Kirkland, Washington – August 27, 2013 – Data from the latest INRIX Gridlock Index (IGI) showed that United States traffic congestion rose by more than seven percent on a year-over-year basis in July 2013, highlighting the overall U.S. economy’s improvement since July 2012’s plunge of 26 percent and underlining the fine line the Federal Reserve must walk as it considers removing the unprecedented support it has provided since the start of the crisis.
IGI data for July 2013 shows traffic congestion at the national level increased by more than seven percent year-over-year and has rebounded strongly from July 2012.
“Traffic reflects the net effect of the shopping, shipping and commuting that keeps our economy ticking,” said Bryan Mistele, CEO of INRIX. “We’ve taken a step forward from last year but we’ll be watching closely to see how the economy holds up as the Fed goes back to business as usual.”
National levels of traffic congestion increased by 7.4 percent from July 2012 to July 2013 to reach a composite IGI score of 6.4, meaning the average trip took drivers in the 100 most populated metro areas over six percent longer due to increased traffic.
July’s traffic congestion data also highlighted interesting regional trends:
• The Midwest had the greatest rise in traffic congestion as a large majority of its most populated metro areas (71%) saw year-over-year traffic increases in July. Double-digit increases in many of its largest metro areas, including St. Louis (39%) and Cleveland (29%) underlined the forward-looking optimism found in a recent survey of business conditions in the region.
• The Northeast experienced an increase in traffic congestion in a majority of its most populated metro areas (58%). Philadelphia’s 20 percent year-over-year increase aligns with recent news of increased manufacturing activity in the metro area. While New York’s metro region experienced 10 percent traffic growth year-over-year, northern neighbors like Syracuse and Buffalo had less hopeful economic tidings, as year-over-year traffic levels declined 52 percent and 39 percent respectively. Moody’s Investor Services took note of the ailing upstate economy in a recent report.
• The most populated metro areas in the West were split almost evenly between advancers (52%) and decliners (48%) for July year-over-year traffic growth. The San Francisco metro area topped the list with a huge year-over-year increase of 35 percent. While some of this was due to a short-lived transit strike in July, most of it was likely caused by the strength of the region’s ongoing boom which is also reflected in record real estate prices. The year-over-year traffic increase in the Portland metro area was the second highest in the region (34%), confirming recent news of its economic health and a rate of employment growth that has outpaced the state. In the Bakersfield metro area, traffic plunged by 76 percent year-over-year, underlining the economic challenges for an area in which a quarter of the population lives in poverty. There was also bad news for the nearby Fresno metro area: its traffic congestion on a July year-over-year basis plunged by 67%, mirroring its high unemployment rate of 12.3%.
• The South saw 54% of its most populated metro areas experience year-over-year traffic growth in July. The Memphis metro area experienced a 51 percent year-over-year increase, in line with a recent business survey that pointed to positive economic sentiment. The Tulsa metro area led the decliners in the region for year-over-year traffic congestion (-45%) ahead of last week’s report that the Oklahoma jobless rate rose in July for the third straight month.
IGI data for July 2013 shows year-over-year gridlock increased at an accelerated pace in the Midwest, and at a more moderate pace in the Northeast, West and South. At the national level, gridlock increased by over seven percent year-over-year.
The national IGI score for June 2013 shows the average trip took just over 6 percent longer due to traffic.
INRIX Gridlock Index (IGI) Methodology
The IGI draws data from the INRIX Traffic Data Archive https://inrix.com/scorecard/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.¬¬
