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Case Study: Montgomery County, Maryland


This case study illustrates the use of accessibility measures in regional planning. The measures can be readily computed using land use and network data typically available from a regional travel demand model. The results showed clear differences in accessibility among alternatives.

Montgomery County, Maryland, northwest of Washington, D.C. (Figure 1), is the largest county in the state. To address significant transportation problems, the county has recently undertaken a number of major investment and project studies. Yet, these studies have generally been conducted in isolation - each assuming that the other projects will not occur.

Not satisfied with this piecemeal approach, the Montgomery County Planning Board recently asked planning staff to evaluate a 20-year future with different transportation projects in conjunction, and to recommend a set of near-term improvements. The board also asked staff to look at longer-term future networks, including conceptual projects such as circumferential transit. Montgomery County planning staff chose to use accessibility as one of a few key indicators of the performance of each alternative transportation scenario. The county's accessibility measures indicate how many jobs the average household can reach within a given travel time, as well as how many households can be reached in a given travel time from employment centers.

Figure 1. Montgomery County, Maryland

Fig. 1 Montgomery County, Maryland

Source: Maryland-National Capital Park & Planning Commission (1999).


Montgomery County, Maryland covers a 497-square mile area of suburbs to the north and northwest of Washington, D.C. Major highways in the county include I-495 - the District's beltway - and I-270, which provides radial service to the northwest (Figure 2). The county is also served by two branches of the Metrorail Red Line, which provide high-speed transit access to the District of Columbia. Development patterns include a handful of older town centers, more recent suburban residential and commercial development, and undeveloped agricultural land in outlying parts of the county. Commercial activities are concentrated especially along the freeway and Metrorail corridors, while residential patterns are more dispersed.

Figure 2. Existing Transportation Network, Montgomery County

Fig. 2 Existing Transportation Network, Montgomery County

Source: Maryland-National Capital Park & Planning Commission (1999).

As a result of rapid growth in travel and development, the county is facing numerous transportation challenges. These include freeways that are heavily congested during peak periods; local roads that are increasingly unable to cope with traffic demands, especially for cross-county (east-west) movements; and limitations in transit service to a number of major activity centers.

Like most other counties in Maryland, Montgomery County has zoning jurisdiction over most of the land within its borders (with the exception of three smaller, incorporated cities). This informs its philosophy to both land use and transportation planning. The county's general plan is based on a long-standing "wedges and corridors" concept. This concept specifies that development should follow transportation corridors, while the areas between these corridors, or "wedges," are preserved. The county has successfully encouraged growth of jobs near transit centers and highways, although residential development has been considerably more dispersed. Land use forecasts used in travel modeling (Figure 3) are consistent with the county's general plan. Then, given this assumed pattern of future growth, the county's goal is to develop a future transportation network that moves people as efficiently as possible.

Figure 3. Housing and Jobs in Year 2020, Montgomery County

Fig. 3 Housing and Jobs in Year 2020, Montgomery County

Source: Maryland-National Capital Park & Planning Commission (1999).

While transportation planning for the broader metropolitan area is carried out by the Metropolitan Washington Council of Governments (MWCOG), the county has well-developed travel modeling capabilities, which it uses to evaluate local projects and transportation alternatives. During 1998 and 1999, the county analyzed five alternative year 2020 transportation networks. The resulting findings and recommendations were presented in a Transportation Policy Report, which was reviewed by the Planning Board and approved by the County Council. The report recommends projects to be included in the Maryland FY 2000-2005 Consolidated Transportation Program, as well as MWCOG's Constrained Long-Range Plan. The report also establishes a longer-term work program for additional analyses.

The County Council directed M-NCPPC staff through the Planning Board to undertake the longer-term work program, and Phase 2 of the Transportation Policy Report is now underway. The Phase 2 study greatly increases the depth and breadth of analysis and looks more definitively at the role of alternative land use scenarios and transportation demand management (TDM) strategies as well as different networks. The public participation element is also greatly enhanced in Phase 2; a 36-member task force representing the diverse interests of the county will provide guidance to staff and the Planning Board throughout the 15-month study. Finally, a team of nationally-renown consultants has been retained for technical assistance throughout the study. This team also includes a facilitator to work within the task force and interface between staff, the task force, and the Planning Board.


Accessibility Measures

Montgomery County selected three types of accessibility measures to compare alternatives:

  1. Destination accessibility, or the number of destinations that can be reached within a fixed travel time. This measure is based on the number of job opportunities that can be reached within 45 minutes by Montgomery County households, and the number of homes that can be reached within 45 minutes from major activity centers of Montgomery County employment. The method for computing these measures is described below. The measures are calculated separately using auto and transit travel times.
  2. Fixed-guideway transit accessibility, measured by the percentage of businesses and residences that are located within one-half mile of fixed-guideway transit stations. The Washington region's extensive rail transit network can provide significant time and cost savings for many trips. This measure also indicates the extent to which options are available to households that either cannot afford or choose not to own a vehicle.
  3. Travel times, measured by average travel times for auto and transit work trips in the evening peak hour. The county's objective is to reduce travel times, especially for transit trips.

In addition to these accessibility measures, the county also computed other measures relating to mobility and environmental impacts. These included VMT, VHT, average travel speeds, and mode shares.


All of the measures were computed based on inputs and outputs of the county's travel model. Montgomery County's model is a P.M. peak-hour model; subsequently the measure calculations use P.M. peak-hour trip tables, where the work end of the trip constitutes the origin i, and the home end the destination j. Data required for the destination accessibility measures include households and employment by zone as well as zone-to-zone travel times by mode. The methods for computing the destination accessibility measures are outlined below in Box 1 (households accessible from employment centers) and Box 2 (jobs accessible from households). The accessibility measures are calculated either county-wide, or for multiple-TAZ activity centers.

Box 1
Calculation of "Households Accessible from Employment Centers" Index

Accessibility from employment center i is computed as:

HAi = where Tij < 45 minutes


i is the TAZs comprising activity center k;

HAi is the housing accessibility of zone i;

HHi is the sum of households in all zones that are within 45 minutes of zone i;

Jobsi is the number of jobs in zone i.

Box 2
Calculation of "Jobs Accessible from Households" Index

JAj = where Tij <45 minutes


j is the TAZs comprising activity center k;,

JAj, the job accessibility of zone j, is the sum of jobs in all zones that are within 45 minutes of zone j;

JAk is the job accessibility of employment center k;

HHj is the number of households in zone j.

The average number of accessible households can be computed and compared for each alternative 2020 network.

The accessibility indices can be computed separately for auto and transit modes, based on the 2020 auto and transit networks. The indices can also be calculated only for "transit" activity centers, to provide a measure of transit accessibility.

In addition, this calculation can be performed to determine "households accessible from jobs" by reversing "jobs" and "households" in the above procedure. It is likely that these measures will closely track each other.

As an example (Table 1), the county estimated the difference in the activity center to households accessibility index between the base 2020 network and recommended plan (for the transit network) to be 66,870. The county interprets this result to mean:

"If you work in an activity center in Montgomery County, and the Recommended Plan is implemented, it will increase the number of houses you can reach from your job site in 45 minutes by transit by nearly 67,000."

Table 1.
Activity Center to Household Accessibility Index (by Transit) for 2020 Recommended Network

Accessible Households


2020 Rec.
Change x Jobs
Bethesda 44,804 299,065 350,945 51,880 17% 2,324,431,520
Clarksburg 3,222 10,443 46,435 35,992 345% 115,966,224
Germantown 20,228 25,418 50,358 34,940 98% 504,486,320
Total 232,248         15,529,823,618
Activity Center Weighted Average Increase =
Total (Absolute Change x Jobs) / Total Jobs

Source: Maryland-National Capital Park & Planning Commission (1999).

Level of Effort

County planning staff used the Department's regional travel demand model, TRAVEL/2, in support of the computation of accessibility measures. TRAVEL/2 is run using INRO's EMME/2 travel demand modeling software package. The TRAVEL/2 model is considered in the upper tier of four-step models in the United States and incorporates feedback loops that modify destination, route, and mode choice based on travel time.

A number of steps were required for the accessibility analysis. In general, these steps included: 1) identification and review of accessibility measures by lay-citizen and technical peer review committees; 2) preparation of model inputs and implementation of model runs and: 3) post-processing selected model results to produce accessibility measures. Geographic information systems (GIS) were used to create buffers around fixed-guideway transit stations in the county for the calculation of the transit accessibility measures. In addition, spreadsheet and database management software packages were used for the post-processing of model results.


Comparison of Alternatives

Figure 4 illustrates the transit county-wide accessibility index to households and jobs under each alternative network is illustrated below. Table 2 shows how the county's accessibility measures compare among the various alternatives. Table 2 compares the transit and auto accessibility measures, and also shows average work-trip travel times under each alternative. Table 2 compares the transit and auto accessibility measures, and also shows average work-trip travel times under each alternative.

Figure 4. Transit County-Wide Accessibility Index

Fig. 4 Transit County-Wide Accessibility Index

Source: Maryland-National Capital & Planning Commission.

Table 2. Measures of Effectiveness

Comb. A
Comb. B
Comb. C
Comb. D
Rec. Plan
Transit Accessibility
County-wide to Households (000s) 98 104 116 129 138 146 137
County-wide to Jobs (000s) 182 194 217 240 267 281 254
Activity Center to Households (000s) 155 162 183 204 250 261 229
Average Travel Time (min.) 55.9 60.4 53.8 48.2 47.6 45.9 46.8
Auto Accessibility
County-wide to Households (000s) 546 647 667 722 653 726 748
County-wide to Jobs (000s) 423 1,134 1,174 1,189 1,107 1,235 1,286
Activity Center to Households (000s) 195 658 672 741 669 740 771
Average Travel Time (min.) 26.0 35.2 33.8 32.6 33.9 32.6 31.1

Source: Maryland-National Capital Park & Planning Commission (1999).

Planning staff also took the measures a step further and compared accessibility to the cost of each alternative to develop a "cost efficiency index." To do this, the change in accessibility was first divided by the cost of the alternative. To develop the efficiency index, the change per unit cost for the best alternative was set at 100, and the change per cost for each other alternative was rated relative to 100 (Table 3).

Table 3: Cost Efficiency Index

Change from Base
Divided by Capital Cost
Efficiency Index
  2020 Comb. A 2020 Comb. B 2020 Comb. C 2020 Comb. D 2020 Rec. Plan 2020 Comb A 2020 Comb. B 2020 Comb. C 2020 Comb. D. 2020 Rec. Plan
Transit Accessibility  
County-wide to Households (000s) 9.06 9.59 10.22 9.70 11.26 80 85 91 86 100
County-wide to Job (000s) 17.36 17.64 21.95 17.09 20.47 79 80 100 78 93
Auto Accessibility  
County-wide to Households (000s) 15.09 28.77 1.80 18.24 34.46 44 83 5 53 100
County-wide to Jobs (000s) 30.19 21.10 (8.12) 23.32 34.46 88 61 (24) 68 100

Source: Maryland-National Capital Park & Planning Commission (1999).

Some of the conclusions the county drew from the evaluation include:

Overall, the county found the combination of mobility and accessibility measures to be helpful in comparing alternatives and developing a recommended plan (Figure 5).

Figure 5. Recommended 2020 Network, Montgomery County

Fig. 5 Recommended 2020 Network, Montgomery County

Source: Maryland-National Capital Park & Planning Commission (1999).

Extension to 2050 Analysis

In addition to evaluating packages of near-term transportation improvements, the county used the accessibility measures to evaluate long-term transportation and land use scenarios. The county evaluated three land use scenarios for the year 2050:

  1. The Master Plan Scenario included the land use pattern anticipated by the build-out of the approved area master plans by the year 2050.
  2. The Transit-Focused Scenario focused development in areas within walking distance of the master planned transit stations, with resulting densities up to 25 percent beyond those in currently approved master plans.
  3. The Locally Balanced Scenario focused development within walking distance of transit stations and, in addition, balanced the number of jobs and employed residents in the two major radial development areas (along I-270 and U.S. 29).

Each scenario was then tested with the full transportation network in the county's area master plans (Master Plan Network), as well as with Enhanced Networks that include transitways.

The analysis concluded that land use patterns make a significant difference in the demands on transportation networks. In particular, the Locally Balanced Scenario achieves significantly greater transportation benefits (on all measures of effectiveness) than the Master Plan Scenario when evaluated with the same network. For example, the Locally Balanced Scenario results in 12 to 22 percent higher accessibility scores than the Master Plan Network, compared to the Master Plan Scenario. The scenario provided similar benefits on the Enhanced Transportation Network (Table 4).

Table 4. 2050 Transportation and Land Use Scenarios

  2050 Locally Balanced Land Use 2050 Master Plan Land Use
Master Plan
Master Plan
Transit Accessibility  
County-wide to Households (000s) 98 104 168 193 139 164
County-wide to Jobs (000s) 182 194 321 384 265 329
Auto Accessibility  
County-wide to Households (000s) 546 647 740 745 607 626
County-wide to Jobs (000s) 423 1,134 1,207 1,354 1,073 1,196

Source: Maryland-National Capital Park & Planning Commission (1999).



Montgomery County's use of accessibility measures provided a number of benefits for comparing transportation alternatives. The measures indicated clear differences among the alternatives and also provided insights into the relative benefits to automobile and transit users. Furthermore, the measures proved useful in comparing longer-term combinations of land use patterns and transportation networks. The measures are clear, easy to understand, and can be computed based on available land use and travel demand model data.

The accessibility measures also point out an interesting finding that conventional measures of transportation system performance hide: accessibility may increase in the future, even though traffic congestion and travel times may also increase. Furthermore, the measures indicate that the gains in accessibility can be realized exclusively by changes in land use patterns, given the same transportation network. Projected growth in employment means that residents will have access to a greater absolute number of jobs than they currently do. Based on this particular accessibility measure at least, the growth in employment outweighs the increased travel "impedance" caused by increased traffic congestion.

Another question important to the use of accessibility measures is how to value these measures when making comparisons among alternatives. Montgomery County approached this by developing a "cost-effectiveness" index to identify the alternatives with the greatest accessibility benefits per unit cost. This approach is similar to calculating a cost-effectiveness index for emission reductions or other benefits that cannot easily be valued in monetary terms.


Accessibility measures such as those used by Montgomery County do require some general cautions. These include:

One specific caution from this case study is that Montgomery County did not include land use feedback in their 2020 analysis, although different land use scenarios were tested in the 2050 scenarios. The county's assumption was that development will generally be fixed in accordance with their comprehensive plan. The county intends to account for feedback between transportation supply and land development in the future, recognizing that developers still have some flexibility within the master plan framework.


Published References

Maryland-National Capital Park and Planning Commission/Montgomery County Park and Planning Department. Transportation Policy Report. Staff Draft (August 1999).


Organization Person Phone
Maryland-National Capital Park and Planning Commission/
Montgomery County Park and Planning Department
Rick Hawthorne, Chief of Transportation Planning, (301) 495-4525
Updated: 6/7/2012
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