Although an MPO in a region with small population may not have as many demands as an MPO in a big city, there is a minimum level of resources required for the MPO to be effective. In other words, an MPO in an area with 100,000 people is more than 1/20th of an MPO in an area with 2 million people. Furthermore, an MPO may have travel issues (for example, a high number of through trips) that are not reflected in its region's population. Steve Williams noted that "at any MPO there are three trains of thought: policy, process, and quantitative. At a small MPO, the quantitative may drop off."
Participants suggested that the minimum staff size of an MPO might be three people, with annual funding of perhaps $150 - 200K. The skills required for an effective MPO are varied, and rarely reside in a single person. They include:
Often, to reduce administrative costs, the MPO may be housed within another entity, such as a city or county planning department or a regional planning council. The MPO may draw on expertise from other agencies. For example, the city where the MPO is housed may have qualified GIS staff and a traffic counting program. Or, a nearby university may provide data and modeling expertise. The State DOT often provides assistance with modeling and data to small MPOs. The MPO may also seek government or private grants, for example, from a computer vendor. Certain data may also be inexpensively available from peer agencies with similar population and travel characteristics.
Overall, there is a significant reliance on in-kind (for example, office space from a city) and shared resources.
For further information on MPO governance and staffing, please see the May 2010 report1, Staffing and Administrative Capacity of Metropolitan Planning Organizations, produced by the University of South Florida Center for Urban Transportation Research.
Many State DOTs are very active in modeling efforts, maintaining statewide or local models, assisting and coordinating with MPOs, or even mandating certain modeling practices. This involvement can help keep local models compatible and facilitate data sharing among MPOs. DOTs may also have resources and expertise that would be difficult for smaller localities to afford.
State DOTs and other State-level organizations typically collect and archive a wealth of data that can be used in modeling efforts. Employment, census, vehicle registration, and licensing data are typically maintained by States. Accessing certain sensitive information, such as driver records, can be somewhat challenging for MPOs or any other organizations outside of State government. One participant overcame this difficulty by hiring the State Department of Employment to perform analyses that required access to sensitive data.
Universities can be an excellent source of modeling expertise and other assistance to MPOs . "Being in a college town, it is easy to find people with technical abilities" (Rita Morocoima-Black, Urbana, IL). Since universities often perform transportation-related research in their own localities, they may offer highly relevant data, knowledge, or even existing model components. Some MPOs near major universities have also been able to make great use of the abundant skilled, short-term labor in the student population.
University faculty may also provide helpful input on modeling techniques, especially when new or experimental methods are being considered.
The use of consultants has both advantages and disadvantages. If sufficient in-house expertise exists, consultants may not be necessary at all. However, in cases where the MPO does not need to engage in modeling all of the time, it may be difficult to maintain the in-house expertise. Here, a consultant may be beneficial. Consultants may also have good insights, from their work in other areas, on what tools might be most beneficial in a particular situation. They may also offer technical assistance to MPO staff.
One participant (Dan Thomas, NC DOT) remarked that "we had really good experiences...Contract and expectation setting are important...we need to be able to use the model afterwards." Steve Williams added that the "model is a long term investment, calibration not just for the corridor in question." Gary Kramer noted that "validation of the model by the consultant can be helpful." Srikanth Yamala noted that a "consultant is as good as the team hiring them."
Disadvantages of using consultants include the high cost, and the sometimes differing objectives. For example, in a corridor study, the consultant might deliver a model that works well for the corridor (thus, fulfilling the contract), while the MPO might be more interested in the model as a long-term investment, well calibrated everywhere in the region. Another challenge is turnover within the consulting firm, where the new consultant personnel need to be re-educated on the MPO's particular situation.
Several participants stated that it is important to set clear expectations on both sides, with a thorough request for proposal (RFP). To be successful, the MPO needs to work closely with the chosen consultant. Typically, the MPO will want to be able to use the model afterwards, and have the in-house capacity to replicate the consultant-supplied model. This suggests that the contract should include documentation as an intermediate deliverable, as well as on-call support from the consultant. The MPO should documentwhat they learn from the consultant so that they may be included in future contracts. It also may be helpful to build up a database of "model" RFPs.
In some cases, alternatives to consultants may exist. In a college town, it may be easy to find people with technical expertise. The software vendors or the State DOTs may provide training opportunities.
A number of resources are also available at the Federal level. They include the Travel Model Improvement Program (http://www.fhwa.dot.gov/planning/tmip/2). In additional to a clearinghouse of documents, TMIP has a peer review program. A number of national data resources (often identified by their acronyms) were mentioned earlier, including the National Household Travel Survey (NHTS), the American Community Survey (ACS) and its associated Public Use Microdata Sample (PUMS), the Census Transportation Planning Products (CTPP), Census Longitudinal Employment Household Dynamics (LEHD) data, the Quarterly Census of Employment and Wages (QCEW) from the Bureau of Labor Statistics, and the Freight Analysis Framework (FAF) from FHWA.
Bay County (Florida) Transportation Planning Organization
North Carolina DOT
The Guidelines are theory, and the Procedures are the "how to." They are specific to TransCAD. NCDOT also offered a training class over a period of several months. Students went over certain elements of modeling in class and then there was an out of class assignment. These tools are also being used in a class at NC State University for model development. While it is not being used in its entirety (due to time constraints in the classroom) it does provide the basis for modeling element of the class. These documents are available upon request to the Transportation Planning Branch at NCDOT.
There are three major areas where the peer exchange participants concluded that it would be helpful to document additional best practices and have more guidance for MPOs. They include:
2 Accessed 6/22/2012
3 Accessed 6/22/2012