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2 VMT Estimation and Forecasting Examples
2.1 Background - Importance of VMT Estimates
The basic process for calculating emissions involves multiplying VMT by a per-mile emission factor. Thus, accurate VMT forecasts are extremely important for developing emissions estimates in the conformity analysis. This section focuses on the methodologies and approaches used for estimating baseline VMT and forecasting future VMT.
Clearly, any methodology to forecast future VMT requires an accurate estimate of current VMT (and often historic VMT and socio-economic factors as well). Data from the Highway Performance Monitoring System (HPMS) are typically used in small urban and rural areas to estimate VMT for the current year.[4] However, the accuracy of HPMS-based estimates may be limited in small urban and rural areas and for local roadways in particular (as opposed to arterials and other higher functional classifications), given the sparse sample sizes at the county level. As a result, some areas have developed detailed inventories of local road mileage and supplemented the HPMS sample with additional traffic counts, and some have developed detailed traffic monitoring systems in order to develop more accurate estimates of VMT at the county level.
A basic process for estimating VMT using a sample of traffic count data for use in emissions analysis is as follows:[5]
- Calculate the sum of counts in each facility type
- Determine the sample size in each facility type (i.e., the number of count sites)
- Determine the average volume for a facility type by dividing total count by sample size
- Obtain total centerline miles of each facility type in the modeling domain
- Multiply average volume by the number of centerline miles for each facility type to estimate total VMT for each facility type.
VMT estimates are used together with per mile emissions factors developed using the EPA MOBILE6 model (or EMFAC in California), which in turn, are dependent on speed estimates. As a result, the level of detail in the estimation of VMT will influence the level of detail that can be used in the estimation of speeds, and will ultimately affect the regional emissions estimates.
VMT estimates are typically developed on a daily basis, for multi-hour time periods, or by hour:
1) Average daily VMT - The simplest approach is to develop estimates of average daily VMT by functional roadway classification. Areas with TDF models use modeled volumes by roadway segment. Areas that do not have a TDF model usually rely on HPMS estimates of VMT by functional roadway classification.
2) VMT for different periods of the day - This approach involves developing estimates of VMT for different periods of the day (e.g., AM peak, PM peak, off-peak). This approach is commonly used in areas where there is significant traffic congestion during peak hours. In areas with a TDF model, the model usually can be run to estimate VMT for the morning and evening peak periods, and for total average daily traffic, in which case, the peak periods can be subtracted from the daily total in order to estimate off-peak VMT. Otherwise, average daily traffic estimates can be disaggregated to time periods using locally-developed factors. In areas without a TDF model, average daily traffic is often distributed between peak periods and off-peak periods based on local factors developed from traffic counts.
3) VMT by hour of day - The most detailed breakdown of VMT can be developed by subdividing estimates of daily VMT or VMT by time period to generate hourly VMT. This hourly breakdown is often based on estimates of hourly volumes from a sample of roadways and average roadway speeds each hour. These sample results provide an estimate of VMT for each of 24 hours in the day. This step allows for a more detailed speed analysis in MOBILE6, which allows VMT to be distributed by hour of the day and by speed category or "bin."
In many small urban and rural areas, a simple analysis of average daily traffic will suffice for the regional emissions analysis. However, it is important to recognize cases where a more detailed breakdown is useful to reflect local conditions that could significantly influence emissions.
Moreover, although many areas use annual average daily VMT (based on estimates of annual average daily traffic, or AADT, on roadways), a seasonal adjustment is sometimes applied so the resulting VMT used in the conformity analysis reflects either an average summer or winter weekday, depending on the pollutant of concern (summer for ozone, winter for CO). This seasonal adjustment is most important in areas with large seasonal variations in traffic patterns, and is more often applied in areas that have regional TDF models.
2.2 MOBILE6 Requirements for VMT
MOBILE6 differs from previous versions of the MOBILE emissions model in that it produces different emission factors for different roadway facility types. The four facility types are:
- Freeways
- Arterials and collectors
- Local roads
- Freeway ramps
Using the VMT BY FACILITY command, the user can input the fraction of VMT that occurs on each facility type. The user can run the model assuming 100 percent for a specific facility type in order to develop facility-specific emission factors, or can input a fractional value for each facility in order to develop a composite emissions factor across all road types.
As noted above, MOBILE6 allows users to input VMT information at different levels of detail, depending on the availability of local data. MOBILE6 allows users to specify the distribution of VMT by hour of the day, by speed, and by vehicle type.[6] Using the VMT BY HOUR command in MOBILE6, the user can input the fraction of VMT that occurs at each hour of the day (24 fractional values). The 24 fractions should sum to 1. If this command or other MOBILE6 commands that allow specification of VMT by hour are not used, then MOBILE6 will use national default data for the distribution of VMT by hour.
2.3 Methodologies for Estimating Local Road VMT
- Method 1: Use statewide data, which is more statistically significant than county-level HPMS data in order to develop a ratio between local roadway VMT and collector VMT; apply this ratio to develop an estimate of local roadway VMT
- Method 2: Conduct a statistical analysis of the relationship between VMT on local roadways and VMT on collectors using available state or county-level estimates, in order to develop a formula to calculate county-level VMT on local roads
- Method 3: Develop a detailed inventory of all local roads, and conduct additional traffic counts or make assumptions about average daily traffic in order to develop an estimate of baseline local roadway VMT
These methodologies can be used both in areas with or without a TDF model, since TDF models generally do not include road links for local roadways.
For purposes of emissions modeling, note that the assignment of VMT as "local road" VMT may not match with the standard highway classifications of urban local roads and rural local roads. In MOBILE6, local roads are defined as facilities having extremely low average speeds and frequent stops at intersections. They generally represent roads in residential areas and are characterized by having no traffic lights, no more than one lane in each direction, vehicle parking on the street, and traffic control handled via stop/yield signs. MOBILE6 assumes an average speed of 12.9 miles per hour for local roads, which cannot be changed by the user. As a result, roadways that fit within FHWA's "rural local roadways" and "urban local roadways" functional classifications with higher average speeds should be considered arterials/ collectors in MOBILE6. Rural local roadways as defined by FHWA will generally not fit the MOBILE6 definition of local roadways, and many urban local roads will also not fit the definition. Given these differences in definitions, it is important for the analyst to develop an accurate estimate of total VMT in the nonattainment or maintenance area, and to pay special attention to classifying the VMT appropriately into the MOBILE6 road classifications.[7]
Estimating Local Road VMT
Method 1: Use Statewide Estimates to Calculate Proportion of Local Road VMT to Collector VMT
- Description
- State-level data on VMT on local roads and collectors is used in order to develop a ratio of local road VMT to collector VMT on urban and rural functional road classifications. This ratio is then applied to county-level estimates of VMT on collectors.
- Method Applicability
- This method is most appropriate when the region being examined is expected to have relatively similar patterns as the State as a whole. This method is broadly applicable to virtually all small urban and rural areas with limited data on local roadway VMT.
- Data Sources and Procedures
-
VMT Estimation and Forecasting
VMT estimates for local roadways in a particular county are developed by multiplying the HPMS estimates of VMT on collectors in the county by the ratio of local roadway VMT to collector VMT developed using HPMS data at the statewide level (see equation below).
The equation is applied separately for rural local roads, using the proportion of statewide VMT on rural local roads to rural collectors, and for urban local roads, using the proportion of statewide VMT on urban local roads to urban collectors. The estimates of VMT are believed to be more accurate at the statewide level than at the county level, given the limited HPMS sample size at the county level. The same procedure can also be applied using ratios developed at a smaller geographic level than the state (for example, a set of counties within a large state), if sufficient data are available.
This procedure may be used to develop a base year estimate of VMT on local roadways or to forecast VMT on local roadways given a forecast of VMT on collectors.
- Advantages
-
- Simplicity of the approach.
- Resource requirements are very small.
- Rationale and data sources are generally accepted.
- Limitations
-
- Methodology may not reflect differences in patterns between the county under consideration and the state (for example, if there is a much smaller local road network proportional to collectors).
- Example Location
-
This approach had been used in Kentucky for rural areas and small urban areas (however, this approach is not currently used). In its original approach, the Kentucky Transportation Cabinet (KYTC) examined the statewide ratio of VMT on local roads and collectors, and used the following ratios to predict local road travel in each county: 0.33 (rural local/rural collector), 0.28 (urban local/urban collector in urbanized counties), 0.12 (urban local/urban collector in non-urbanized counties).
Website: http://transportation.ky.gov/Multimodal/Air_Quality.asp
References:
M.L. Barrett, R.C. Graves, D.L. Allen, J.G. Pigman, G. Abu-Lebdeh, L. Aultman-Hall, S.T. Bowling, Analysis of Traffic Growth Rates, University of Kentucky Transportation Center, August 2001.
Bostrom, Rob and Jesse Mayes, "Highway Speed Estimation for MOBILE6 in Kentucky," Kentucky Transportation Cabinet, 2002.
Excel Spreadsheet tables, "2001-2030 VMT Tables," supplied by Jesse Mayes, Kentucky Transportation Cabinet.
Estimating Local Road VMT
Method 2: Develop Statistical Relationship between Local Road VMT and Collector VMT
This methodology is similar to Method #1, but uses several data points in order to develop a formula relating local road VMT to collector VMT. It relies on several samples of local and collector VMT (e.g., county-level estimates, for various years).
- Method Applicability
- This method is applicable to virtually all small urban and rural areas with limited data on local roadway VMT for the nonattainment or maintenance area. It requires, however, sufficient data on local and collector VMT from several samples of counties in order to conduct the statistical analysis.
- Data Sources and Procedures
-
VMT Estimation and Forecasting
An analysis is conducted using available state-level HPMS estimates or county-level samples in order to relate VMT for local roads with VMT for collectors. The analysis can be conducted by testing various equations to describe the relationship between local road and collector road volumes and selecting the best fitting equation. For example, a typical spreadsheet package can test the following:
Simple linear equation[8]:
Logarithmic equation:
Exponential equation:nbsp;
Power equation:nbsp;
In all cases, a and b are constants that are determined based on the relationship of existing local and collector VMT data.
The formula that is developed from this analysis can then be used to develop an estimate of county-level VMT on local roads given an estimate of county-level VMT on collectors. The formula can be used both for the baseline analysis and projections.
- Advantages
-
- Relative simplicity of the approach.
- Rationale and data sources are generally accepted.
- Limitations
-
- Requires several estimates of local and collector VMT at a county level, drawn from more detailed sampling and traffic counts on roadways.
- Methodology may not reflect conditions that are particular to the county under consideration that may make the relationship between different functional roadway class traffic volumes different from other parts of the state (for example, if there is a much smaller local road network proportional to collectors).
- Methodology may not substantially improve upon estimates using a simple ratio of local road VMT to collector VMT.
- Example Location
-
The approach has been used by the Kentucky Transportation Cabinet (KYTC) for small urban and rural areas in order to improve estimates of local road VMT previously developed using Method #1. KYTC used GPS technology to develop accurate mileage data fro local roadways statewide. Reasonably good ADT data at the county level were available from HPMS down to the collector functional class.
Research conducted by the University of Kentucky Transportation Center (see first reference below) found that a simple ratio of local road to collector VMT was inadequate to predict local road VMT. Researchers graphed local ADT against collector ADT to develop the best fitting relationship between these two measures. For Kentucky, they arrived at the following equation:
Local ADT = 3.3439 x (Collector ADT)0.6248
KYTC selected to use this equation rather than a simple ratio since they found that local roads carry much less traffic relative to collectors in locations where collectors have higher VMT. Therefore, if a simple ratio had been used as in method #1, then local road VMT would have been overestimated where collector VMT was relatively high.
Website: http://transportation.ky.gov/Multimodal/Air_Quality.asp
References:
M.L. Barrett, R.C. Graves, D.L. Allen, J.G. Pigman, G. Abu-Lebdeh, L. Aultman-Hall, S.T. Bowling, Analysis of Traffic Growth Rates, University of Kentucky Transportation Center, August 2001.
Bostrom, Rob and Jesse Mayes, "Highway Speed Estimation for MOBILE6 in Kentucky," Kentucky Transportation Cabinet, 2002.
Excel Spreadsheet tables, "2001-2030 VMT Tables," supplied by Jesse Mayes, Kentucky Transportation Cabinet.
Estimating Local Road VMT
Method 3: Estimate Average Daily Traffic on Inventory of Local Roadways
Not Applicable (only rated for forecasting methodologies)
* Note: This method is used solely to develop an estimate of baseline VMT for local roadways, with or without a TDF model. Projections can be made using any of the methods described in Sections 2.4 or 2.5, depending on whether a TDF model is available; a very simple approach is to estimate and apply a growth factor.
- Description
- This approach involves developing an inventory of all local roadways in the county of interest. Data on average daily traffic (ADT) on individual road links, based on traffic counts, are then applied to the roadway mileage. For links where there are no data, the ADT from other roadways or a default ADT assumption can be applied.
- Method Applicability
- This method is broadly applicable to virtually all small urban and rural areas. It is most appropriate when the region being examined is expected to have different patterns from the state as a whole and if local roadways make up a disproportionately large share of total traffic.
- Data Sources and Procedures
-
VMT Estimation
A detailed inventory of total road mileage on local roadways is required. Traffic counts are conducted in order to develop estimates of average daily traffic (ADT) on a sample of local roadways in the area of interest. The ADT estimates are then applied to the appropriate road links or assumed to apply to other nearby links. Alternatively, an overall average ADT can be applied across all road mileage. VMT is estimated by multiplying ADT by the link length.
- Advantages
-
- Accounts for actual road mileage of local roadways in the area of interest.
- Use of traffic counts provides better indication of actual traffic levels in the county of interest as opposed to using statewide data.
- Level of data collection can vary, and should depend on whether there is great variation in traffic volumes on local roadways.
- Limitations
-
- Methodology requires additional data collection compared to those that rely on statewide data.
- Assumptions of ADT may not be accurate for all roadways.
- Additional resources and complexity are introduced in the analysis if local road links are examined at a detailed level.
- Example Location
-
North Carolina DOT (NCDOT) applied this methodology in conducting analyses of regional emissions in donut areas outside of MPO boundaries. NCDOT records AADT for all roads in all functional classifications. Since less than 74 percent of local road mileage was covered by actual counts, for local road links without traffic counts, NCDOT assumed 400 ADT. This is the maximum amount of traffic expected on low-volume local roads.[9]
The Rogue Valley MPO in Medford-Ashland (Klamath County), Oregon, used an assumption of 20 ADT on unpaved roads in the base year as part of its conformity analysis for the 2004-2007 Transportation Improvement Program (TIP). The ADT average was developed by the Oregon Department of Transportation's Transportation Planning and Analysis Unit. The MPO assumed a growth rate of 1.2 percent per year for future projections.
References:
North Carolina DOT, Davidson County, and the North Carolina Department of Environment, "Emissions Analysis Report for the Transportation Plan for the Rural Portion of Davidson County." September 27, 2002.
Rogue Valley MPO, "2004-2007 Transportation Improvement Program and
Air Quality Conformity Determination," August 26, 2003.
