5 Components of Transportation Planning

With the recent trend of increased integration between transportation planning and traffic operations, it is important for new traffic analysts and engineers to understand the different levels of planning along with the most appropriate tools and methods of analysis. As planning encompasses areas ranging in size from a few intersections to entire sub regions of the United States, selecting the proper tools and analysis procedures will yield better answers and maximize government agency resources.

Statewide Planning: Given the large geographic size, travel demand models are typically used for statewide analysis. These models can be estimated and developed at the statewide level, or they can be developed by combining regional models within the state. However, this can be challenging if the regional models are not consistent with one another (i.e., different demographic assumptions, functional classification differences, etc.). Statewide planning can evaluate goods or people movement and is often used to identify project needs in rural areas of the state. Given the large geographic scale of the study area, the models are typically not as refined as those used for urban planning. 

Regional Planning: Regional planning is typically conducted by Metropolitan Planning Organizations (MPOs) using a travel demand model, which can be either trip-based, tour-based, or activity-based. The regional travel demand models include finer-grained geographies and more detailed roadway network coding than statewide models. This is consistent with the models covering denser urban areas with more complex origin-destination patterns and modes of travel. Regional planning includes air quality conformity analysis, development of the long-range plan, regional freight and transit studies, and regional Congestion Management Processes (CMP).

Comprehensive Planning: This involves city or countywide planning that looks at existing and future land use, market conditions, parks and recreation, civic buildings and spaces, transportation, and infrastructure. Given the comprehensive nature of these plans, travel demand models are the most appropriate analysis tool to evaluate the impacts of future land use decisions on the transportation network. The travel demand modeling analysis can be replaced with GIS-based sketch planning tools if there is no travel demand model for the area. Depending on the available budget and direction from the city or county, some spot intersection-level analysis can be conducted to evaluate locations of concern in more detail.

Subarea/Corridor/NEPA Planning: This is where planning and operations analysis are fully integrated. The level of analysis requires both travel demand modeling to develop intersection/interchange forecasts and traffic simulation modeling to evaluate how well a proposed design solution works in the future based on future demand. 

Traffic Impact Studies: These studies evaluate specific developments using methods to predict trip generation and distribution of development-related traffic on the transportation network. Impacts are evaluated using capacity analysis software or microsimulation modeling to assess study intersections for existing, future no-build, and future build conditions.

As a rule of thumb, if the question is related to how land use decisions would impact the transportation network, macroscopic tools, such as travel demand models for large study areas or highway capacity software for small study areas, should be used to identify the differences in volume/capacity based on the different land use scenarios.

Traffic simulation has increasingly been integrated into these types of studies; however, the level of effort (and cost) required to obtain and thoroughly review traffic count and speed data, model coding, and calibration are generally inconsistent with the budgets available for planning efforts. Moreover, as simulation models clearly illustrate congestion points, there is a strong tendency for traffic engineers to optimize signal timing and adjust intersection geometries to minimize queuing in the network.