Commuting

In May 2006, the U.S. secretary of transportation identified traffic congestion as one of the single largest threats to U.S. economic prosperity and way of life. This is reinforced by the most recent Urban Mobility Report by the Texas Transportation Institute (TTI), which estimated that the cost of traffic congestion in the United States (due to congestion-related delay and wasted fuel) was approximately $115 billion in 2009, a fivefold increase from $24 billion in 1982.

Traffic congestion is highest during the morning and evening commute periods, corresponding to the time when workers make the transition from home to work or from work to home. According to TTI's mobility report, the congestion-related annual delay per U.S. peak period traveler was approximately 34 hours in 2009, up from 14 hours in 1982. The corresponding direct annual cost to a peak period traveler was estimated at $757. This “wasted” cost to the average peak period traveler is an obvious cause of concern in an already struggling economy. At the same time, global climate change, the broad term used to reflect recent global warming trends, has been linked unequivocally to human activity that results in the emission of greenhouse gases. In the United States, energy-related activities account for three quarters of total human-generated greenhouse gas (GHG) emissions, mostly in the form of carbon dioxide (CO2) emissions from burning fossil fuels. Recent projections show that the nation's CO2 emissions would increase from about 5.9 million metric tons in 2006 to 7.4 million metric tons in 2030 if measures were not taken to reduce carbon emissions. While about one half of these emissions come from large stationary sources such as power plants, the transportation sector ranks second and accounts for about one third of all human-generated GHG emissions. Further, the transportation sector is one of the most rapidly rising sources of GHG emissions. For example, total U.S. GHG emissions rose 13% between 1990 and 2003, while those from the transportation sector rose 24% during the same period.

The statistics above should make clear that commuting in urban areas is a major contributor not only to traffic congestion but also to other adverse consequences of traffic congestion. As urban areas expand in population and home real estate values in areas with high office development escalate rapidly, the distance between the home and the workplace will continue to increase. This increase in commute distance, in addition to the overall increase over time in many urban areas in the number of commuters, will lead to an increase in urban traffic congestion unless proactive traffic congestion alleviation measures are considered. In this context, there are several [Page 79]possible congestion reduction strategies, which may be grouped into one of three broad categories:

• 1.
  Increase supply or the vehicular carrying ability of roadways by expanding the road network or making the road network more efficient (building new highways, adding lanes to existing highways, new overpasses, improved incident detection and response systems, better signal timing and coordination, and other strategies fall within this category).
• 2.
  Influence vehicular traffic patterns by reducing the percentage of commuters driving alone or the percentage of commuters using specific highways (high-occupancy lanes, commuter rail and other transit improvements, pedestrian-friendly and transit-friendly urban form design, and auto-use or highway-use disincentives such as tolls, congestion pricing, and parking pricing fall within this category).
• 3.
  Change commuter travel patterns by reducing travel or spatially and temporally shifting commuters’ travel (teleworking strategies, work-staggering strategies, flexible work hours, and improved spatial balancing of jobs and housing to reduce commute distances fall in this group).

The accurate analysis of the potential effectiveness of the congestion mitigation strategies identified above (and their combinations) is critical to making informed policy decisions and capital infrastructure investments. In turn, this requires a systematic process for analyzing commuter travel behavior, which is characterized by several choices, such as home and work location, the travel mode, the time of day to travel, and travel route. Behavioral models for such choices are typically estimated by collecting survey and supporting transportation and land use-network data. The results from these models provide the public and planning organizations with the necessary commute travel insights to effectively address difficult policy and infrastructure investment questions.

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