Design Year

Cities must make investments that consider the life and longevity of any major infrastructure investment, accounting for anticipated future growth and development. Such projections should reflect a city’s adopted goals and project an intended outcome, coordinated with land use controls.

The design year assigned to a roadway represents an estimation of the future traffic demand and volume expected on that facility. Design year typically relies on travel demand models and other methods that often implicitly assume steady traffic growth. These projections tend to stand at odds with both local policy and recent travel trends. While travel demand modeling has evolved into a highly sophisticated and refined field, it still remains an educated estimate and should be qualified by intended outcomes and goal-driven city policies.

A 2% compound traffic growth rate doubles traffic in 35 years.

While trends indicate that traffic volumes have leveled off or even decreased over the past 10 years in jurisdictions throughout the United States, traditional forecasting substantially overestimates the potential for traffic growth.² Similarly, many modeling efforts underestimate the potential benefits (traffic reduction impacts) of improved land use decisions, natural growth in other modes (such as bicycling) and an overall cultural shift in urban mobility choices.

Traffic Growth Projections

Federally funded projects and environmental reviews typically require the projection of traffic volumes 10–30 years in the future, typically assuming a 1–2% annual growth in vehicle volume.³ These traffic projections are then analyzed in relation to existing performance measures (typically, level of service) to determine if future mitigations are necessary.

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In most places, traffic projections are based on the selection of a transportation model (typically at the regional level), which is calibrated to emulate existing and future transportation levels based on land use, transportation investments, and other factors. A recent study investigated the postconstruction accuracy of traffic forecasts and revealed that traffic on roads in urban settings (arterials and collectors) were typically overestimated by a significant amount.⁴ Despite common logic, overdesigning and over-engineering a street from a roadway capacity standpoint may actually be detrimental to public safety. Furthermore, overdesigning roadways to meet an inaccurate future demand presents a major opportunity cost for other land uses within a city’s public realm.

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City transportation policies often prioritize walking, bicycling, and transit. In some cases, cities aim to achieve explicit mode share targets to reduce dependence on single occupancy vehicle use.⁵ Meeting these aggressive goals and targets will require a shift in both infrastructure investment and traveler behavior.

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Individual projects should be assessed on a case-by-case basis to analyze how standard traffic growth factors (land-use trip generation, ambient growth) may conflict with or inhibit the desired diversification of street users and uses over time.⁶ Future analysis should begin with the vision for future function of the street or facility, and identify design treatments (and in some cases policy) that will achieve this vision. In some cases, a negative VMT growth factor may be required to meet intended goals.

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Reflecting changing land uses and behaviors, projections may be utilized to satisfy warrants and other criteria for the installation of particular traffic control devices, such as stop signs, traffic signals, or other measures.

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Induced Demand

The graphic below illustrates how a road designed to a 20-year horizon induces traffic. The road is (re-) built with 20-year capacity, but is completed in 5 years. Drivers react to the additional road space by driving more, and expanded roadways built in recent years typically degrade the pedestrian experience, reducing the propensity of people to walk to schools, stores, or other destinations. Drivers also switch from alternative routes and earlier or later times for their commutes to fill the new capacity. The end result is that the road reaches its capacity in 10 years instead of 20.¹¹

Cities can alter this paradigm by constructing streets that support other uses (walking, cycling, transit, sitting, retail), assuming that these choices will prompt more walking, cycling, and local retail activity.

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Alternate Methods

To supplement existing traffic models, several other strategies should be considered that may present more accurate estimates for future traffic demand.

Comparative Projection

While the ITE Trip Generation Manual is a frequently cited source, in urban settings the manual’s outputs may not be a strong comparative match. To better meet the needs of urban settings, numerous research studies have been developed through universities and state DOTs that provide more precise trip generation rates for urban settings.¹²

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Growth Projection

In many cities, traffic analysis requires the use of an “ambient growth factor,” which reflects the underlying baseline traffic growth. This growth factor is often provided by city staff and is based on a moving average from past growth (typically 1–2%). This growth factor is often considered to be an assumed positive factor but should be strongly reconsidered due to its potential inaccuracies given recent cultural trends. Growth factors should no longer be strictly based on multiyear moving averages since recent VMT trends have been shown to be volatile (or declining). While growth projection factors of 1–2% seem minimal, it can have a significant cumulative impact over each year it is applied.

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Mode Targets

Several U.S. cities (Chicago, Minneapolis, San Francisco, and others) and states have developed specific mode targets to achieve within a set time frame. For example, MassDOT has established a goal of tripling the number of trips by transit, bicycle, and walking. San Francisco has established a goal of 50% non-auto trips by 2018. These goals provide a set objective and spur the rapid implementation of programs that seek to accomplish them. These types of underlying programmatic shifts are often not explicitly integrated into traffic modeling efforts, but can serve as a baseline from which to better understand potential future modal shifts.

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Greenhouse gas reductions

Another underlying factor that may play a major role in changing future traffic demand is greenhouse gas (GHG) emissions. Several states across the United States are employing GHG targets that filter down into several more tangible objectives (such as mode share, VMT reduction, and others). Massachusetts has established a target of 25% reduction in GHG by 2020 and 50% by 2050.¹³

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Induced Demand Projection

If a project is determined to require an increase in roadway capacity, induced traffic demand should be considered a negative externality as a result. If the additional traffic demand created exceeds local policy thresholds (such as mode shift, as described above), it should be investigated if traffic can be mitigated through other non roadway infrastructure strategies.

1. Vehicle Miles Traveled (VMT) trends are captured by the Office of Highway Policy Information.
   
   “Traffic Volume Trends,” accessed June 3, 2013, http://www.fhwa.dot.gov/policyinformation/travel_monitoring/tvt.cfm.
   
   The USDOT reports that the percentage of the US population between ages 16 and 19 holding a driver license has been in decline since 1998. While some of this may be caused by increases in minimum age to drive, trends also hold true for those aged 18, 19, and into their 20s. ↩︎
2. State Smart Transportation Initiative, “Motor vehicle travel demand continues long-term downward trend in 2011,” accessed June 3, 2013, http://www.ssti.us/2012/02/motor-vehicle-travel-demand-continues-long-term-downward-trend-in-2011/ vmt-chart-2/. ↩︎
3. Additional information on the NEPA environmental review process for transportation can be found via the USDOT.
   
   Interim Guidance on the Application of Travel and Land Use Forecasting in NEPA (Washington, D.C.: USDOT, 2010).
   
   The California DOT Guide for the Preparation of Traffic Impact Studies denotes that analysis scenarios should reflect traffic volumes (trip assignment) and peak LOS for the year anticipated of project completion (as compared to a 15–25 year time horizon).
   
   Guide for the Preparation of Traffic Impact Studies (Sacramento: California Department of Transportation, 2002).
   
   The Utah DOT specifies that the design year is based on the level of traffic impact. Projects that generate less trips (<100 ADT) need only analyze the year of completion, whereas projects that generate more trips (greater than 10,000 ADT) require a design year at the opening day of the project, five years, and twenty years.
   
   Traffic Impact Study Requirements (Salt Lake City: Utah Department of Transportation, 2004). ↩︎
4. Pavithra Parthasarathi and David Levinson, “Post Construction Evaluation of Traffic Forecast Accuracy,” Transport Policy (2010): 1–16. ↩︎
5. Many cities are currently establishing goals to increase non-motorized mode share. Cities include Boston, Chicago, Minneapolis, San Francisco, Portland, and others. ↩︎
6. In Washington, D.C., annual growth or decrease in through traffic is to be included in traffic analysis based on historical data provided by DDOT. A DDOT Case Manager is given the final authority on projected annual growth (or decline) factors to be used in traffic analysis. DDOT Guidelines for Comprehensive Transportation Review (CTR) Requirements (Washington, D.C.: District Department of Transportation, 2012). ↩︎
7. National Transportation Statistics (Washington, D.C.: USDOT Bureau of Transportation Statistics, 2013), 71.
   
   Data derived from bicycling data for 70 largest United States
   cities.
   League of American Bicyclists, “Bicycle Commuting Data,” accessed June 3, 2013, http://www.bikeleague.org/news/acs2010.php. ↩︎
8. Traffic evaporation is the counterpart to induced traffic, in which increased capacity increases demand. Desire for roads, like all economic goods, increases and decreases as supply changes. See for example:
   
   Douglass B. Lee, Lisa A. Klein, and Gregorio Camus, “Induced traffic and induced demand,” Transportation Research Record. No 1659 (1999): Appendix B. ↩︎
9. S. Cairns, Carmen Hass-Klau, and Phil Goodwin, Traffic Impact of Highway Capacity Reductions: Assessment of the Evidence, (London: Landor Pub, 1998): 29. ↩︎
10. S. Cairns, S. Atkins, and P. Goodwin, “Disappearing traffic? The story so far,” Municipal Engineer 151 (2001): 13–22. ↩︎
11. A literature review of several studies focused on induced demand found that between 50–100% of new roadway capacity is often absorbed by traffic within three or more years. Furthermore, the Handbook of Transportation Engineering notes that urban highway capacity expansion often fails to significantly improve travel times or speeds due to latent demand.
    
    Todd Litman, “Generated Traffic and Induced Travel,” ITE Journal 71 (2001): 38–47. ↩︎
12. Caltrans has developed trip-generation rates for urban infill land uses in California.
    
    Trip Generation Rates for Urban Infill Land Uses in California (Sacramento: California Department of Transportation, 2008).
    
    Researchers at UC-Davis have developed a Smart Growth Trip Generation Adjustment Tool, which provides more accurate trip forecasts for urban areas. Final Report: California Smart-Growth Trip Generation Rates Study (Davis, CA: University of California, 2013). ↩︎
13. Transportation is second only to buildings as a source of greenhouse gas emissions, with the vast majority of transportation emissions coming from cars and trucks. Governor Patrick signed the Global Warming Solutions Act into law in 2008, and in 2010 established targets of 25 percent reduction in GHG emissions from 1990 levels by 2020 and an 80 percent reduction from 1990 levels by 2050—the most ambitious GHG emissions limits for any state in the nation.
    
    Massachusetts Department of Transportation, “MassDOT Goal: Triple Travel by Bicycle, Transit, Walking,” (October 2012) http://transportation.blog.state.ma.us/blog/2012/10/massdot-goal-triple-travel-by-bicycle-transit-walking.html. ↩︎