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3-50 Guidebook for Freight Policy, Planning, and Programming in Small- and Medium-Sized Metropolitan Areas specifically address freight issues. The following summarizes the key challenges and offers poten- tial solutions: Common Issue Potential Solution Lack of available data and tools. The use of tools Investigate sources of freight data and tools. There and models requires significant data resources. are a number of publicly available freight data sources These data are not always available and can be and tools that can be useful. State DOTs, FHWA, and costly and difficult to collect. Many MPOs do not other agencies are potential sources of freight data have a suite of tools to assess freight transportation and in many cases are sources of tools and analytical projects. Air quality and travel demand models support. Many states are supporting freight planning may be common, but they do not always account at their MPOs by developing freight models for them. specifically for freight. Other models that provide State DOTs can also be important sources for other specialized calculations, such as economic impacts, tools and techniques, such as benefit-cost analysis are less common. and others. See the Data and Analytical Tools section of this module for more guidance. Development of new processes. The effective use Designate a Freight POC. A freight technical lead of existing and new models specifically designed should be designated within the MPO. This POC can or enhanced to accommodate freight project act as the liaison between the MPO's various trans- characteristics will likely require the creation and portation initiatives and between the MPO and other adoption of new processes. These will need to be agencies and stakeholders to ensure that freight issues effectively integrated into existing processes. In are addressed within multiple MPO activities. addition, to assess effectively the impacts of freight projects, a variety of activities will be required. One of the most difficult activities will be the integration of the various results to develop final conclusions and recommendations. Lack of staff expertise. Most MPOs currently do Investigate training and education opportunities. not have staff with extensive experience assessing There are a number of training and education oppor- freight project impacts. This will require the tunities available to MPO staff to enhance under- development of new skills. standing of freight, its common issues and concerns, and how it can be more effectively integrated within a transportation planning process. See Module 5 for a listing of training and education resources. Data and Analytical Tools Overview There is a wide variety of data that small- and medium-sized MPOs would like to have to sup- port freight policy, planning, and programming activities. In fact, data availability and quality will likely be the most significant consideration driving an overall transportation program. Spe- cific freight data and analytical tools have been called out within each of the subject areas to reflect the fact that they directly impact all aspects of a freight transportation program. The key types of freight data include the following: · Commodity flow data describe the types of commodities that move in a region, the origins and destinations of the flows, and the modes used; · Traffic data describe volumes of vehicle movements on critical facilities by mode; · Trip origin-destination data describe where freight shipments are moving; · Travel time data describe how long it takes to move from point A to point B; · Freight rates and costs describe total transportation costs; · Trip generation characteristics of different types of land uses (for impact analysis) describe the types of industries that generate the largest number of trips;
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Integrating Freight into MPO Activities 3-51 · Emissions from freight activity describe air quality and noise impacts of freight traffic; and · Accident and safety data related to freight activity describe accident rates and safety implications of freight movements. In a number of instances, these types of data are available from public sources. However, these publicly available data are not often available with sufficient detail to be useful to small- and medium-sized MPOs. Thus, these MPOs may be faced with the need for tools that can be used to estimate local data from state and federal sources or they will have to collect data themselves. There are a variety of analytical tools in use today throughout North America. These tools allow MPOs to forecast traffic movements, measure air quality impacts, evaluate economic impacts, and analyze and display data and networks geographically. More advanced tools work in concert with other tools to conduct specific calculations relating to modal diversion, mode choice, travel behavioral patterns, performance measures, and so forth. Examples of analysis tools include the following: · Economic impact models, · Travel demand models, · Air quality impact models, · Performance-based models (e.g., Surface Transportation Efficiency Analysis Model [STEAM], IDAS), · Discrete choice models and modal diversion models, and · GIS. Basic versus Advanced Approach The development of a comprehensive data collection program and supporting analytical tools demands a significant effort and commitment by MPO staff. The basic approach focuses on initial data collection activities. This approach consists of the steps required to describe and quantify freight movements in a region and directly supports the development of a regional freight profile and many subsequent activities. The basic approach works with established and available data sources from local, regional, state, and federal sources. A limited number of surveys and interviews are included to provide more detailed descriptions of key freight characteristics and movements. The advanced approach builds on the basic approach. It focuses on the development and application of a range of tools and models to analyze the available data. Development of a truck assignment feature within a regional travel demand model is an example of an advanced approach, because it integrates basic data already collected by many MPOs, such as traffic counts and vehicle classification data, and incorporates behavioral characteristics captured from surveys and interviews. Key Activities All MPOs have data collection programs that support their transportation programs. These data collection programs rely on local, state, and federal initiatives. For example, state DOTs provide traffic volumes and vehicle classification counts for the state highway system. The U.S. DOT pro- vides extensive data resources through the BTS. Local agencies augment these resources with local data that provide congestion, LOS, and traffic volumes on local highways. In addition, data typi- cally are available from major ports, airports, and railroads. The data collection activities described in this section focus on the effective integration of available data sources, the inclusion of freight- specific data, and the collection of more detailed freight data through use of surveys and interviews. The data collection program provides descriptive information that can be used to develop a regional profile, identify needs and deficiencies, and ultimately support the development of improvement projects. These data collection activities also feed into available tools and models.
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3-52 Guidebook for Freight Policy, Planning, and Programming in Small- and Medium-Sized Metropolitan Areas This section identifies the types of tools and models used by MPOs and describes the opportuni- ties that exist to use them for freight planning and programming activities. For example, small- and medium-sized MPOs can develop freight and truck models to analyze existing and future system performance. Multimodal freight models are rare but there is some guidance in NHI-sponsored courses and other resources on how these types of models are applied in MPO settings. More often, small- and medium-sized MPOs develop simple truck model add-ons to their existing travel demand models. A simple technique for doing this with default data is described in FHWA's Quick Response Freight Manual. NCHRP Synthesis 298 also describes this technique in general terms and provides alternative sources for truck trip generation data that can be used in these models. Basic Approach Activity · Data and Analytical Tools--Basic Activity Type · Policy, Planning, and Programming Level of Effort · Moderate Technical Complexity · Low to Moderate Data/Analytical Tool Needs · N/A Outreach/Partnership Needs · Moderate. Requires outreach to private partners through interviews, focus groups, surveys, and formation of a freight technical advisory committee to support a wide range of activities that rely on data and input. Training/Education Needs · Moderate. Requires that staff understand and be able to work with avail- able freight data sources; should explore resources and training available from FHWA and NHI. · http://ops.fhwa.dot.gov/freight/FPD/index.asp Related Activities · Supports all activities. Key Activity: Compile readily available data from public sources and conduct simple surveys. Step 1. Identify and collect readily available freight data. The types of data that are likely to be available to small- and medium-sized MPOs will include the following general sources: · Vehicle classification counts on state roads (from state DOT), · Truck-involved accident data on roads (often available from state DOT), · Data on rail tonnages and commodities from Surface Transportation Board (STB) Carload Waybill Sample, · Data on waterborne commerce tonnages and commodity from Army Corps of Engineers Waterborne Commerce Series, · County-level commodity flow data (from TRANSEARCH). (The cost of this data may be pro- hibitive for some small MPOs but a number of states have purchased these data for their MPOs), · Truck trip generation data for different land uses (available in NCHRP Synthesis 298), and · General economic data (employment by industry at the county level in County Business Patterns). Step 2. Collect basic stakeholder data through interviews and surveys. In addition to the available data sources, it is useful to conduct modest surveys of freight stakeholders to get infor- mation about the location of major freight facilities, the volumes of traffic they handle, and the general origin-destination characteristics of the traffic. Step 3. Feed data into other freight policy, planning, and programming activities. Freight data represent the basic ingredients for the majority of guidelines provided in this Guidebook. They impact the definition of goals and objectives, the development of a regional profile, the identification of needs and projects, and all the activities used to program and fund improve- ment projects.
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Integrating Freight into MPO Activities 3-53 Advanced Approach Activity · Data and Analytical Tools--Advanced Activity Type · Policy, Planning, and Programming Level of Effort · High Technical Complexity · High Data/Analytical Tool Needs · N/A Outreach/Partnership Needs · High. Requires outreach to private partners through interviews, focus groups, surveys, and formation of a freight technical advisory committee to support a wide range of activities that rely on data and input. Training/Education Needs · High. Requires that staff understand and be able to work with available freight data sources and tools such as travel demand models; should explore resources and training available from FHWA and NHI. · http://ops.fhwa.dot.gov/freight/FPD/index.asp Related Activities · Supports all activities. Key Activity: Develop local data collection program and develop analytical tools as appropriate. Step 1. Identify and collect readily available freight data. Before a data collection program can be developed, it is important to identify what is already available (see Step 1 under Basic Approach). Step 2. Identify data needs and data collection activities. After reviewing what is available, MPO staff should develop a data collection plan that will be used to fill in the missing areas of data based on what the MPO is trying to accomplish. This should include expanded count pro- grams, roadside intercept surveys, freight facility surveys, and stakeholder interviews. The fol- lowing summarizes these activities: · Vehicle Classification Count Programs. Generally, vehicle classification counts are the easi- est type of local data to collect. They can be collected at a relatively low cost and are useful for identifying critical corridors, monitoring growth in truck activity, and validating models. MPOs should work closely with state DOTs so as not to duplicate efforts. Counts on nonstate facilities (especially major arterials and local roads that connect to major freight facilities) are good candidates for local data collection. · Roadside Intercept Surveys. Roadside surveys are useful to get an idea of commodities that are moved on key facilities as well as for getting origin-destination data. The problem with roadside surveys is that there are very few places where they can be conducted without dis- rupting the flow of traffic. Weigh stations, inspection stations, rest areas, and truck stops are some of the types of places where MPOs are conducting roadside surveys. It may be possible to find these types of places on major roads entering and exiting a region so these are used for this type of data collection. · Freight Facility Surveys. Interviews or mail out surveys can be conducted to get information on the volumes and types of goods that are handled at major facilities. This can be useful to develop trip generation data. · Stakeholder Surveys. A limited number of interviews should be conducted with key stake- holders to gather detailed information that can be used to qualify and describe the quantita- tive datasets described. One of the key activities that will be addressed by this effort will be the development of specific logistics patterns and supply chain management techniques. Step 3. Identify and review available analysis tools. There are many types of analysis tools in use today to support transportation planning and programming activities. Before specific data collection activities begin, it is important to understand the extent that these tools are available
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3-54 Guidebook for Freight Policy, Planning, and Programming in Small- and Medium-Sized Metropolitan Areas and planned for use in freight initiatives. The selected tools will in part dictate the type of data that will be required. Step 4. Identify and develop new or enhanced analysis tools. Based on a review of the avail- able tools, MPO staff should determine which tools will best support freight program develop- ment. In some instances, this may require enhancements to existing models or development of new models. The development of new models can be a significant undertaking. Staff is encour- aged to work within established models when possible. For example: · Travel Demand Model. An existing travel demand model may or may not have truck assign- ments. If it does, staff should review the development process and data requirements. If it does not, staff should work with the modeling staff to ascertain the requirements necessary to develop one. · Economic Development Model. There are a variety of economic impact models. Some pro- vide sketch tool planning, others consist of data intensive input and output elements which yield benefit-cost ratios. If an MPO does not currently have an economic impact model, staff should review applicability of models used by counterparts in other locations. · Air Quality Model. Development of an emissions inventory is an important element of regional planning. Most MPOs have some experience in this arena. The typical mobile source analysis focuses on highways, including trucks. Emissions factors also are available for other modal vehicles. MPO staff should review available models and data to determine what is avail- able to measure the impact of freight operations. Step 5. Conduct data collection. MPO staff should develop and implement a data collection program designed to enhance existing data and support the development and use of individual tools and models. Steps 1 through 4 describe the types of activities that the data collection pro- gram will support. Step 6. Integrate data into key activities and established tools to support development and maintenance of the freight-related activities addressed by this Guidebook. This final step should effectively manage and integrate the data collection and tool applications, as appropri- ate, to support the subject areas defined and discussed in this Guidebook. Common Issues and Potential Solutions There are several key challenges that impact the development of a successful data collection program and the effective use of quantitative tools and models. These challenges include avail- able funding, level of staff expertise, soliciting input from private partners, maintaining the pro- gram over time, and the need to support multiple activities. The following summarizes the key challenges and offers potential solutions. Common Issue Potential Solution Funding. The development and implementation Investigate cost-effective sources of freight data and of a comprehensive data collection program and tools. There are a number of publicly available freight the tools and models it supports are significant data sources and tools that can be useful to MPOs undertakings by MPO staff and its partners. Data and that have minimal costs. In addition, state DOTs, collection can be costly, as can be tool and model FHWA, and other agencies are potential sources of development. freight data and in many cases are sources of tools and analytical support. There are many opportunities for MPOs to combine different data sources to develop a more comprehensive understanding of freight movements in their area.