fall to 6.5 to 6.8 percent, below the 6.7 to 7.0 percent previously forecast.

The IGI draws data from the INRIX Traffic Data Archive, 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.¬¬

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