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34 Guidebook for Understanding Urban Goods Movement Exhibit 4-5. Integrating node data for travel demand modeling and other planning issues. Proprietary sources of freight facility data also are available and include specific estimates about the volume of shipments produced and received at each facility. Typically these datasets are modified versions of business establishment data from sources such as InfoUSATM, Harris InfoSource, or ThomasNet. Typically, secondary data sources about facilities can be supplemented through online, phone, or mail surveys. There are field examples of study efforts wherein the largest facilities (top 20 per- cent by number) produced 80 percent or more of the total freight flow volumes for a given study area. These instances of the Pareto principle (the 80/20 rule) suggest that concentrating survey efforts on the very largest commodity producing facilities in an urban area is an efficient, cost- effective manner for improving the quality of freight facility data. Large freight facilities also can be productive locations for conducting surveys to determine local bottlenecks or other opera- tional issues affecting truck movements in a local area. Agency studies have had success conduct- ing break-room surveys at local truck terminals to hear from drivers about operational issues they face in making regional deliveries. Exhibit 4-5 provides some guidance on how primary and secondary node data can be integrated to address urban freight planning needs. Freight Network Data Freight network data helps define major route patterns and critical infrastructure being used to convey freight shipments through the various modal systems. Truck counts are probably the most common data element collected by public planning agencies that contribute network information about freight. Heavy truck counts can provide information about the key network elements used for freight movements and the associated infrastructure demands on various

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Using Freight Data for Planning 35 Exhibit 4-6. Freight network data. Source: Wilbur Smith Associates. highway segments. Other elements of network data include rail line capacity, inland waterway capacity (including locks and dams), port throughput capacity, posted speeds, and weight and dimension limitations on bridges and pavements. See Exhibit 4-6. In the urban context, it is likely that freight network data is most pertinent to highway net- works that service the key freight nodes across all modes, such as rail intermodal yards, ports, airports, manufacturing facilities, and distribution centers. From a freight movement stand- point, network roles should be a central part of planning a region's transportation system and should be managed both developmentally and operationally. Developmentally, freight networks should be protected by proper zoning, building permits, and enforcement, so that key network elements are capable of sustaining truck traffic volumes effi- ciently. Road geometry, pavement structures, and bridge designs should be planned to accommo- date large or heavy vehicles, with appropriate turning radii, height clearances, and passing points. Operationally, freight networks should be managed for productive freight movements. In urban areas traffic signals on freight network routes should be timed for truck movements from known freight generators and receivers. Construction activities should avoid disrupting primary and relief routes simultaneously, and construction, as far as practical, should be coordinated with industry, avoiding commercially sensitive time periods (like month's end) and understanding the time pat- terns of line-haul and city freight schedules. Exhibit 4-7 provides an example of how primary and secondary data sources can be used to help identify bottlenecks on urban freight networks. To support the developmental and operational elements of freight networks requires data such as average speed by route, time of day, and seasonal truck traffic. Most of this data is collected by planning agencies through roadside data collection, surveys, or increasingly through advanced technology. A new form of network data has emerged on the market because of such technolog- ical changes. Today, many trucking companies and private carrier fleets use global positioning systems (GPS) to keep track of driver and equipment movements. Vendors of GPS and fleet man- agement software are packaging the data in formats that allow public agencies to examine the net- work choices made by truck drivers operating in urban areas and across the country. FHWA has been working with ATRI to present truck performance data on some of the nation's key Interstate highways. The FHWA/ATRI "Freight Performance Measures" (FPM) project now provides access to online performance data that can be accessed at http://www.freightperformance.org. Private sources of vehicle tracking data also are emerging as GPS data become more available via cell phone networks. INRIX is one example of a proprietary vendor that can develop customized