KIRKLAND, Wash., March 5, 2013 /PRNewswire/ -- The U.S. economy is coming back, and so are its traffic jams. The most recent INRIX Gridlock Index (IGI) shows drivers spent more time in traffic during January this year than in January 2012. The 1.6 percent increase marks the second straight month that gridlock has risen over the prior year, breaking a string of declines that stretched back to 2011.
INRIX Gridlock Index data for January 2013 shows traffic increased by almost two percent year-over-year, a good sign for the economy.
Now expanded to cover 100 U.S. metropolitan areas, the latest IGI brings some good news to those looking for green shoots in the nation's economy. Traffic congestion usually increases as companies ship more goods, hire more people and consumers spend more money.
"While these increases bode well for our economic outlook, we don't expect them to bring a smile to the face of the average commuter," said Bryan Mistele, CEO of INRIX. "Stalled traffic is actually a side effect of a moving economy as people go to work, spend money and businesses respond to demand."
IGI's positive direction was also confirmed by the latest Thomson Reuters/University of Michigan index of consumer sentiment, which saw February's reading beating expectations to hit a three-month high.
January's composite IGI score of 6.4 meant that the average trip took drivers in the 100 most populated metro areas 6.4 percent longer because of increased traffic congestion. While the latest IGI trends suggest economic conditions might be getting better, a look over the longer-term shows the economy still has a ways to go. January's IGI score is still far below the level last reached in 2010, when U.S. GDP growth bounced back into positive territory after two years of contraction.
While the INRIX Gridlock Index for January 2013 shows the economy might be stabilizing, it has not recovered all of the ground lost since 2010.
Fifty-five of America's 100 largest metropolitan areas as measured by IGI experienced increases in traffic congestion in January 2013. Among them, the following metro areas had the biggest changes in gridlock from January 2012 to January 2013:
- Salt Lake City (up 111 percent) and Ogden, Utah (up over 200 percent) experienced the biggest increases in traffic congestion in line with recent reports of higher-than-expected levels of income, sales and other tax receipts in the Beehive State.
- Traffic congestion in Greensboro, North Carolina rose by 192 percent, aligned with recent job growth and economic expansion from increased investment by the regions local employers as the state rebounds from having the nation's fifth-highest unemployment rate.
- Traffic congestion increased over 100 percent in Knoxville, Tenn. offering another potential indicator of an improving economy along with recent predictions of modest economic growth for the state this year.
- Gridlock in Richmond, Va. rose by 86 percent, underlining the impact of the budget debate on a state that would feel the effects of federal spending cuts.
- Traffic in Louisville, Ky. decreased 61 percent, the largest decline among IGIs 100 metro areas.
- Traffic in Youngstown, Ohio decreased by 57 percent and declined by 44 percent in Akron, Ohio, illustrating the difficult road ahead for a state that recently received low marks for its citizens' overall level of financial opportunity.
- Traffic congestion in Buffalo, New York decreased by 45 percent, highlighting the continuing challenge for a manufacturing region that has been in decline for over three decades.
- Gridlock in Fresno, California decreased by 49 percent, highlighting the stark differences in fortune between the state's Central and Silicon Valley.
INRIX Gridlock Index (IGI) Methodology
The INRIX Gridlock Index 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 approximately 100 million 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. cities. 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 and 15:00 to 19:00, 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.
INRIX® is a leading traffic intelligence platform delivering smart data and advanced analytics to solve transportation issues worldwide. INRIX crowd-sources real-time data from approximately 100 million vehicles and devices to deliver traffic and driving-related insight, as well as sophisticated analytical tools and services, across five industries in 32 countries.
With more than 200 customers and partners including Audi, ADAC, ANWB, BMW, the BBC, Ford Motor Company, the I-95 Coalition, MapQuest, Microsoft, O2, Tele Atlas, Telmap, Toyota and Vodafone, INRIX's real-time traffic information and traffic forecasts help drivers save time every day.
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